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Some External Diseconomies Of Urban Growth And Crowding: Los Angeles

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Some External Diseconomies Of Urban Growth And Crowding: Los Angeles

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Content 70-19,107 BECHDOLT, JR., Burley Vincent, 1935- SOME EXTERNAL DISECONOMIES OF URBAN GROWTH AND CROWDING: LOS ANGELES. University of Southern California, Ph.D., 1970 Economics, general University Microfilm s, A XEROX Company , Ann Arbor, M ichigan © Copyright by BTJRLEY VINCENT BECHDOLT, JR. 1970 THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED SOME EXTERNAL DISECONOMIES OF URBAN GROWTH AND CROWDING: LOS ANGELES by Burley Vincent Bechdolt, Jr. A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (Ec onomics) June 1970 UNIVERSITY OF SOUTHERN CALIFORNIA T H E G R A D U A TE S C H O O L U N IV E R S IT Y PA R K LO S A N G E L E S , C A L I F O R N IA 9 0 0 0 7 This dissertation, written by Burl ey Vine entBe ch.dolt_Jjr.... under the direction of Dissertation Com mittee, and approved by a ll its members, has been presented to and accepted by The Gradu ate School, in p a rtia l fulfillm ent o f require ments of the degree of D O C T O R O F P H IL O S O P H Y I n O Dean Date Jme.J-2.7-Q DISSERTATION COMMITTEE ACKNOWLEDGEMENTS In addition to my Chairman, Dr. John H. Niedercorn, and the other members of my dissertation committee, Dr. Gerhard Tintner and Dr. Ira M. Robinson, I would like to acknowledge my appreciation to others who have provided direct or indirect assistance during the course of this study and the writing of this dissertation. Mr. Glenn Johnson and his staff of the City of Los Angeles, Department of City Planning, Systems and Data Services Division provided much of the census tract data used in the analysis of external diseconomies of crowding presented in Chapter IV. Mr. Robert Troy and his staff of the Computer Center at California State College, Los Angeles supplied data services. Mr. Paul Greek provided special computer programming services. Finally, I want to thank my wife, Margaret, for her assistance in data tabulation and typing and for her patient encouragement throughout this study. TABLE OF CONTENTS Chapter I. II. III. IV. INTRODUCTION................................ Urban Growth and Urbanization of the United States Some External Effects of Urban Growth Purposes of the Dissertation Scope, Methodology, and Organization of the Dissertation THEORETICAL CONCEPTS ....................... Welfare Economics and External Effects Location Theory and External Effects Land Use Theory and External Effects Urban Economic Growth, Urban Growth, and External Effects SOME EXTERNAL DISECONOMIES OF URBAN GROWTH OF THE LOS ANGELES AREA .................. Population and Economic Growth Land Values Traffic Congestion Air Pollution Crime Government Expenditures SOME EXTERNAL DISECONOMIES OF CROWDING IN LOS ANGELES, 1960 ......................... Population Density and Overcrowding Commercial Employment Density and Unemployment Substandard Housing Crime Communicable Diseases Separation and Divorce V. EVALUATION AND CONCLUSIONS APPENDIX . BIBLIOGRAPHY LIST OF TABLES Table Page 1. Gross National Product, Population, Urban Population, Population Density and Number of Urban Places of the Continental United States, Census Years 1790 to i960 . . 3 2. Population, Los Angeles and Los Angeles County, 1850 to 1 9 6 8 ..............................16k 3. Total Civilian Employment, Total Unemploy ment, and Total Civilian Labor Force, Los Angeles County, 1958 to 1968 . . . . . . 172 k. Manufacturing Employment and Manufacturing Establishments, Los Angeles and Los Angeles County, 1939, 19^7, 195^, 1958, and 1963 175 5. Value Added in Manufactures and New Capital Expenditures by Manufactures, Los Angeles and Los Angeles County, 1939, 19^-7, 195^-, and 1958 to 1965, Current and Constant Dollars........... 176 6 . Area and Population Density, Los Angeles and Los Angeles County, 1850 to 1968 .... 180 7. Assessed Valuation and Estimated Market Value of Land Subject to Local Taxation, Los Angeles County, i960 to 1967, Current and Constant Dollars ................. 186 8. Coefficients of Correlation and Determina tion, Estimated Market Value of Land and Population, Real Per Capita Personal Income and Real Investment by Manufactures, Los Angeles C o u n t y .............................. 190 9. Total Vehicle Miles, Street Miles, and Vehicle-miles per Street Mile, Los Angeles, 1957 to 1967......... .................. 192 v 197 204 20 5 209 212 216 217 219 222 224 225 Coefficients of Correlation and Deter mination, Vehicle-miles per Mile of Street and Population and Real Per Capita Personal Income, Dos Angeles . Emissions of Air Pollutants Per Day by Source of Pollutant, Los Angeles County, Selected Years from 1956 to 19^9 .......... Motor Vehicle Emission of Air Pollutants Per Day by Type of Pollutant, Los Angeles County, Selected Years from 1940 to 1968 Coefficients of Correlation and Determina tion, Motor Vehicle Emissions of Air Pollutants per Day and Population, Real Per Capita Personal Income, and Vehicle- miles Driven in Los Angeles, Los Angeles County ......................................... Number of Crimes and Crime Rates and Percen tage Changes by Type of Crime, United States, 1968 .................................. Crime Rates by Type of Crime, United States, Cities over 250,000, Suburban and Rural, 1968 ........................................... Crime Rates hv Type Crime, Cities by Population Siz<; 968 ........................ Crime Rates by Type of Crime, Standard Metropolitan Statistical Areas with Population of 1,000,000 or More, 1968 . . Crime Rates for All Major Crimes Combined, Los Angeles, Los Angeles - Long Beach SMSA, California, and United States, 1958 to 1968.................................... Crimes, Los Angeles, 1957 "to 1 9 6 8 ............ Crime Rates by Type of Crime, Los Angeles, 1957 to 1968.................................... Table Page 21. Coefficients of Correlation and Determina tion, Crimes Against Property Per Capita and Population, Real Retail Trade Trans actions, and Employment in Retail Trade in Los Angeles County, Los Angeles...........234 22. Total and Per Capita Expenditures, County of Los Angeles, Fiscal Years 1959-60 to 1966-67 ......................................... 239 23. Total and Per Capita Expenditures, City of Los Angeles, Fiscal Years 1947-48 to 1966-67j Current and Constant Dollars .... 240 24. Coefficients of Correlation and Determina tion, Real Per Capita Expenditures of the County of Los Angeles and the Population and Real Per Capita Personal Income, Los Angeles C o u n t y ................................ 241 25. Coefficients of Correlation and Determina tion, Real Per Capita Expenditures of the City of Los Angeles and Population and Real Per Capita Personal Income, Los Angeles............. 243 26. Land Use Acreages and Percentages, Los Angeles, i960 ............................. 256 27. Population, Gross Area, and Population Density by Section and Statistical Areas, Los Angeles, April 1, i9 6 0 .................... 257 28. Statistics and Significance Tests, Population Density Function .............................. 263 29. Statistics and Significance Tests, Over crowding Function......................... . 267 30. Statistics and Significance Tests, Nonwhite Overcrowding Function ......................... 269 31. Statistics and Significance Tests, Commer cial Employment Function ..................... 272 vii Table Page 32. Statistics and Significance Tests, Unem ployment Function.................................275 33* Statistics and Significance Tests, Substan dard Housing Function .......................... 278 34. Statistics and Significance Tests, Nonwhite Substandard Housing Function ................. 280 35. Statistics and Significance Tests, Rate of Crimes Against Property Function ............ 285 36. Statistics and Significance Tests, Rate of Crimes Against Persons Function .............. 288 f . 37* Statistics and Significance Tests, Tuberculosis Rate Function ................... 292 38. Statistics and Significance Tests, Mumps Rate Function..................................... 293 39* Statistics and Significance Tests, Measles Rate Function..................................... 29^- 40. Statistics and Significance Tests, Separa tion and Divorce Function ............ 300 LIST OP ILLUSTRATIONS Figure Page 1. United States Gross National Product, Census Years 1910 to i960, 1957“59 Dollars ............................................ 5 2. Total and Urban Populations of the Continental United States, Census Uear s 1790 to i9 6 0 .............................. 6 3. Urban Population as a Percentage of Total Population of the Continental United States, Census Years 1790 to i960 . 7 4. Population Density of the Continental United States, Census Years 1790 to i9 6 0 ............ 8 5 . Urban Places in the Continental United States, Census Years 1790 to 1 9 6 0 ...................... 9 6 . Product Transformation C u r v e .......................40 7. Utility Possibility Curves ....................... 41 8 . Social Welfare Indifference C u r v e s ................44 9. Utility Frontier ................................... 46 10. Utility Frontier and Social Welfare Indifference Curves .............................. 47 1 1 . Demand Cone of a P r o d u c e r ............................ 64 12. Demand and Long-run Average Cost Curves of a P r o d u c e r .......................................... 65 13. Bid Rent C u r v e ........................................ 75 14. Aggregate Rent S u r f a c e ...............................76 15* Bid Rent Curves for Two P r o d u c t s .................. 78 16. Bid Rent Curves for Three P r o d u c t s ................81 ix Figure Page 17* Total Revenue as a Function of1 Distance .... 84 18. Price and Cost Curves of a Typical Commercial F i r m ....................................86 19* Bid Rent Curve for a Particular Commercial Land U s e ...........................................87 20. Isoquant Curves and Total Outlay Curves of a Commercial Firm at the Center of the City and at a Given Distance from the Center . . . 88 21. Total Revenue and Total Cost Curves at Differ ent Distances from the Center of the City . . 90 22. Bid Rent Curves for Three Commercial Industries........................................ 91 23. Total Revenue and Total Cost Curves of a Manufacturing F i r m ...............................93 24. Isoquant Curves and Composite Isocost Curves for a Manufacturing F i r m ........................9^ 25. Budget Constraint and Indifference Curve for Housing Services and Other Goods and Services...........................................99 26. Bid Rent Curves and Rent Gradient............... 102 27. Urban Production Possibility Curve ......... .119 28. Some Possible Shifts in the Urban Production Possibility Curve .... 121 29. Margin L i n e s .......................................139 30. Population, Los Angeles County and Los Angeles, 185O to 1 9 6 8..........................167 31. Total Civilian Labor Force and Total Civilian Employment, Los Angeles County, 1958 to 1968 173 32. Employment by Industrial Group, Los Angeles County, 19^-9 to 1 9 6 6 ........................... 174 x Figure Page 33* Total and Per Capita Personal Income, Los Angeles County, 1947 to 1968, 1957-59 Dollars................. 179 34. Estimated Market Value of Land Subject to Local Taxation, Los Angeles County, i960 to 1967, 1957-59 Dollars.............................187 35* Vehicle-miles Per Street Mile, Los Angeles, 1957 to 1 9 6 7 .......................................193 36. Total Motor Vehicle Emission of Air Pollutants Per Day, Los Angeles County, Selected Years from 1940 to 1 9 ^ 8 ................................. 207 37. Percentage Change in Crimes per 100,000 Population and Population Relative to i960 by Type of Crime, United States, i960 to 1968 213 38. Gross and Net Values of Stolen Property, United States, 1957 to 1968, Constant Dollars..............................................215 39. Crime Rates by Type of Crime, Los Angeles, 1957 to 1968 226 40. Total Federal, State, and Local Government Expenditures, 1950 to 1966, 1957-59 Dollars..............................................237 41. Per Capita Government Expenditures, United States, California, Los Angeles County, and Los Angeles, 1950 to 1968, 1957-59 Dollars..............................................238 42. Statistical Areas, Los Angeles ................. 253 CHAPTER I INTRODUCTION This dissertation is a study of some of the economic and social effects of urban economic growth, urban population growth, and urbanization, with parti cular emphasis on detrimental effects of urban growth and crowding in Los Angeles, California, hereinafter called Los Angeles. This study is part of what might be called a study of the "economics of crowding,! ' As an urban area undergoes economic growth, people and capital tend to migrate to the area in search of employment opportunities. Indeed, cities can be viewed as open economies producing multiple products using a variety of economic resources and consuming, saving, and trading their product. But as this process of agglomeration of human and capital resources pro gresses, the increased demands for land for many different uses in the area result in a reallocation of increasingly more dear and productive urban land. The general result is increasing population density. The central hypothesis of this dissertation is that this very process of 2 increasingly more compact living in urban areas is at least a partial cause of* many of the problems that are part of the current "urban crisis" in the United States. The purposes of this chapter are (l) to present a brief survey of population growth and urbanization in the United States and its metropolitan areas, (2) to discuss the nature of external effects of urban growth and some examples of such effects, (3) to state the px’ in- cipal purposes of this dissertation, and (4) to outline the scope, methodology and organization of this disser tation. Urban Growth and Urbanization of the United States Economic growth of the United States has been accompanied by three interesting demographic phenomena: (l) urban growth, (2) urbanization, and (3) increase in the number of urban places.1 Table 1 and Figure 1 show the gross national product (GNP) of the United States in constant dollars for census years from 1910 to i960; Table 1 and Figures 2 through 5 show the total population, urban population, urban population as a percentage of total population, population density, and number of urban places of the United States for census years 1790 through i960. Figures 1 through 5 suggest that all of these TABLE 1.— Gross National Product, Population, Urban Population, Population Density and Number of Urban Places of the Continental United States, Census Years 1790 to i960 Year Gross National Product (Billions of 1958 Dollars) Population Population Density (Persons per Square Mile) Urban Places Total (Thousands of Persons) Urban Number (Thousands of Persons) Percentage of Total 1790 $ • • . 3,929 202 5-1 ^.5 24 1800 • • • 5,308 322 6.1 6.1 33 1810 • ■ • 7,240 525 7.3 4.3 46 1820 « • • 9,638 693 7.2 5.6 61 1830 • • • 12,866 1,127 8.8 7.4 90 1840 • • • 17,069 1 ,845 10.8 9.8 131 1850 • it 23,192 3,544 15.3 7.9 236 1860 • • • 31,443 6,217 19.8 10.6 392 1870 • • • 39,818 9,902 24.5 13.4 663 1880 • • • 50,156 14,130 28.2 16.9 939 1890 • • • 62,948 22,106 35.1 21 .2 1,348 1900 « • * 75,995 30,160 39.7 25.6 1,737 1910 120.1 91,972 41,999 45.7 31.0 2,262 1920 i4o,o 105,711 54,158 51.2 35.6 2,722 1930 183.5 122,775 68,955 56.2 41 .2 3,165 (Continued) TABLE 1.--(continued) Year Gross National Product (Billions Total of 1958 (Thousands Dollars) of Persons) Population Urban Population Density (Persons per Square Mile) Urban Places Number (Thousands of Persons) Percentage of Total 1940 $227.2 131,669 74,424 56.5 44.2 3,464 1950 335.3 150,697 89,749 59.6 50.7 4,054 1960 487.7 178,464 112,531 63.O 60.1 5,022a New Urban Definition 1950 $. • » « • • • 96,468 64.0 • • 4,741 1960 • • • 1 • • • 124,699 69.9 • • 6,04la aIhcludes Hawaii and Alaska, Sources: U, S, Bureau of the Census, Long Term Economic Growth, 1860-1965 (Washington, D, C.: U. S. Government Printing Office, 1966), A2. U, S, Bureau of the Census, Historical Statistics of the United States, Colonial Times to 19W (Washington, D. C, : u] s"! Government Printing Office, i960), Series A 17-21, A 34-50, and A 181-191. U, S. Bureau of the Census, Statistical Abstract of the United States. 1962 (Washington, D. C,: U. S. Government Printing Office, 1962), Tables 1, 12, and 13. Gross National Product (Billions of* Dollars) 400 - 300 ' 250 - 200 ' 150 - 100- 1910 1920 1930 1940 1950 1960 Source: Table 1. Pig. 1.--United States Gross National Product, Census Years 1910 to i960, 1957-59 Dollars 6 Total Population (Millions of Persons) 180- 1 60- 1 20- 1 00 - 80- Total Urban 60- 20- o i - - T------ t------ i i...i i 1780 1800 1820 1840 1860 1880 1900 1920 19^0 i960 1980 Source: Table 1. Fig. 2.— Total and Urban Populations of the Continental liiited States , Census Years 1790 to i960 Percentage Urban 90 80 70 60 50 30 20 1780 1800 1820 1840 1860 1880 1900 1920 1940 i960 198O Source: Table 1. Fig* 3*— Urban Population as a Percentage of Total Population of the Continental United States, Census Years 1790 to i960 8 Population Density (Persons per Square Mile) 70- 60- 20- 1780 1800 1820 1840 1860 1880 1900 1920 1940 i960 1980 Source: Table 1 . Fig. 4.— Population Density of the Continental United States, Census Years 1790 to 1960 9 Urban Places 5 ,000- 3,500- 3,000- 2,000- 1 ,000- 500- 1780 1800 1820 1840 i860 1880 1900 1920 1940 i960 1980, Source:, Table 1. Fig. 5*— Urban Places in the Continental United States, Census Years 1790 to 1960 i 10 variables have similar trends. The gross national pro duct since 1910 is clearly associated with total popula tion (p), urban population (Pu) , percentage urban population (^Pu ), and urban places ( u ), as shown by the correlation coefficients below. r log P log Pu log $PU log U log GNP 0.986a 0.974a 0.979a o,986a aSignificant at the 0.001 level. Urban growth has occurred in every region and in virtually every state in the United States each decade since 1900. Despite this nearly ubiquitously steady urban growth, urbanization of some regions and several 3 states has not always increased each decade since 1900. This is especially characteristic of states in the New England, Middle Atlantic, East North Central, and Pacific regions and of certain states in the South Atlantic and Mountain regions. However, between 1900 and i960, only three states--Massachusetts, Rhode Island, and Delaware (only with the previous urban definition)— deurbanized. The urbanization of the states is also reflected in the fact that the smallest rate of urbanization increased from 6 per cent for Idaho in 1900 to 33 per cent for 11 Delaware in i960 (35 pen cent for North Dakota in 19^0 using the new urban definition). The increase in the total number of urban places in the United States from 1790 to i960 has been accom panied by a gradual, decade-by-decade, absolute and relative redistribution of urban places by population 4 size as a result of urban growth. The percentage of the United States population living in urban places has grown from 5 per cent in 1790 to 63 per cent in i960 (70 per cent using the new urban definition) As United States urban growth took place, suburbanization and "sprawl1 1 of larger cities occurred, the previously rural hinterlands became increasingly urban in character, and in several regions called megalopoli, it became increasingly difficult to distin guish one urban area from another. Standard metropolitan areas (SMA), now called standard metropolitan statistical areas (SMSA), were defined by the Bureau of the Census to provide a more representative geographic urban area.^ Table A-7 shows the population of the New York and Chicago standard consolidated areas and the 40 largest standard metropolitan statistical areas in i960 and their central cities for each census year from 1900 to i960. During each decade from 1900 to i960, the two standard 12 consolidated, areas and each, of1 the 40 largest standard metropolitan statistical areas in 1960 increased in population. However, the population of the central cities of many of these standard metropolitan statistical areas, especially those in the northeastern and midwestern regions, decreased during the 1940-1950 and, especially, the 1950-1960 periods, reflecting the postwar out migration of population from many central cities. Table A-8 shows the land area and population density of the New York and Chicago standard consolidated areas and the same 40 standard metropolitan statistical areas as listed in Table A-7> and their central cities for census years 1940, 1950, and i960. Decade-by-decade changes in population density figures for many of the standard metropolitan statistical areas do not accurately reflect the actual population densities because of often very large changes in the land areas resulting from changes in the geographic boundaries of the areas. Because central cities typically do not experience large changes in land area between census years, population density figures for central cities provide more accurate measures of the actual changes in population density. 13 Some External Effects of Urban Growth. Population growth, that accompanies the economic growth of an urban area increases the size of the local market and typically tends to provide a more diversified set of occupational skills. The increased demand for products of local firms and the increased potential for specialization and increased productivity within the urban area allow decreasing-cost firms in the area to realize internal economies of large-scale production. Public service industries, such as those providing water, gas, electricity, as well as local government, are examples of industries that can usually realize internal economies of large-scale production or operation as urban growth occurs, at least for moderate increases in urban population. But urban growth also produces opportunities for both beneficial and detrimental external effects on firms and industries and on urban residents. Benefits that accrue to existing or potential firms in an urban area that the firms do not have to pay for are called external economies; costs of firms1 pro duction or operation that are incurred by those outside such firms are called external diseconomies. Benefits that accrue to existing or potential individuals in an urban area that the residents do not pay for can be 1 k called external utilities; detrimental effects to such, individuals caused by the actions of others can be called external disutilities. (Hereinafter, the terms "external economies" and "external diseconomies" will be used to denote respectively, external effects that are beneficial to firms or individuals and those that are detrimental to firms or individuals.) Over time, as an urban area experiences urban growth, the local market for goods and services becomes larger and more diversified, and production becomes more roundabout as greater specialization leads to greater vertical industrial specialization and a growing urban product. As the urban population increases, residents begin to enjoy greater choice of consumer goods and services, such as services of colleges and universities, museums, sports stadia and other entertainment and cul tural facilities, hospitals, research centers, and many other facilities that can be supported only by a large market. Furthermore, large urban areas usually provide better occupational and employment opportunities and retraining facilities. Firms in a growing urban area benefit from lower recruiting and, for some, training costs of a concentrated local skilled labor force and 15 from the lower cost of transportation and communication resulting from the proximity of suppliers, customers, and business services. However, urban growth not only induces expansion of residentiary industries but also provides external economies that stimulate the further expansion and diversification of the export sector, that group of firms and industries in an urban area that produces products and services that are exported from the urban area. Industries that are attracted to large urban centers to take advantage of these economies are called external- economy industries. Firms in these industries often operate under uncertain market conditions and are typically (l) relatively small, (2) single-plant firms producing (3) non-standard products under (b) short pro duction schedules (5) without heavy investment in specialized capital equipment.^ These firms must remain small and clustered in order to make and implement swift decisions. Because these industries often produce new and untried products or new varities of older products and tend to change their production methods frequently, they cannot afford to invest in specialized capital and typically have low capital-labor ratios. Consequently, the short-term growth of external-economy industries 16 tends to talce the form of increased employment, rather g than large increases in productivity. Because of the relatively low capital investment in these industries, entry is relatively easy. Ease of entry, in turn, tends to keep profits and wages low, thereby discouraging capital investment and depressing the rate of growth of 9 labor productivity. In the long run, as new technology is developed, some existing external-economy industries in an urban area tend to spatially separate their opera tions according to functions with relatively standard operations being conducted at low-rent locations away 1 O from the high-rent urban centers. Firms in external-economy industries tend to cluster in order (l) to share common specialized services (2) to obtain these services quickly, and (3) "to maintain face-to-face contact with suppliers, competitors, and 1 1 customers. Approximately 17 pear cent of all national- market industries in the United States in 195^ were external-economy industries, and about 15 per cent of the total manufacturing employment in the United States was 1 2 in external-economy industries. Typical examples of external-economy firms and industries in the New York metropolitan area include high-fashion women's clothing manufacturers, leather goods manufacturers, jewelers, 17 publishing companies, job printing companies, military electronic equipment and component manufacturers, finan cial institutions, central offices, and cultural services such as art museums, theaters, and music and concert 1 3 halls. J In large and growing urban areas, external diseconomies produced by firms and individuals are intensified as the population of such areas increases. External diseconomies of urban areas not only contribute to the misallocation of resources, but tend to retard urban economic growth and population growth. In the large urban centers in the United States, misallocation effects seem to have outweighed the depressing effects on urban economic growth and population growth; the preceding section shows that the total and metropolitan populations of the United States have grown steadily and have become increasingly more urbanized despite external diseconomies of urban growth. External diseconomies are not taken into account by existing or potential firms and industries in urban areas in determining their locations and levels of pro duction or operation. Nor do the external diseconomies resulting from residential location, movement, and con sumption decisions of existing or potential residents of an urban area enter into their decisions. Decisions 18 concerning location, production, and consumption are based on private benefits and costs, not social benefits and costs. Therefore, whenever external diseconomies result from the decisions of firms and individuals, the 1 it costs of their decisions tend to be underestimated. For example, when a firm is faced with the decision as to whether or not to locate in the central business district of an urban area, the firm can be expected to consider only the private benefits and costs of locating in the central business district, not, say, the increased traffic congestion and noise caused by its employees each morning and evening in making their journey-to- work.^ ^ Each individual who considers migrating to an urban area can be expected to base his decision on the private benefits and costs of his alternatives, not upon the external effects of his decision, such as increased traffic congestion, greater natural-resource pollution, higher rents, decreased open space, higher cost of public services, higher insui’ ance rates, increased noise, and other social costs that typically accompany urban growth. ^ The problem of congestion of urban transportation systems is very common and often acute in rapidly 19 growing urban areas. The problem can be viewed, as a 1 7 pricing problem involving external diseconomies. For example, each user of an urban freeway or expressway system needs to consider only the private benefits and costs of his marginal contribution to increased traffic in the system, not the increased congestion, loss of time spent travelling, and increased noise and dirt experienced by other motorists. Purposes of the Dissertation This dissertation contains a summary of economic theoretical concepts that relate to external effects of urban economic growth, urban growth, urbanization, and crowding and presents the results of a study of selected external diseconomies of urban growth of Los Angeles and Los Angeles County and of differences in the degree of selected external diseconomies among subareas of Los Angeles. Correspondingly, the principal purposes of this dissertation are: To summarize economic theoretical concepts relating to external effects of urban economic growth, urban growth, urbanization, and crowding. To study the relationships between economic, demographic, and social variables that are believed to be associated with selected external diseconomies of urban growth in Los Angeles and Los Angeles County. 20 To study the relationships between economic, . demographic, and social variables that are believed to be associated with differences in the degree of selected external diseconomies among census tracts and statistical areas in Los Angeles. Scope. Methodology, and Organization of the Dissertation This dissertation is organized into five chapters including this introductory chapter. Chapter II is a summary of economic theoretical concepts that are related directly or indirectly to the external effects generated or realized by firms, industries, and individuals in urban areas. Chapter III presents a statistical-historical description of the urban growth of Los Angeles and Los Angeles County and statistical analyses of some of the external diseconomies produced by this growth. Chapter IV presents the results of a cross-sectional, multiple- regression analysis of selected external diseconomies in Los Angeles in i960. Chapter V presents a general evaluation and some conclusions of the study. Footnotes to Chapter 1 "Urban growth." refers to the generally sustained increase in the absolute population of an urban area. "Urbanization" refers to the generally sus tained increase in the percentage of the national, regional, or metropolitan area population that is urban. Before the 1950 U. S. Census of Population, urban places were incorporated places with popula tions of 2,500 or more persons and other places considered as urban places under special rules relating to population size and density. Beginning with the 1950 U. S. Census of Population, urban places were incorporated cities, towns, villages, or boroughs, larger unincorporated places outside urban areas having a population of 1,000 or more persons, and towns in New England, townships in New Jersey and Pennsylvania, and counties recog nized as urban. The only exceptions are (l) a decrease in the urban population of New Hampshire from 255,000 to 250,000 between 1910 and 1920, (2) a slight decrease in that of Delaware from 148,000 in 1950 to 145,000 in i960 (if the current definition of urban popu lation is used, there was an increase from 199,000 to 293,000), and (3) a decrease in that of the District of Columbia from 802,000 in 1950 to 764,000 in i960. See Tables A-1 and A-2 in the appendix for the urban population of the United States, regions, and states for each census year from 1900 to i960. See Tables A-3 and A-4. See Table A-5• See Table A-6. For the definition of standard metropolitan areas, see U. S. Department of Commerce, Bureau of the Census, Standard Metropolitan Statistical Areas (Washington, D. C.: U. S. Government Printing Office, 1967). 22 7. Raymond Vernon, Metropolis 1985 (Cambridge, Massachusetts: Harvard University Press, i960), pp. 68-73. 8. Ibid.. 77. 9. Vernon, Metropolis 1985. pp. 77-78. 10. For a related ' ’filter-down" hypothesis of indus trial location, see Wilbur R. Thompson, "Internal and External Factors in the Development of Urban Economies," in Issues in Urban Economics, ed. by Harvey S. Perloff and Lowdon Wingo, Jr. (Baltimore: The Johns Hopkins Press, 1968), pp. 55“57• 11. Vernon, Metropolis 1985. p. 73* 12. Vernon, Metropolis 1985. p. 5, Table 2. Robert M. Lichtenberg, One-Tenth of A Nation (Cambridge, Massachusetts: Harvard University Press, i960), p. 39, Table 3. 13. Vernon, Metropolis 1985, pp. 68-73, 80-81, and 96. Lichtenberg, One-Tenth of A Nation, pp. 58 and 70. 14. Ezra J. Mishan, The Costs of* Economic Growth (New York: Frederick A. Praeger, Publishers, 1967), p. 75. 15. Mishan, The Costs of Economic Growth, p. 7^« 16. For expositions of some of these external economies, see E. Higbee, The Squeeze. Cities Without Space (New York: William Morrow & Company, T960") and M. Gordon, Sick Cities. Psychology and Pathology of American Urban Life(Baltimore: PenguinBooks, Inc., 1965). 17. Wilbur R. Thompson, A Preface to Urban Economics (Baltimore: The Johns HopkinsPress,19^5), PP* 335-351* Mishan, The Costs of Economic Growth, chap. vii . CHAPTER II THEORETICAL CONCEPTS The purpose of this chapter is to present economic theoretical concepts related directly or indirectly to external effects of large urban size, urban growth, and crowding. The first section is a summary of selected topics in welfare economics and shows the impact of external effects on the conditions for Pareto- optimality and discusses conditions for maximizing a welfare function. The second section discusses concepts from classical location theory on the analysis of the spatial agglomeration of industries (microagglomeration) and from theories and studies of the systematic empirical size relationships among urban areas of an economy (macroagglomeration). The third section is a summary of agricultural, commercial and manufacturing, and residen tial land use theory and theoretical and empirical con cepts relating to the overall pattern or structure of urban land uses. The fourth section is a discussion of topics related to urban economic growth, urban growth, and some of the external effects of urban growth. 23 zh Welfare Economics and External Effects1 Welfare economics is a branch, of economics that deals with the formulation of criteria which can be used to evaluate the social desirability of alternative economic states. Certain fundamental ethical value n judgments are usually accepted in welfare economics. First, each consumer— and only he--is the best judge of his own welfare. Second, social welfare depends only upon the welfare of the persons comprising the society. Third, social welfare is increased if the welfare of at least one person is increased without decreasing the wel fare of any other person. Fourth, if an increase in the welfare of at least one person can be achieved only by decreasing the welfare of at least one other person, then (1) policy makers can refrain from selecting among alter native economic states until an acceptable social welfare function is specified (until all alternative states have been ranked according to some set of value judgments), (z) policy makers can make value judgments about the welfare associated with a ranking of particular alterna tive economic states, or (3) pol icy makers can apply a principle of compensation. Welfare economics deals principally with ques tions of the social desirability of the distribution of 25 resources among alternative uses &nd the distribution of* commodities among consumers within a framework of static general equilibrium theory. Pareto Optimality, Competition, and Imperfect Competition Positive economic theory derives the necessary conditions for economic efficiency and explains why they are met if the economy is a competitive economy without external economies or diseconomies in consumption or production. Theoretical welfare economics explains why these conditions for economic efficiency also meet the welfare criterion of Pareto optimality. The conditions of Pareto optimality in consumption and production are: Any redistribution of consumer goods and consumer-owned resources would reduce the welfare of at least one consumer. Any redistribution of resources within or among firms would reduce the output of at least one firm. The following assumptions are usually made in 3 theoretical welfare economics. Each person in the society consumes some positive quantity of each product and supplies some positive quantity of each resource in the economy, or x_^ ^ 0, where x.. = quantity of product j (j = 1, . . ,,r) ' L' ^ consumed by person i (i = 1 , . . . , n) or quantity of resource j (j = r + 1, . . ,,m) supplied by person i. 26 All products and resources are sufficiently divisible to permit marginal adjustments. Products or resources comprising a class of products or resources are perfect substitutes for one another within each class. All relevant functions are differentiable and have tangency solutions. Xn this section, second-order conditions of utility, pro duction, or welfare maximization are assumed to have been met. In the consumption sector of a competitive economy, consumers are price takers in both product and resource markets and they have no individual influence on prices. Each of the' n consumers in this economy can be assumed to have a utility function U. = U. (x. . , . . . , x. ) (l ) i i v x1’ ’ imy v ' where x_^ . = quantity of product j (j = 1 , . . ,,r) used by consumer i or quantity of resource j (j = r + 1, . . .,m) retained by consumer i which he wishes to maximize subject to his budget constraint j where p. = pric© of product j or of resource j J Y. = income of consumer i 27 The first-order conditions for this constrained maxi mization of utility are that the marginal rates of sub stitution (MRS) among pairs of products consumed or factors retained equal the inverse of the ratios of the prices of the products. s = F 1 (j» k = 1, . . mj J d ij k j Jt k; (3) Because all consumers face the same set of prices, their price ratios must all be the same; consequently, their MRSs must be the same. - * * * & ^ fi, h = 1, . . ., n; i j f c h) (j , k = 1 , . . . , m; j j* k) Equations (4) show that the MRSs of all persons for all pairs of products are the same, which, in turn implies that everyone is on the contract hyperplane (corres ponding to the contract curve for the two-person, two- product economy). Any changes on the contract hyperplane will involve an increase in the utility of at least one person and a decrease in the utility of at least one other person. This condition meets the requirements for Pareto optimality. Different points on the contract hyperplane can be compared only by introducing the 28 value judgment that the evaluator can make interpersonal comparisons of utility. In the production sector of a competitive economy, firms are price takers in both product and resource mar kets and they have no influence on prices. Each of the firms in this economy can be assumed to have a production function Q. = Q.(y. , . . ., y. ) = 0 (5) x i w i 1 ’ i n ' v / where y.. = product j ( j = 1, . . .,r) produced by firm i or resource j ( j = r + 1, . . ., m) used by firm i, where resource y. . = - x. . i j i j The first-order conditions for profit maximization of firm h in a competitive economy are _ _ Li (6) ^yij pk { } "When j and k denote products, equation (6) shows that firm i's rate of commodity transformation between all pairs of products j and k, RPT^^ (j ^ k), equals the inverse ratio of their prices. Likewise, when j and k denote resources, equation (6) shows that firm ifs mar ginal rate of technical substitution of resource j for resource k, MRTSj^, equals the inverse ratio of their prices. If k denotes a product and j a resource, equation (6) shows that the firm i's marginal product of 29 ( X ) resource j used in the production of product k, M P , equals the ratio of the price of resource j to the price of product k. Because all equilibrium prices are given to producers in a competitive economy, the price ratios dis cussed above are the same for each firm. Consequently, the RFT^^, MRTs(1 i^, and Mp (^ are equal for all pro- jk jk ’ jk ducts and all 1 S T firms. In general, ^yik ^ ^hk ( • - u , 1 vr \ /r,\ - r r r : — - ~ r-r x' h “ ^ • * • > N ) (?) d yij O yhj (j, k = 1, . . . , m) Equations (7) meet the requirement for Pareto optimality in two senses. First, any reallocation of resources among firms so as to increase the output of at least one firm will result in a decreased output of at least one other firm. Second, any reallocation of resources within firms so that the aggregate production of at least one product is increased will result in the decreased aggregate production of at least one other product. In summary, a competitive economy without exter nal economies or diseconomies optimizes welfare in the narrow sense that it provides an efficient allocation of resources among alternative uses and an efficient distri bution of products among consumers, and an efficient 30 allocation of* resources fulfills the conditions of Pareto optimality. Within and among all product markets, the MRSs for all consumers equal the MRTSs for all firms and products. Within and among all resource markets, the MRSs for all consumers equals the MPs of each resource for all firms and all products. However, as Ezra J. Mishan points out, a competitive economy without external economies or diseconomies is neither necessary nor suffi- k cient for Pareto optimality. One of the greatest difficulties of using the criterion of Pareto optimality is that it does not pro vide any means of comparing alternative economic states or points on a contract hyperplane. Pareto Optimality and External Effects The Pareto optimality conditions discussed in the foregoing section were derived under competitive condi tions with no external economies or diseconomies of con sumption or production. The absence of external economies or diseconomies of consumption or production implies an atomistic world in which the utility function and productivity of each consumer are independent of the consumption of other consumers and the production functions of all firms are independent of the production of other firms. But even 31 casual observation of consumer behavior and business and industrial behavior indicates that economies are not atomistic; a person's utility and productivity are dependent upon the preferences and consumption of other consumers, and a firm's production function is dependent upon the output of other firms. These interdependencies result in external economies or diseconomies to consumers or firms as consumption of other consumers and production of other firms change. Whenever external economies or diseconomies are present, there is a divergence between social and private benefits or costs that can result in a misallocation of resources. This divergence of social and private returns usually means that there are market imperfections because the price system either does not price or underprices the external benefits or losses. If social and private returns are different in a competitive economy, prices could be adjusted so as to shift resources among alternative uses so as to adjust output from the competitive equilibrium output to an optimal output where the social value of the marginal products (SVMP) of resources are the same in all uses; If social and private returns are different in an imperfectly competitive economy, the private values of 32 the marginal products (VMP) of* resources in alternative uses are different, so that any adjustments in prices to attempt to compensate for the external economies or dis economies may result in an inferior state. Four categories of external economies and dis economies are usually considered: External economies of consumption External diseconomies of consumption External economies of production External diseconomies of production External economies and diseconomies of consump tion result when a change in the consumption of at least one person causes a change in the utility or productivity of at least one other person which is not reflected in the returns of the person or persons producing the change in consumption. In a competitive economy, Pareto optimality may not be achieved even when MRSs of all con sumers are the same, if there are external economies or 5 diseconomies of consumption. External economies and diseconomies of consump tion are very readily observable. Individual consumers1 tastes and consumption patterns are strongly influenced by socially prevalent tastes. Socially influenced tastes 33 and consumption of clothing, housing, food, transporta tion, and recreation in the United States economy are obvious examples. External economies of production result when an increase in the production of at least one firm causes an increase in the production of at least one other firm or an increase in the utility of at least one person. Direct and indirect external economies of production have been identified. An example of direct external economy of an increase in production by a firm is the increase in productivity of employees through training that resulted when the firm had to train more workers in order to expand its production. Other typical examples of external economies of production include the spatial agglomeration of skilled labor force resulting from investment in an area by other firms, existence of fin ancial institutions in an area, presence of firms pro viding business services in the area, and the presence of debt-free public facilities, such as roads and high ways. These are some of the major factors that explain the tendency for firms to agglomerate. An example of an indirect external economy of an increase in production by a firm is the reduction in the price of at least one resource, because, with the increased derived demand for 3k tlie resource, the resource supplier could realize economies of large scale production. External diseconomies of production result when an increase in the production of at least one firm causes a decrease in the production of at least one other firm or a decrease in the utility of at least one person. Two kinds of external diseconomies have been distinguished in the literature on welfare economics: technological and pecuniary external diseconomies of production. A tech nological external diseconomy of production exists when the increased production of at least one firm results in at least one other firm having to use more resources to produce a given output. A pecuniary external diseconomy of production exists when the increased production of at least one firm causes the price of resources to increase, such that at least one other firm is forced to pay higher prices for its resources. Only technological external diseconomies of production are important for welfare economies because they result in changes in resource allocation; pecuniary external diseconomies of production do not alter the allocation of resources and, conse quently, do not increase the social cost of production. However, pecuniary external economies and diseconomies are important for economic growth and development. 35 When external economies and diseconomies of pro duction are considered, Pareto optimality in production necessitates the equality of price and (increasing) social marginal cost (SMC) of all products in all firms as well as equality of the corresponding social rates of product transformation. Social rates of product trans formation are measures of the real opportunity cost to society of producing additional units of products. If each firm producing each product produces those outputs at which prices equal the SMCs, then consumers' MRSs and the corresponding social rates of product transformation will be equal. But if a firm or a person is generating external economies, social marginal benefits will be greater than private marginal benefits and the firm tends not to pro duce as much output or the person tends not to supply as much of a resource as is required to satisfy the interests of society. In the case of the firm, it tends to produce less than the socially optimal output because it has not been adequately compensated. Consequently, resources are underallocated to the production of products whose pro duction generates external economies. In the case of the individual, he tends to supply less than the socially optimum amount of a resource because his compensation is too small. 36 If* a firm or- person is generating external dis economies, social marginal cost exceeds private marginal cost and the firm tends to produce more output and the person tends to consume more than is required to satisfy the interests of society. In the case of the firm, it tends to produce more than the socially optimal output because it does not have to bear all of the costs of production. Consequently, resources are overallocated to the production of products whose production generates external diseconomies. In the case of the individual, he tends to consume more than the socially optimal amount because products are underpriced. Government might use subsidies to encourage firms which generate external economies to increase their pro duction and might use taxes to encourage firms which generate external diseconomies to decrease their production. Ezra J. Mishan suggests that social welfare could be increased by establishing and maintaining separate facilities for those in favor of generating external dis economies and those who prefer not to have to experience 7 them. This concept seems to be a potentially useful tool for urban planning. 37 Welfare Criteria and Functions The basic economic problems of determining what combination of products is to be produced in an economy and how that combination of products is to be distributed are interrelated problems in welfare economics. Depending upon the initial stock of products and the initial dis tribution of income, there are many possible distributions of the aggregate combination of products that can typi cally satisfy the condition of Pareto optimality. With a given set of tastes, alternative patterns of income dis tribution can result in a competitive economy producing at different points on the boundary of the product trans formation hyperplane. Policy decisions concerning what combination of products along the boundary of a product transformation hyperplane and what distribution of pro ducts along the contract hyperplane will be more pre ferable cannot be made without value judgments about the distribution of income. Pareto, Kaldor, Hicks, Scitovsky, g and Bergson have provided alternative welfare criteria. The Pareto criterion, again, is that any change in economic states which increases the utility of at least one person without decreasing the utility of any one else provides an improvement in social welfare. The Pareto criterion deals only with changes which do not 38 involve any decrease in utility by anyone, and, there fore, does not deal with, the problem of interpersonal comparisons of utility. Consequently, it is of no value in comparing changes in states which would increase the utility of at least one person and decrease the utility of at least one person. The Kaldor criterion is a compensation test for changes in economic states in which one or more persons would gain from the change and one or more would lose. The Kaldor criterion is that a change in economic states provides an improvement in social welfare if those who gain from the change in economic states assign a higher monetary value to their gains than the losers do to their losses. The Hicks criterion resembles the Kaldor criterion. The Hicks criterion is that a change in economic states provides an improvement in social welfare if those who would lose if the change were made cannot profitably bribe those who would gain from the change to not make the change. According to the Kaldor-Hicks criteria, gainers only have to be able to pay a compensation to the losers; they do not have to actually make such payments. Utility possibility curves have been used to com pare alternative combinations of products and their 39 distribution. Assume a simplified two-person (A and B) economy in which two products (X and Y) are produced in combination , which is a point on the product trans formation curve, QQ1, in Figure 6. A utility possibility curve, in Figure 7> shows the set of all possible combinations of the utility of A and B, U(a ) and u (b ), that can be obtained by redistributing income along the contract curve, OQ^ in Figure 6, for the given combina tion of products . Figure 6 shows that there is a different contract curve for each point on the product transformation curve QQ1. Consequently, there is a different utility possibility curve for each contract curve. For instance, ^'n F:*-£ure 7 might t>e the utility possibility curve corresponding to the contract curve when the economy produces combination of X and Y in Figure 6. Utility possibility curves can be used to test a proposed change in economic states, say from to , using the Kaldor-Hicks criteria. Suppose that the pro posed change from to would result in a shift from point D on Q-j i*1 Figure 7 to point E on Q^Q^. According to the Kaldor-Hicks criteria, the change from to would be an improvement because following a shift from D to E, A could compensate B (redistribute income from 40 Y Q X Fig. 6.--Product Transformation Curve 4i u (a ) u (b ) o Pig. 7-— Utility Possibility Curves 42 A to B) so that either (l) B is not made worse off and A still gains (point F on 0-2^2^ ’ °r both- A and B are better off (point G on But the Kaldor-Hicks criteria do not necessarily lead to consistent conclusions. Reconsider the proposed change from to assuming that X and Y are distri buted so that point H in Figure 7 represents the original utility combination, and point I on ^'tle combination after the change. The change from Q1 to will not be an improvement because B can compensate A so that either (1) A would be no worse off than if the change from Q.j to had been made and B would be better off than if it had (point J on QJJ ), or (2) both A and B would be better off by not making the change (point K on Q^j ). Xn this case, the Kaldor-Hicks criteria do not indicate whether is to be preferred to or vice versa. The Scitovsky criterion is a double or reversal test intended to remedy the inconclusiveness of the Kaldor-Hicks criteria. The Scitovsky criterion is that a change in economic states provides an improvement in social welfare if both (l) those who would gain from the change assign a higher monetary value to their gains than the losers do to their loss and (2) those who would k3 lose from the change cannot bribe those who would gain to not make the change. These compensation criteria all suffer from an implicit assumption that A and B have the same utility of money function. But this assumption involves an unacceptable interpersonal comparison of utility. Unless compensation is actually paid, the welfare effects of a proposed change in economic states cannot be evaluated. The Bergson criterion is that a change in econo mic states provides an improvement in social welfare if the change results in an increase in a welfare function that reflects a set of explicit value judgments of the welfare evaluator. A social welfare function, ¥, is an ordinal function of the utility of everyone comprising the society in question. Continuing the example of the two-person, two-product economy, the traces or contours of the social welfare function ¥ = ¥(U(A), U(B)) (8) representing different levels of welfare are shown in Figure 8 as social welfare indifference curves, where ¥^> ¥^> ¥^ ^ ¥^. Each social welfare contour shows the combinations of U(a ) and u (b ), that correspond with the set of all combinations of X and Y and all possible distributions of income, which are deemed to be equally satisfying to A and to B. Once such a welfare function U(A) O Fig. 8.--Social Welfare Indifference Curves k5 is defined, the desirability of alternative economic states, including not only the possible combinations of products X and Y, but also their distribution between A and B, can be compared. The concept of a utility frontier is especially useful for determining the econo mic state that maximizes the social welfare function. A utility frontier (Figure 9) is simply the envelope of the set of all utility possibility curves, such as Q1 , and in Figure 7 which in turn reflects the set of all possible combinations of X and Y on the product trans formation curve, QQ1 in Figure 6. That combination of X and Y, Q*, corresponding with the combination of U(a ) and u (b ) at the tangency of the utility frontier and the highest social welfare indifference curve can be shown to maximize the social welfare function subject to the production capabilities of the economy (Figure 10).^ Let the utility functions of A and B be U(A) = U 1 = Ul(q1l, q12, x., ) 1 (9) (10) where consumed by person i (i = (A = 1), (B = 2)) x - x labor provided by person i k6 u (a ) Q U(B) i 0 Fig. 9.--Utility Frontier 47 u(A) Q Q* U(B) o Q' Fig. 10.— Utility Frontier and Social Welfare Indifference Curves 48 Let tlie aggregate production function be F = (q11 + q21 ’ q12 + q22 * X 1 + X 2^ = ° The necessary conditions for maximizing the social welfare function ¥ = W(U1( U2) (12) subject to F are the first-order conditions for maxi mizing W - X - = ¥ - \ F (13) with respect to all q. x. , and X . The solution of the 3-3 1 resulting set of seven partial derivatives, each set equal to zero, satisfies all of the conditions for Pareto optimality and provides the socially optimum pro duct vector Q* = (q-tf, q|) = (X*, Y*) (1 4) and the socially optimum distribution of products and allocation of labor F* = (q*., + q*1t q*2 + q ^ , x* + x*). (15) The problem of defining a social welfare function for a democratic society that "satisfactorily" reflects the values of the individuals comprising that society may be impossible. Defining such a welfare function implies that members of society must communicate with one another and must decide socially what the parameters of such a function would be. This is usually done by 49 voting and some criteria for interpreting the results of4 the voting, such as majority rule, is used to arrive at a final social decision. Arrow has shown that it is impossible to cbtain a social decision without violating at least one of five conditions that he established as being reasonable for social decision-making in a demo- 1 o cratic society. Location Theory and External Effects Location theory is that branch of economics that deals with the spatial distribution of resources among alternative uses, production, and consumption so as to maximize profits of entrepreneurs, utility of consumers, or social welfare of the public. Because individual production and consumption locations are usually fixed during short intervals of time, location theory deals principally with long-run economic condi tions of production and consumption. The first significant contribution to location theory was made in 1826 by Johann Heinrich von Thunen.^ Von Thunen showed how homogeneous land surrounding a central market in an isolated state would be used in the production of alternative agricultural products. Early contributions to the foundations of location theory were 1 2 made by German economists. 50 Two major theoretical approaches to the study of* location developed from the work of von Thunen: (l) a least-cost, static, partial-equilibrium theory of indus trial location developed by Alfred Weber and (2) a some what macroeconomic theory of location and a space- economy under conditions of monopolistic competition using the idea of economic regions developed by August 1 T Losch. These two approaches to location and space- economy and related theories of land use and urban structure were integrated with general economic theory and trade theory by Walter Isard in his "general theory relating industrial location, market areas, land use, 1 b trade, and urban structure." This section is a summary of concepts from location theory that relate to the spatial agglomeration 1 ^ (deglomeration) of economic activities. Microagglomeration: Agglomeration Economies and Diseconomies In Alfred Weber's classic theory of the location of industries, he identified three principal factors that determine the location of industries: transport cost differentials, labor cost differentials, and 1 6 agglomeration (and deglomeration) factors. He showed 51 that the costs of transporting resources from their loca tions to a plant location and of transporting products from plants to markets establish a systematic structure of transport costs. Given the resource costs at each resource location and the transport rates from each resource location and to a market location, Weber argued that the point of optimum location was that point where 1 7 transport costs were minimized. Labor costs at differ ent possible locations tend to shift the optimum location based on transport costs toward one or more of the locations where labor costs are relatively low. Weber showed that transport and labor cost differentials deter mined the regional distribution of industries. Agglomeration factors were introduced to explain why firms and industries concentrate in local areas (or tend to disperse). Later writers, especially Edgar S. Hoover and Walter Isard, developed the Weberian theory of 18 location. Four categories of agglomeration economies (and deglomeration diseconomies) have been identified. Transfer economies (diseconomies) Economies (diseconomies) of large-scale production Localization economies (diseconomies) Urbanization economies (diseconomies).^ 52 Transfer economies (diseconomies) are reductions (increases) in cost that result as firms locate close to one another. Transfer economies (diseconomies) can be represented by downward (upward) shifts in the long-run average cost curve of firms. Firms may locate close to one another if they perform successive phases of produc tion. Retail trade and service firms may locate together in shopping centers so as to benefit from the increased sales resulting from the large volume of customers who prefer to take one trip to a shopping center rather than several trips to diverse locations. Neighborhood effects of firms in a particular industry locating near one another result from consumers1 preferences to go to one location to find a variety of a particular type of pro duct or service, such as automobiles, furniture, or entertainment. Economies (diseconomies) of large-scale produc tion are internal to the firm and can be represented by movements down (up) the long-run average cost curve of the firm as it expands its production. Economies of large-scale production can be realized by a firm at a particular location if that firm's production costs are reduced so that it can undersell other firms at farther 20 distances. The reduced production costs offset the 53 Increase in transport costs of serving a larger market area. Localization economies (diseconomies) are immobile external economies (diseconomies) of scale that are internal to a particular industry at a particular location. Localization economies (diseconomies) tend to concentrate (disperse) firms in a particular industry at (from) the location of the localization economies (diseconomies). Localization economies (diseconomies) can be represented by downward (upward) shifts in the long-run average cost curve of firms in a particular industry at a particular location as industry production increases. This condition implies that localization economies can be realized only by firms in a decreasing cost industry because only in a decreasing cost industry is it possible for industry output to increase and for the long-run average cost curve of the firms in the 22 industry to shift down. Furthermore, localization diseconomies can be realized only by firms in an increasing cost industry because only in an increasing cost industry is it possible for industry output to increase and for the long-run average cost curve of the 23 firms in the industry to shift up. 5k In general, each, firm’s profit function is TI^ = — (i = 1, 2, . . . , n) O^) where = t otal profit of firm i R. = total revenue of firm i i C. = total cost of firm i i If all of the firms are assumed to be located at the same place and each firm’s long-run total cost is a function of the levels of production of all of the firms in the industry (external economies or diseconomies), then each firm's profit function can be written as ' T{ ± = R± - C±(q1 , q2, . . . , qn ) (17) where = production of firm i Each firm can be assumed to be motivated to maximize its profit function with respect to its own level of produc tion. The first-order condition for profit maximization by each firm is j'n’ i _ ^Cj(q1’ q2’ • • •’ Si) _ ■ 0 /18. A <ii Aq± Aqi The second-order condition for each firm is that .2_, »2t, v2 (19) 55 which, show that marginal cost must be increasing at a firm's marginal cost curve could be negatively sloped, zero-sloped, or positively sloped. Regardless of the slope of the marginal cost curve of each firm, the long- run industry supply function i could be positively sloped, zero-sloped, or negatively sloped depending upon whether the industry is an increasing cost, constant cost, or decreasing cost industry. Typical examples of localization economies are: Lower-cost resources as industrial production increases, Cost reductions reflecting the increased pro ductivity resulting from greater specialization of firms, Lower costs because of the existence of a large, skilled, local labor force, Benefits resulting from the establishment of firms that specialize in processing wastes of large-scale production industries, and Benefits of research and development that can be made possible only when industrial produc tion is large. faster rate than marginal revenue 2k Therefore, each (20) 56 Typical examples of localization diseconomies are: Higher-cost resources as industrial production increases either because of diminishing returns to local resources or because of increased trans port cost of obtaining remotely located resources, and Increases in land values and rents as more capital and population are combined with fixed amounts of local land. Isard has pointed out that much of Weber's analysis of localization economies is essentially the same as the analyses of economies of large-scale production. Isard also points out the uncertainty and indeterminacy of the problem of determining the location of industry production when, initially, the firms in the industry are located at particular sites and they could realize localization economies by relocating (assuming tempor arily that there are no relocation costs). He points out that concepts from game theory might be applicable to this problem. Urbanization economies (diseconomies) are external economies (diseconomies) to firms in many industries at a particular location. Urbanization economies (dis economies) tend to concentrate (disperse) firms in many industries at (from) the location of the urbanization economies (diseconomies). Like transfer and localization economies (diseconomies), urbanization economies 57 (diseconomies) can be represented by a downward (upward) shift; in the long-run average cost curve of firms in many industries as the urban product of the location 2 6 increases. Typical examples of urbanization economies are advantages arising from: Greater productivity resulting from increased specialization, Larger, more diversified, more mobile, and more adaptable labor force, More efficient transportation and other urban public utility facilities and services, Proximity of commercial and financial services, Nearness of large-scale transfer and ware housing facilities, Smaller inventories because of the nearness of wholesale distributors, and 27 Public services. Typical examples of urbanization diseconomies are dis advantages arising from: Higher product prices and wages in urban areas, Higher cost of materials locally processed or produced under conditions of diminishing returns, Increased time and other costs of transportation, and 28 Higher land prices and rents. 58 Most of the author’s on location theory tend, to distinguish between urbanization economies (diseconomies) / \ 29 and localization economies (diseconomies). However, to the firm that is motivated to maximize profits, both types of economies (diseconomies) are external effects acting to reduce (increase) the cost of production. Furthermore, localization economies seem to be a subset of urbanization economies. In fact, the Weberian concept of the labor (or other localized resources) orientation of a firm toward (away from) a particular location sup posedly unimpeded by what Hoover later distinguished as the external effects of localization and urbanization economies (diseconomies) seems to be an artificial con struct. Whatever advantages there are to be gained by locating a firm toward or at a particular location include the external effects of moving toward or to that location. Assuming that all n firms in an urban area are motivated to maximize profit, each firm will try to adjust his level of economic activity so that its profit function = (i = 1 , 2, . . . , n) (21 ) is maximized. Assume that the cost functions of each 59 of the n firms are functions of not only each individual firm's level of economic activity hut of that of the other firms in the area. 0-2 » • * •» (22) Then just as in the case of localization economies (dis economies), each firm would tend to adjust its level of economic activity to that level at which each firm equalizes marginal revenue with marginal cost, and the same general optimization conditions would obtain. A profit maximizing firm that is faced with the choice of where to locate would have to evaluate the profitability of locating at each alternative location in light of both anticipated total revenue as well as anticipated total cost, which would be affected by both internal as well as external economies (diseconomies) of locating there. These external effects would include what has been distinguished as transfer, localization, O p i and urbanization economies (diseconomies). At any point in time, all advantages (disadvan tages) of spatially concentrating economic activities can be derived from reducing (reducing too much) the distances that the activities are from one another. In principle, whatever economic activities can be performed when economic activities are spatially concentrated can 60 be done, although, not necessarily as well, when these activities are dispersed, but. usually at much higher (perhaps uneconomically high) costs of1 transportation or communication. As distance between interrelated econo mic activities decreases, product and resource market conditions can be expected to change to reflect the effects of decreased distance on product and resource prices and quantities. As firms agglomerate in space, firm and market product demand and supply may increase resulting in increased derived demand for resources and probably an increase in mobile resources. Both internal and external economies and/or diseconomies may result from the spatial concentration of economic activities to further affect the allocation of resources. From the urban consumer’s standpoint, increased spatial concentration of (l) economic activities that typically accompany urban economic growth and (2) popu lation, resulting in the urban growth of the area are typically accompanied by external effects, some of which generally increase individual utility and social welfare, such as the amenities of urban life, and others which generally decrease individual utility and social welfare, such as congestion, environmental pollution, reduced real income from high urban land costs, and urban rents. 61 Macroagglomeration: Systems of1 Cities Weberian, location theory focuses on determining the least-cost plant location of industrial firms by studying the comparative advantages of alternative loca tions when the locations of resource and product markets and the prices of resources and products are given. But Weberian location theory is not particularly appropriate for determining the locational pattern of cities. August Losch developed such a theory of a space- economy based on the theory of central places, developed by Walter Christaller from his study of the location of 31 centers in Southern Germany. Losch showed that even if land formed a flat homogeneous plain with uniformly dis tributed natural resources and an initially even distri bution of population, production and population would tend to agglomerate causing cities of different sizes to develop in a regular pattern. Losch developed this theory 32 around the idea of economic regions. He assumed that the population lived on self-sufficient farms which were regularly distributed throughout the plain. Each farm is assumed to be able to realize internal economies of large-scale production from increasing returns to out lay. Each farm could produce and sell more than it needed as long as the savings from large-scale production is at 62 least as great as the transportation cost of getting the product to the consumer. Diminishing long-run average cost of production encourages specialization and division of labor, thereby increasing production, whereas transportation cost (the same in every direction from the producer) limits pro duction indirectly through its effect on demand. In deriving the demand function for each pro ducer, Losch assumes that consumers have identical nega tively sloped demand functions, which are functions of the delivered price, Ppq• <lpd = a + bPpd <a> °? b> C> <23> = a + b(p + rd) where q , = quantity demanded by a consumer located a linear distance d from the plant when the price at the plant is p Ppd = delivered price of the product at distance d from the plant when the price at the plant is p p •= price at the plant r = transport rate per unit of product per unit distance d = linear distance from the plant Because consumers have to pay the product transport costs, they are assumed to purchase the product from the closest 63 producer*. Therefore, each, producer has some monopolistic control of the market in which he sells. For a given value of p, the market area is delimited by the circular locus of points ABCE in Figure 11 at that distance from the plant where = 0. Figure 11 shows the demand cone for the producer at location 0 when the price at the plant is p. The total quantity demanded, Q, of the pro ducer at location 0 when the price at the plant, p, is represented by the volume of the cone multiplied by the population density. Given the values of a, b, and r in equation (23)> for each value of p, there will be a different demand cone and, consequently, a different value of Q (Figure 12). If demand curve were the producer's demand curve at one point in time, he would be making a profit if p = p^. Profits would invite entry of new firms. As new firms enter the industry, the mar ket area of each competitor is reduced. Entry will con tinue until there are no profits to be made, or alternatively, until the demand curve, , is just tan gent to the L.RAC curve (p = LRAC) for all firms in the industry. The resulting market areas that collectively just satisfy the demands of all consumers for the pro duct and are large enough to provide only normal profits qpd A B Fig. 11.--Demand Cone of a Producer 65 LRAC Q Q Fig. 12.— Demand and Dong-run Average Cost Curves of a Producer 66 will be hexagonal in shape. Collectively, these market areas form a uniform honeycomb pattern or network. Networks for products whose producers have the same size hexagonal market areas can be aligned so that the centers of the market areas form central places of one or more producers. Sets of such market places can be centered on one of the original farm sites and aligned to form a system of cities. Losch showed that these net works could be rotated until twelve radial sectors are formed, extending from the pivotal central place. In six of the sectors, there would be a heavy concentration of central places and very few in the remaining six sectors. This pattern (l) maximizes the number of cen tral places that coincide, {2) maximizes local demand, and (3) minimizes the sum of distances between central places. This arrangement forms a hierarchy of cities, with the pivotal city as the largest city. All products would be sold in this metropolis, and fewer products would be sold in lower order cities. Furthermore, the lower the order of cities, the more cities there are of 33 that order. Critics of Losch*s theory point out inconsis tencies and limitations of his scheme. In reviewing Losch1s book, Wolfgang F. Stolper points out that Losch 67 does not determine the maximum number of firms when the Chamberlinian tangency condition exists and, therefore, the number and size of hexagonal market areas in each 34 industry are not determined. Furthermore, if equili brium conditions were approached by assuming that there were more than the equilibrium number of firms in the industry, each of optimum size, Losch gives no way of determining which firms would leave the market. 35 Isard mentions several significant criticisms. Losch’s model is not a general equilibrium system because product and resource markets are not interrelated through utility and pro duction functions. Equality of the number of equations and unknowns does not prove the existence of an equilibrium. Losch’s model has too many equations and unknowns. Once the location of one producer of a parti cular product is given and once one of his market area boundary equations is given, the location of all other producers of that product and the equation of all other boundary lines are deter mined . Losch's model is inconsistent in that it yields a pattern of agglomerated production locations but assumes that products are sold to a popula tion that remains uniformly distributed over the plain. Losch’s model does not account for any non- uniform distributions of resources and, there fore, pertains only to industries, such as firms providing services, which do not require localized raw materials or other resources or can obtain these resources everywhere at the same price. 68 Isard also suggested that as firms locate closer to one another because of agglomeration economies, the market areas of these firms would tend to become smaller because the higher-density population near the center of large cities provides adequate demand over a smaller market area.^ Isard also suggests that Weberian and Loschian location theory can be made consistent by using Weberian theory to determine the location of industries that require localized resources and to then use Loschian theory to determine the location of industries that 37 require ubiquitiously available resources. Martin J. Beckmann extended Losch’s theory by developing a model of city hierarchy based on two addi- n O tional assumptions. First, the population of each city is proportional to the rural population that it serves. Second, the cities in each order of the hierarchy, except the lowest order, have a fixed number of "satellite” cities of the next-lower order. Let m = order of a city (m = 1, 2, . . ., N) Pm = population served by each city of order m — population of each city of order m C k 2? P m s = number of cities of order m - 1 that are served by each city of order m (except when m = 1 ) 6 9 r = rural population served by each, first-order city P = total population T = total number of cities N = total number of orders of cities From the first assumption, C = kP (24) m m and from the second, P = C + sP 1 m m m-1 - ■ - s- - p = (- JL,.\ 2 P 1 - k m-1 V1 _ ]J m-2 Since and then C1 = k(r + C1) k 1 - r P1 = r + C1 1 - k m- 1 P = S r and C = (1 - k)1 ksm“^ r (1 - k)' (26) (27) (28) 70 Hence, both, population served and urban area population increase exponentially with the order of the urban area. For m > 2, the population of each urban area of order m is s times larger than that of an urban area of order 1 - k m - 1. Beckmann also showed that, given s, N, r, and k, N-1 P = P S3 — -------------— f 30 ) N (1 - k ) K U } given s, N, k, and P log — N = ------- (31) 39 and given s and N <=N+1 1 T = ■ — T ~ (32) Beckmann also showed that the empirical "rank- size rule", used extensively by George K. Zipf, is "com patible with the ideas on hierarchies of market areas and their central cities as developed by Losch and other 40 location theorists." Zipf used the rank-size rule to estimate the statistical relationship between the (1) rank, r, of a city (largest city has rank 1, second largest has rank 2, etc.) and (2) its population, P. rPq = K (33) 71 or log r + q log P = log k (3^) 41 where q and K are constants. Beckmann showed that the rank of a city halfway in city size class n is approximately Rank sn + s ] _- -,) (35) and its size is^ Si- - pN-n - ( r ) ( i 4 - k)’ " n (36) By multiplying rank times size, he gets (Rank) (Size) = (1 + C H r ^ ) 0 “ k>n (37) For values of k near zero, (1 - k)"n £^1 (38) and the product of the rank and size of a city is approximately equal to the constant K =s f (k, r, s, N) - ¥ (a* i-H) (i-H)” (3 9) Hence, the rank-size rule is compatible with the hier archical system of market areas represented in his pre viously discussed model. Beckmann shows that the rank-size rule is a Pareto distribution when q (in Zipf's \ 43 equation) is equal to 1. 72 Land Use Theory and External Effects Land use theory is a branch of location theory 44 tliat deals with, the determination of how land is used. This section is a summary of theories of agricultural, commercial and manufacturing, and residential land use and generalizations of urban structure. Agricultural Land Use The theory of agricultural land use was first outlined by Johann Heinrich von Thunen in 1826. This was the first significant contribution to what today is known 45 as location theory. Von Thunen was the first economist to explicitly incorporate the distance dimension of economic activity into economic theory and to clearly state that economic rent is the controlling determinant 46 of land use. Von Thunen treated rent as a surplus, just as David Ricardo, but whereas Ricardo attributed rent to differences in the inherent productivity of land, von Thunen showed that rent would be generated even if all plots of land were identical in terms of inherent productivity because of locational advantages arising 47 out of lower costs of transporting products to market. Concepts from von Thunen's theory can be found in later work in market and supply area analysis and they form 48 the foundation of urban land use theory. 73 The theory of agricultural land use is an aggre- 49 gate theory based on the following assumptions: Flat plain with equally fertile land throughout and with no navigable rivers or canals. Only one (punctiform) town, located in the center of the plain, where agricultural pro ducts are sold. At a great distance from the town in every direction, the plain ends in a wilderness which isolates it from the rest of the world. All mines and mineral deposits are located next to the town. All manufactured products are produced in the town, and all agricultural products consumed by the town's population are produced in the town's hinterland. Transport rates are the same in all directions. Agricultural product markets are competitive and product market prices are given. Labor (or labor-capital) and land are the only two resources used in agricultural production. Wage rate is the same throughout the hinterland and is given. Given these assumptions, agricultural land uses are determined by the highest rent that can be paid at each location. That is, landlords will rent their land to those who can pay the highest rent. But rent is a function of distance. Consider the following model for 50 the single-product case. Let R = rent per unit of land k = distance from the town 74 E = product per unit of land p = market price a = average cost of production r = transport rate per unit of distance per unit of product R = aggregate rent Along any linear ray extending from the town, a 5 1 bid rent function, R, can be defined. R = E(p - a) - Erk (4o) Equation (4o) and Figure 13 show that the maxi mum rent per unit of land is (Ep - a) at the town and that the maximum distance from the town that the product can be produced without the producer incurring a loss is . Aggregate rent, R, is represented by the volume of the rent cone (Figure 14) generated by rotating the bid rent curve about the OR axis (Figure 13) • k „ R = 211^ (E(p - a)k - Erk )dk (41 ) o Marginal rent is the integrand. The first order condition for maximization of aggregate rent is = 21TE(p - a)k - 21tErk2 = 0 (42) or k = ^ (43) In other words, aggregate rent is maximized when pro duction is carried on throughout the circular area about 75 R E(p-a) O k p-a T Pig. 13*— Bid Rent; Curve Fig. 14,— Aggregate Rent Surface 77 the town within a radius of k units of* distance from the town. Notice that R equals marginal rent when k = -————, and both equal marginal cost (horizontal axis) since rent is net of costs. The two-product case introduces additional con straints and conditions. Figure 15 shows an example of a relevant two-product agricultural land use problem. Lines AB and CD show the bid rent functions for products 1 and 2 respectively. The two-product location case exists only when the bid rent curves of the two products inter sect in the positive quadrant. This condition implies that the bid rent curve with the higher rent intercept also must have a smaller distance intercept, as does the bid rent function for product 1. Therefore, the necessary and sufficient conditions for the formation of rings of different agri cultural land uses can be expressed as A> C > O or E1(p1 - a^> E2(p2 - a2)> 0 (44) and B < D or kR1=0 < kR2=0 (45) ; i In Figure/'l5> product 1 will be produced immediately 1 around the town in the circular area with radius Ok1 because industry 1 can pay higher rents than industry 2 near the town (R-| > R2)* Product 2 will be produced in a 78 R A C E R k ' k D O B Fig. 15•--Bid. Rent Curves for Two Products 79 concentric ring of" low-rent land surrounding the circular land area where product 1 is being produced because beyond a distance of k ! from the town industry 2 can pay higher rents than industry 1 (&2^ R 1)’ Th® rent gradient, AFD, is an envelope showing the maximum rent per unit of land bid at different distances from the town. The equilibrium boundary distinguishing these two areas (where R^ = ) can be found by first defining a total net rent function, , for industry 1 which gives the rent generated by industry 1 net of the opportunity cost of possible returns from producing product 2. 5, = Hi - R2 k = 2TT* § (E1(pl - a 1 )k - E ^ k ^ d k o k P - 2TT £ (Ep(Pp - aQ)k - E^rpk )dk (46) 2 2 o The first-order condition for maximization of total net rent is that marginal net rent be equal to zero. dR1 d i r = E i p i = V - E irik - e2(p2 ~ a2^ + E2r 2k = ° (^7) The boundary between the areas in which products 1 and 2 are produced is simply the circular locus of points at a distance E1(p1 - ai) - e2(p2 - a2> <48) E 1r l - E 2r2 80 from the town. At a distance k 1 from the town, the mar ginal rent of industry 1 equals that of industry 2. Product 1 will be produced within a distance of k' miles from the town in every direction; product 2 will be pro- ^2 ~ a2 duced in the circular ring area between k 1 and ------- r2 (D in Figure 15) miles from the town. For the multiple-product case where there are n products and industries, there will be n bid rent curves, R1, R2, . . ., Rn, which can be assumed to be listed in the order of their decreasing slope. In equi librium, the ith product will be produced in a ring (l) whose inner boundary is at a distance of k ^ where R. = R. „ and kT. is smaller than any other distance x r-1 Ii where the ith industry’s bid rent curve intersects that of any other industry with a flatter slope and (2) whose outer boundary is at a distance of kQi where R^ = Rj_+- j and is larger than any other distance where the ith industry's bid rent curve intersects that of any other industry with a steeper slope. Figure 16 shows rent bid curves for three industries and the boundary distances for each industry land use. If the productivity of the land for industry i, E^, were to increase, perhaps because of improved technology, or if the transport rate for industry i, r^, 81 R 02 “ 13 03 k k 01 12 Fig. 16.— Bid Rent Curves four Three Products 82 were to increase, the slope of1 the bid rent curve for industry i, R_^, would increase. Correspondingly, a decrease in E_^ or in r_^ would reduce the slope of the 52 bid rent curve. If the market price of product i, p^ , increases or if the average cost of production of product i, a^, decreases, the bid rent curve, Ih , would shift up. Con versely, if p^ decreased or if a_^ increased, the rent bid rent curve would shift down. Any shift in or change of slope of the bid rent curve of any industry will cause spatial disequilibrium of land uses. Spatial equilibrium would tend to be re-established as industries compete for the use of agricultural land. Commercial and Manufacturing Land Use Although Ricardo’s and von Thunen1s theories of rent, both with principal regard to agricultural land, were formulated relatively early in the history of economic thought, few economists have taken interest in 53 urban land rent. Alfred Marshall included a chapter in his Principles of Economics on urban land in which he concluded that land will be put to that use which has 54 the highest "situation value" or rent. Edward H. Chamberlain in his The Theory of Monopolistic Competition emphasized that urban land rent for retail firms is a 83 monopolistic return, and that a given urban land site tends to be put to those uses for which, its owner can t r c obtain the most rent. Later writers on urban land use theory include Richard M. Hurd, Ernest W. Burgess, Robert M. Haig, Roderick D. McKenzie, ¥alter Firey, and Richard U. Ratcliff, Amos H. Hawley, Lowdon Wingo, Jr., 56 William Alonso, Walter Isard, and Hugh 0. Nourse. For many commercial industries in an urban area, access to customers is very important for maximizing profit. Because the central portion of urban areas pro vides access to the largest number of customers, total revenue increases as a firm locates closer to the center of the urban area. Figure 17 shows how total revenue varies with distance from the center of the city, given the values of variables that offset total revenue at various distances from the center of the city, such as 57 selling costs. At any given distance, say Ok in Figure 17» the total revenue 0-TR can be anticipated if the land is used by a particular industry. If cost functions of each firm in this industry are the same throughout the city, then for a given product price, assume that a profit (rent) can be realized by each firm by selling that volume (0Q^ in Figure 18) corresponding to the anticipated total revenue 0-TR at distance Ok. 84 Total Revenue TR 0 k: Distance Fig. 17*— Total Revenue as a Function of Distance 85 The maximum total rent that could be paid by a firm selling OQ.j units of product at a distance of Ok from the center of the city is PABC in Figure 18 and by OR in Figure 1 9 • Rent would have to be paid, because, although every firm in every commercial industry would like to locate in the center of the city, they could not do so because each requires space and, therefore, would be forced to compete with one another for the use of the more favorable central locations. If land can be substituted for nonland resources at increasing distances from the center of the city, prices of nonland resources are the same throughout the city, and rent per unit of land decreases with increasing distance from the center of the city, then quantity supplied can be increased by locating at increasing dis tances from the center of the city. Figure 20 shows the income and substitution effects of the differences in rent per unit of land at the center of the city and at a distance k from the center, using labor as the nonland resource. However, the decreasing total revenue at increasing distances from the center of the city places an upper limit on the increase in the quantity that can "be profitably supplied. In general, at every distance from 86 AC MC P C o Q1 Q/t Fig. 18.— Price and Cost Curves of a Typical Commercial Firm 87 Rent R O k Distance Fig-. 19 .— Bid Rent Curve for a Particular Commercial Land Use 88 Land Labor 0 Fig. 20.— Isoquant Curves and Total Outlay Curves of a Commercial Firm at the Center of the City and at a Given Distance from the Center 89 the center of the city (Ok in this example), there is some rent per unit of land. (AB in Figure 18) that equates total revenue with total cost (including rent), as is 59 shown in Figure 21. Commercial land uses would "be determined, as in the case of agricultural land use, by the maximum rent that can be paid for the use of any given plot of land (Figure 22). Within a distance of Ok^ of the center of the city, land would be used for commercial industry 1, between Ok^ and by commercial industry 2, and between 0k2 and Ok^ by commercial industry 3» Line CDEk^ is the rent gradient for these three industries. Figure 22 shows that in spatial equilibrium, commercial industries are located at different distances from the center of the city, with land being used by those industries which can afford to pay the highest rent at each distance. Because firms in manufacturing industries typi cally sell their products to buyers both outside as well as within the city in which they are located, interurban and regional differentials usually are more important than intraurban differentials. Once a manufacturing firm has decided on the city in which it is going to locate, its total revenue does not tend to vary much at different locations within the city.^ But total cost of production 90 TC 9 TR, TC TR. O Q Q, Q Fig. 21.— Total Revenue and Total Cost Curves at Different Distances from th.e Center of the City 91 Rent C B A 0 k1 k2 k^ Distance Fig. 22.--Bid Rent Curves for Three Commercial Industries varies with location because of different wages and other resource costs and rent per unit of land at different locations within the city. For example, wages can usually be expected to be somewhat lower in and around the densely populated center of the city, where journey- to-work distances, travel times, and travel costs are small, than at a site on the fringe of the city where population densities are low and journey-to-work distan ces, travel times, and travel costs are high. But rent per unit of land near the center of the city usually tends to cause many manufacturing firms to locate at some dis tance from the center of the city. Assuming that land is substitutable for nonland resources at increasing distances from the center of the city, that product price is given, and that wages are low at the center but increase as a firm locates closer to the fringe of the city, at any distance k from the center of the city and with a given outlay, there will be some rent per unit of land that will equate total revenue and total cost (including rent), as shown in Figure 23* Figure 23 shows that, for a given outlay, OQq would be produced if the firm located at the center of the city, whereas OQ^. would be produced if the firm located at a distance k from the center of the city. Figure 2k shows several 93 TR, TC TC. TC TR 0 Q, Q, Q Fig. 23.--Total Revenue and Total Cost Curves of a Manufacturing Firm 9h Land O Labor Fig. 2k-.— Isoquant Curves and Composite Isocost Curves for a Manufacturing Firm 0 95 isoquant curves and composite isocost curves for a 61 manufacturing firm with, several different outlays. Figure 24 shows that if the firm plans to produce at pro duction levels of Q.j or » it should locate at the center of the city whereas if it plans to produce or units of the product, it should locate at a distance k from the center of the city. Residential Land Use The theory of residential land use has developed, like commercial and manufacturing land use theory, from earlier work in agricultural land use theory and from utility theory. But empirically derived relationships have also had a very significant impact on the develop ment of residential land use theory. Colin Clark showed that the distribution of urban population density about the center of a city could be described by the negative exponential function, Dk = Dc e-bk (49) or log Dk = log Dq - bk (50) where Dk = population density at a distance k from the center of the city Dq = population density extrapolated to the center of the city (k = 0) 96 b = population density gradient k = distance from the center of the city The population density gradient, b, is related to the areal extent of a city and might be used as an index of urban "sprawl". The value of b is influenced greatly by the transportation systems of a city. Trans portation systems that can transport people to and from relatively long distances from the center of a city rapidly and at relatively low cost will tend to reduce the value of b; with relatively inferior transportation systems, people will tend to live more densely near the center of the city so as to reduce travel distances for 6k trips to work and to shop in the center of the city. The population density at the center of the city, Dq, is an extrapolated value and invariably overstates the 65 actual population density at the center of the city. The population of a circular city with radius m 66 can be found by integrating , m . , Pm = 21T 0 D e k dk ^ 0 = 2TTDq b“2 £1 - e-bk(l + bk)J (51) Xn developed countries, the value of b for a particular city over time or for cities of different sizes at a given point in time depend on population,^^ b = a p-C (52) 97 The population density at the center of the city, Dq, 6 9 depends upon the age of the city. Therefore, once a city's population and age are known, the distribution of 70 population within the city can be estimated. Models of residential land use by Richard F. Muth and William Alonso provide theoretical explanations of Clark's negative exponential population density 71 function. These models assume a city (at a point), where all factor and product market transactions take place, with homogeneous land extending indefinitely in all directions. Furthermore, consumers are assumed to be motivated to maximize utility by substituting housing services for other products and services within income constraints. Given the income constraint of consumer i, Y. - C(k) = pzZ. + PhH. (53) where Y. = income of consumer i i C(k) = cost of travelling k miles Pz = price of the composite good, Z Z. = quantity of all goods and services except housing services purchased by consumer i Ptt = price of housing services, H ri H. = quantity of housing services purchased by consumer i 98 U. = U.(H., Z . , k) i a.v i ’ i ' = utility of consumer i consumer i can find a combination of H and Z (point A in Figure 25) for any given distance, k 1, from the city and prices (ptt) and p„, which will maximize utility. At a H I distance k^ from the city, consumer i*s real income would have decreased because of the increase in the cost of transportation, c(k2) - c(k1). Consequently, he could purchase a maximum of Y i - °(k2> PZ Yi - C<k2> of Z (H = o) of H (Z = O) or with a given money income, Y^, and prices p^. and (Pjj) - j • But there is a price, (pj^)2 ^ 1 ’ w* 1- * - c* 1 consumer i would be indifferent between the combination of H and Z represented by point B in Figure 25 and that represented by point A. At the lower price of housing services, at a distance k^ from the city consumer i has substituted housing services for other goods and services, Z, and accessibility, k. Assuming that all nonland resources have the same prices in all locations and that all households have the same incomes and tastes, rents per unit of land 99 z Yi-C(k1) Y±-C(k2) Y±-C(k) H O ^ • P H^2 Fig. 25*— Budget Constraint and Indifference Curve for Housing Services and Other Goods and Services 100 in a competitive housing market must decrease with increasing distance from the city or housing services would not be provided. If, as distance from the city increases, the price of housing must decrease in order to leave consumers indifferent between livigg at a more remote site than at or near the city, then the total revenue of suppliers of housing services must decrease, at least in the inelastic range of the demand function 72 for housing services. Since total revenue decreases with increasing distances, rent per unit of land must decrease in order to reduce total cost (including rent) of housing services enough so that some equilibrium level of housing services will be provided at each distance from the city. The bid rent curve for residential land use shows the maximum rent that can be paid at each distance from the city. High-rent (per unit of land) housing services, such as high-rise and other apartment houses, would tend to be located near the city, whereas low-rent (per unit of land) housing services, such as single-family houses, would tend to be located away 73 from the city. Urban Structure The bid rent curves for agriculture, commercial, manufacturing, and residential land uses can be superinposecl 101 to determine the overall spatial equilibrium of* land uses (Figure 26). The rent gradient, ABCDE in Figure 26 is an envelope which shows the maximum rent that can be paid at each distance from the center of the city. In Figure 26, land within lc1 miles of the center of the city would be used for commercial purposes, land between k^ and k2 miles for manufacturing, between k^ and k^ for residences, and between k^ and k^ for agricultural production. The resulting areal land use pattern is a series of concentric rings or zones of different land uses. This pattern is altered to more closely reflect actual land uses as assumptions about (l) the uniform fertility of the soil, (2) uniform topography, (3) equal transport rates in every direction from the center of the city, and (4) a single market center are relaxed. Relaxing these assumptions for a metropolitan area results in a rent gradient surface that reflects the effects of topography, satellite cities, soil fertility, and trans port costs throughout the area. External effects are particularly evident in the 75 land use pattern of commercial and residential sectors. For the commercial sector, the central business district extends out along transport routes, reflecting transport 102 Rent A Commercial Manufacturing Residential Agricultural 0 k. kr k^ Distance from the Center of the City Fig. 26.— Bid Rent Curves and Rent Gradient 103 rate differentials in different directions from the center; small shopping centers are established throughout the area reflecting the external economies of localized consumers; large shopping centers and satellite cities near the periphery of the city reflecting the relatively low rent per unit of land at increasing distances from the center of the city. For the residential sector, external effects tend to affect the size of lots at different distances from the center of the city, but the general pattern of concentric zones of residential land use could still be expected to develop. However, external effects also result from people in similar socio-economic groups typically preferring to reside in more or less distinct areas of a city. This agglomerating tendency becomes increasingly significant with increasing city size and tends to support a sector hypothesis of urban structure. For the manufacturing sector, transport facilities usually produce the most significant external effects on land use patterns. Xn most American cities, there seem to be forces simultaneously tending to produce concentric zones and sectors. Three principal empirical generalizations have been made to describe the structure of urban land uses: concentric zone, sector, and multiple nuclei hypotheses. Ernest ¥. Burgess advanced the concentric zone hypothesis 77 of land use in American cities. The concentric zone hypothesis stated that the areal expansion of a city produces five concentric circular zones of different land uses, similar to von Thunen's rings, about the center of the city: (l) central business district, (2) zone in transition from residential to business and light manufacturing, (3) zone of workingmenfs homes, (4) higher-quality residential zone, and (5) commuters' zone. The concentric zone hypothesis conforms generally with the land use pattern implied by spatial equilibrium r y Q derived through the theory of urban land use. Burgess claimed that over time as the urban population increased, population density tends to increase, and areal expansion begins to occur, the area of each zone tends to increase by extension of the land uses of each zone over the area 79 of the next outer zone. The concentric zone hypothesis has been criticized for not adequately describing the urban structure of many cities, and has been defended 80 for its gross descriptiveness of land use patterns. Homer Hoyt advanced the sector hypothesis of 81 residential land use in American cities. The sector hypothesis states that residential land tends to be in the form of wedges or sectors extending from the center of the city along transportation lines. Hoyt claimed 105 that high-rent areas tend to be located in one or more of the sectors comprising the city and that rent decreased in all directions from these high-rent areas. Low rent areas form other sectors that extend to the periphery of 82 the city. Over time, as housing units age, the high- rent sector is extended toward the periphery of the city go and the vacated area becomes a medium-rent area. Hoyt believed that the movement of the high-rent areas was the most important determinant of urban residential land use patterns. Hoyt said that high-rent areas tend to expand outwardly from the center of the city along existing transportation lines, especially along the fastest lines, to locate along nonindustrial waterfronts, and to expand toward high ground, open country, the resi dences of leaders of the community, and commercial . 84,85 buildings. The multiple nuclei hypothesis of land use in American cities was advanced by Chauncy D. Harris and 8 6 Edward L. Ullman. The multiple nuclei hypothesis states that a city's land use pattern develops around multiple nuclei or centers, rather than around the single center assumed in the concentric zone and sector hypo theses. Multiple nuclei develop because (l) some acti vities require specialized resources that are localized at 106 certain places in the urban area, (2) some similar activities spatially concentrate so as to realize higher profits resulting from agglomeration economies, (3) some unlike activities tend to disperse from one another because of external diseconomies of agglomeration, or some activities cannot afford to pay higher rents. Harris and Ullman identified nine general types of nuclei or districts: central business, wholesale and light manufacturing, low-class residential, medium-class resi dential, high-class residential, heavy manufacturing, outlying business, residential suburb, and industrial ft *7 suburb. The multiple nuclei hypothesis seems to pro vide a comparatively realistic structure of urban land 88 uses. Urban Economic Growth. Urban Growth, and External Effects This section is a summary of selected concepts from national, regional, and urban economic growth theory and demographic theory that relate to the economic growth and development and population growth of urban areas, with special emphasis on the role of external effects in urban economic growth and urban growth. 107 Specialization, Unban Economic Growth., Urban Growth and External Economies Adam Smith pointed out that the productivity of* labor could be increased by specialization and division of labor, which could be realized if people exchanged their product. He and others have emphasized that the degree of specialization and division of labor is limited 89 90 by the extent of the market. ’ Opportunities for increased specialization and division of labor not only permit increased productivity but also tend to concentrate production and consumption 9 1 in space. Many opportunities for increased specializa tion can only be realized when economic activities are located near one another. The greater the spatial con centration of production and consumption, the greater the degree of specialization. The very process of agglomeration of economic activities and population growth of an urban area produce net external economies that promote the continued growth and development of the area. Edgar M. Hoover said that external economies of production derived from urban concentration arebbased on three principles: multiples, massing of reserves, and 92 bulk transactions. The principle of multiples applied to urban areas is that specialization tends to take place 108 among firms as the aggregate urban product increases. As city size increases, functions that firms would have to perform themselves (or not at all) can be provided by other firms specializing in these functions at lower cost because of internal economies of large-scale opera tion. The principle of massing of reserves is that, as city size increases, material and supply inventory costs of urban firms decrease because these inventories do not have to be as large when additional materials and supplies can be obtained on relatively short notice. The prin ciple of bulk transactions is that, as city size increases, unit transfer and terminal handling costs tend to decline. External economies reflect direct interdependen cies among different economic activities and individuals in an urban area, that tend to concentrate economic activities and population so as to reduce the costs of 93 spatial interaction. Interdependent economic activities tend to concentrate in space and to form integrated urban- industrial complexes. As technology and functional and spatial changes occur in an urban area, the industry mix, reflecting internal and external economies arising from large-scale production and increased specialization, tends to change so as to provide opportunities for 9k further specialization. 109 Diminishing returns to urban concentration set limits to external economies derived from some parti cular site in an urban area but do not as yet seem to 95 affect the long-run trend of urban growth.. In the developed western economies, economic growth has resulted in an increasingly larger proportion of the gross national product being produced in tertiary industries. As personal income increases, a larger pro- 96 portion of income is spent on labor-intensive services. The increasing demand for services promotes concentra tion of tertiary industries in urban areas and greater 97 urban growth. Stages of Urban Economic Growth Although location theory is static, the theory of location often provides implications for a theory of regional economic growth. Empirical studies by A. G. B. Fisher and Colin Clark suggested that as regions develop, 98 they progress through stages. As a region develops, the proportion of the labor force employed in the agri cultural sector decreases, first as the proportion of the labor force employed in the secondary sector increases, and then as the proportion of the labor force 99 employed in the tertiary sector increases. Edgar M. Hoover and Joseph Fisher suggested that a successfully 1 10 developing region would pass through, five stages in its * 100 development: Self-sufficient subsistence economy (primary products) Some interregional trade and local specialization accompanying improvements in transportation Intensive farming Industrialization (secondary products) Mature regional economy (tertiary products) Wilbur R. Thompson outlines a somewhat similar set of five stages through which a successfully developing 101 urban economy might be expected to pass. Export specialization: The local economy is built around a dominant export industry or firm. Export complex; Greater industrial diversifica tion resulting in more products or in the addi tion of firms operating in prior or subsequent stages of the production of the dominant industry. Economic maturation! Local service industries develop providing import substitution and a variety of business and consumer services. Regional metropolis: The local economy becomes a center exporting products and services to smaller neighboring cities. Technical-professional virtuosity; The local economy becomes a nationally prominent source of specialized products or services. (stage 5 may precede or follow stage 4.) A local economy may not progress to the stage of economic maturity if an adequate industrial export cora- 1 02 plex is not developed. But after some critical 111 population size (perhaps 250,000 persons) is reached, cities seem to become permanently established; absolute 1 03 reduction of* the population size is very unlikely. This "urban size ratchet" effect of urban econo mic growth and urban growth of large cities might result from (l) ability of large cities to adjust to economic changes without severe instability because of their relatively high degree of industrial diversification, (2) political power of large urban areas, (3) large capital stock invested in cities that cannot be^aban doned, except at great costs, in response to economic changes, (4) an increasingly larger proportion of econo mic activities that is consumer- or market-oriented, and (5) the greater likelihood of new growth industries locating in a city the larger the population of the 10k city. These factors as well as improvements in urban technology, political innovation, and imaginative urban administration seem to have sufficiently offset the dis economies of scale in the provision of urban public 105 services. Although the stages theory of urban economic growth is not really a theory in the strict sense, it does provide an evolutionary hypothesis and framework for analysis of the growth of some urban areas. The 1 12 stages theory suggests the importance of* industrial specialization, internal and external economies of large- scale production, and population growth in urban econo mic growth. Its emphasis on the development of trade is compatible with short-run theory of urban income and trade; its emphasis on long-run adjustments in the indus try mix from one export base to another is compatible with the long-run theory of urban economic growth based more on the resources of the urban area. Theory of Urban Income and Trade Over relatively short time periods, product prices, wages, technology, tastes, income distribution, and resources in an open urban economy might reasonably be considered as being given. Under these conditions, the net income of an urban economy equals the sum of expenditures on consumption, net investment, government, and exports minus expenditures on imports. Y = C + I + G + X - M = E + (X-M) (5*0 where Y = aggregate urban net income C = aggregate urban consumption expenditure I = aggregate urban net investment expendi ture 1 1 3 G = aggregate urban government expenditure X = aggregate urban export expenditure M = aggregate urban import expenditure E = C + I + G Assume that the combined consumption, net investment, and government expenditures, E, as well as imports, M, are linear functions of net income, Y, and that export expen ditures, X, are exogenously determined as a function of the income of the rest of the world with which the given urban economy trades. E =s a + bY M = c + eY X = x where a = autonomous consumption, net investment, and government expenditure c = autonomous import expenditure b = marginal propensity to spend e = marginal propensity to import x = given export expenditure Therefore, Y = — ("b " e " ) (a ” c + x) (55) The urban net income multipliers are dY _ dY 1_______ da ~ dx ~ 1 - (b - ej where (b - e) is the marginal propensity to spend, in the urban area. This macroeconomic urban income and trade model underestimates the change in net income because any increase in expenditures will result in an increase in income, which, in turn, will result in an increase in imports, causing income in the rest of the world to increase and expenditures on locally produced exports to increase, initiating still another round of expenditure- 1 07 income changes. Real urban net income can increase until the resources of the urban economy are fully employed. A major limitation on the use of this type of short-run macroeconomic model in empirical studies and for planning purposes is the lack of sufficient data on urban economic activity. One attempt to circumvent this data problem has been the use of a model based on the export-base theory. Export-base theory is based on the Mercantilist idea that the economic growth of a region depends upon the exports of the region. Net income earned in the export (basic) industries is used to buy imports and to 115 stimulate the growth of local services (nonbasic) or residentiary industries. The export-base concept has 1 08 been traced back to Werner Sombart. The export-base concept has been used to explain 1 09 the growth and development of regional economies. The export-base concept forms the basis of the urban export- base (or economic base) theory of the economic growth of an urban economy. The urban export-base theory was explicitly outlined and used for the first time in urban analysis by Robert Murray Haig and Roswell C. McCrea in 110 their study of the New York metropolitan region in 1927* Since then the urban export-base theory has been deve loped, extended, and criticized by men such as Arthur M. Weimer, Homer Hoyt, Charles M. Tiebout, Wilbur R. Thompson, Richard B. Andrews, Hans Blumenfeld, John W. Alexander, Ralph W. Pfouts, and Erie T. Curtis, and 1 1 1 Charles E. Ferguson. The urban export-base theory is a simple hypo thesis about the short-run income and trade of an urban economy under ceteris paribus conditions of given pro duct prices, wages, technology, tastes, income distri bution, and resources. The urban economy is divided into three sectors: exports, E, local investment, X, and 112 local consumption, C. Y = C + I + E (58) 1 1 6 In the short run, local investment and exports are exogenously determined (l = 1 and E = E); local con sumption is endogenously determined as a function of local income. C = cdY where c = marginal propensity to consume d = marginal propensity to create income per dollar of consumption Therefore, where dY dX 1 - cd (I + E) (59) dY dE 1 - cd 1 (60) and is the ratio of nonbasic income to total income, commonly called the base ratio. This ratio has been found to be unstable over time and among urban economies. The ratio tends to be larger as the size of the urban 1 13 economy and its degree of spatial isolation increase. The urban export-base model can be modified for long-range forecasting by making local investment a function of income. I = ijY (61) 117 where i = marginal propensity to invest j = marginal propensity to create income per dollar of local investment Therefore, where Y = dY dE 1 - cd - ij r-s E (62) 1 - cd - ij One criticism of the use of this model for long-term (63) forecasting is that the marginal propensity to consume locally, c, as well as the marginal propensity to create income per dollar of consumption, d, tend to increase 1 14 with city size and degree of isolation. Because of a lack of adequate income and expendi ture data for urban areas, employment data has been used as a proxy for income or value-added, but employment is less responsive to changes in expenditure than income and it does not reflect increases in labor productivity or nonwage income.Xn summary, urban export-base theory is a short-term, demand-oriented, macroeconomic theory of income and trade that is best suited for short term forecasting. Urban Economic Growth The longer the period of time, the more important the resources and other supply factors of an urban area 1 1 6 are in determining urban income and its growth. In the long term, prices, technology, tastes, income dis tribution, and mobile resources are variable, and each urban area tends to generate a full-employment level of 1 17 m e ome. For any given combination of technology, labor productivity, labor force, capital stock, natural resources, transportation system, and economic organiza tion, there is a production possibility hyperplane that defines the full-employment combinations of all export and residentiary products and services produced by an urban economy. In a simple case in which the urban area is assumed to produce only two products— an export pro duct, X, and a residentiary product or service, R,— in competitive product markets, a production possibility curve (AB in Figure 27) depicts the set of full- employment combinations of exports and residentiary products. With a particular set of prices for export and residentiary products, a combination of export and resi dentiary products represented by point C in Figure 27 could be produced. At this set of prices, the first- 119 o B R Fig. 27*— Urban Production Possibility Curve order conditions for urban income maximization would be met; the marginal rate of transformation of export for residentiary products equals "the reciprocal of their price ratio. p dX _ IR dR “ Px The combination represented by point D would be produced if the price of the export product increased relative to the price of the residentiary product, but no economic growth would have occurred by producing combination D rather than C or vice versa. Urban economic growth occurs when the urban area produces more of the export product with no change in the quantity of the residen tiary product, more of the residentiary product with no change in the quantity of the export product, or more of both the export and the residentiary products. There fore, an urban area can experience economic growth only if its production possibility curve shifts out away from the origin beyond at least part of its original position. The production possibility curve shifts with changes in technology, labor force, productivity of labor, capital stock, natural resources, urban transportation system, 118 and economic organization. Figure 28 shows the original production possibility curve, AB, and three other hypothetical production possibility curves. The production 121 X F E C A O D B G Fig. 28.— Some Possible Shifts in the Unban Production Possibility Curve 122 possibility curve might shift from AB to CD if changes in the determinants of urban economic growth made possible the production of a larger maximum quantity of the export product but a smaller possible quantity of the residentiary product; here more of both the export and residentiary products can be produced only at rela tively small quantities of the residentiary ppoduct and at relatively large quantities of the export product. The production possibility curve might shift to EB if a change in growth determinants made possible the produc tion of a larger quantity of the export product, but did not affect the residentiary product. Production possi bility curve FG might result if the changes in the growth determinants made possible production of a larger quan tity of both the export and residentiary products. With a given production possibility curve, the full-employment combination of export and residentiary products that will tend to be produced depends on the prices of the products, which in turn depend upon market supply and demand conditions. Over time as national income increases, changes in demand for each export product of an urban economy will vary according to its income elasticity of demand. Differences in income elasticity of demand also account for differences in the 119 rate of growth between urban areas. 123 Changes in the demand for resources for use in producing export and residentiary products are derived from the changes in demand for the export and resi dentiary products. The location, or change in location, of resources depends upon the prices of resources in different uses in different urban areas. Resource prices in a particular urban economy are affected, not only by changes in product demands, but by (l) changes in resource combinations, which affect the productivity of each resource, (2) changes in resource costs outside the urban economy, and (3) changes in transport costs, both within 1 20 as well as outside the urban economy. These differ ences in resource prices are the principal determinants of mobile resource migration. Capital is the most mobile class of resource of the four basic classes of resources (labor, capital, 121 land, and entrepreneurship). Capital is allocated through capital markets according to its rate of return in alternative uses. If a particular urban economy affords profitable investment opportunities, capital will tend to migrate to that urban economy. An adequately high time rate of "foreign" capital investment is a key 1 22 factor in the economic growth of an urban economy. An expanding urban capital stock increases the productive 124 capacity of an urban economy and, ceteris paribus, increases the productivity, and, hence, the prices, of other resources in the urban economy. Higher resource prices induce migration of other mobile resources, such as labor, entrepreneurs, and raw materials. In this sense, urban growth can be viewed as a result of urban economic growth stimulated by positive net investment in 1 23 the urban economy. Differences in the rates of growth of urban economies would tend to disappear if real rates of return to resources were equalized within and among urban 124 economies. But market imperfectxons result in inequalities of real rates of return to resources in different uses in different urban economies. The following model of urban economic growth, which follows Horst Siebert's general model of regional economic growth, shows the relationships among most of 125 the important determinants of urban economic growth. This model describes the changes in economic variables of a particular open urban economy, city 1, in a two-city 126 world. This model consists of identities and behavioral equations in general functional form; again, actual dynamic urban economic growth processes are still not fully understood. Endogenous Variables: dc1 change in consumption in city 1 dD1 change in internal demand in city 1 E 1 inventions in city 1 E11 internal inventions in city 1 dl1 change in investment in city 1 t-i4 investment in city 1 between and t time t 1 ,I, 1 investment in city 1 between time t and b X J + I . ^ t + 1 1 dK change in capital stock in city 1 1 1 dK internal change in the capital stock of city 1 2 1 dK inflow of capital from city 2 to city 1 T dL change in labor force in city 1 1 1 dL internal change in the labor force in city 2 1 dL in-migration of labor from city 2 to city 1 1 dM change in imports to city 1 1 dQ change in potential output in city 1 1 dT change in technical knowledge in city 1 1 d¥ change in welfare in city 1 resulting from trade with city 2 1 dX change in exports from city 1 1 dY change in real income in city 1 126 Exogenous Variables: dB change in population in city 1 2 1 E inflow of new technical information from city 2 to city 1 dP change in the terms of trade between city 1 and city 2 R research expenditures 1 r rate of interest in city 1 ■ j r, . rate of interest in city 1 at time t - 1 t- 1 2 r, 1 rate of interest in city 2 at time t - 1 U ” I 1 S savings in city 1 w^ wage rate in city 1 2 w wage rate in city 2 2 dY change in real income in city 2 change in the barriers to trade between city 1 and city 2 e Model: rate of depreciation Real Income: t-idYLi = min C<t-idQi+i + t-idMi+i>’ (t-1dDi + 1 + + t-id w i+ i < 6 5 ) 127 Production Function: Capital : t-1dKl - t-1dK” + t-1dK?1 <67) t-idK" I1 = t-1 t = t-isl) (68> (69) dK21 = r2_i> (70) t-1 t Labor: dLI = *-,dL*1 + *.idL?1 (71) t-1dLt1 = f(dB> wi-1> (72) t-l^t1 = w t-1) < 7 3 > Technical Knowledge: t.,dTt = fK-i> t-idKi> t-i0t> » i - l = Elh + Et-1 (75) 1 1 E -1 = (76) 128 Internal Demand: t - i d D t + i = t - i dG t + i + t - i d I t + i ^77^ t-idrt+i _ t^+i " t-\xt ^ 7 9 ^ td " W i = f <r!> (80) Imports: 1 , ,, 1 Exports: t-1dXt+1 “ f^t-1dYt+1’ t-l^t+1^ Welfare: t-idWl+i - f(t-idPt+1) (83> The increase in real urban income, equation (65)9 is the smallest increase of supply or demand. The increase in potential output, equation (66), is a func tion of the increases in capital, labor, and technical knowledge from within the city and from city 2 , equa tions (67) through (76). An increase in internal demand, equation (77) is simply the sum of changes in consumption and investment, equations (78) through (80). The change in imports into city 1, equation (81), is a function of 129 the change in real income in city 1 and in the barriers to trade with city 2. The change in exports from city 1 to city 2, equation (82), is a function of the change in real income in city 2 and the barriers to trade with city 2. The change in the welfare effect, equation (83), is a function of the terms of trade between city 1 and city 2. From this general model and from a specific two- region model, Siebert derived 16 theorems or implications 1 27 concerning growth differences between regions. The content of these theorems is summarized below in terms of the effect of different factors on the growth differ ential among urban economies. Growth differentials vary directly with: Differences in the rate of inventions among cities. Relative rates of change in capital and labor among cities. Increase in the quantity of a resource in a city when that resource has a comparative advantage in production of the goods produced in that city. Relatively large differences in profit rates in favor of city 1 and relatively small differences in wages in favor of city 2. Reinforcing effects in the urban economy that tend to sustain and accentuate any original growth differentials. Mobility of factors that are induced by an increase in an autonomous growth factor in, say, city 1. (Example: An autonomous increase 130 in technical knowledge in city 1 may induce capital and, perhaps, labor in city 2 to migrate to city 1.) Immobility of pecuniary diseconomies in slowly growing regions. Growth differentials vary inversely with: Differences in the mobility of growth deter minants in different cities. Mobility of external economies. Tendencies to equalize urban social character istics. Degree of technical change in interurban trans portation systems. Interurban trade according to the principle of comparative advantage, if growth differentials are caused by factor immobility. This rein forcing effect is a function of changes in the terms of trade. Mobility of pecuniary external diseconomies in gr owing cities. Price increases of immobile factors in a growing city. Ease of substitution of mobile for immobile factors, making pecuniary external economies more mobile. Throughout this section, urban economic growth has been discussed without reference to the welfare of the residents of urban areas. Even if real urban income were the same in each city in a national or regional economy, substantial differences in per capita income among cities could exist because of the distribution of 131 1 28 different income earners among cities. Some reasons for interurban differences in per capita income are differences in wages because of different occupational distributions, differences in labor force participation rates, differences in the age distribution of urban popu lations, differences in racial composition, differences in the sexual composition of the labor force (related to differences in wages in different occupations), differences in the property-income earners as a percen tage of the urban population, and differences in prices of consumer goods. As urban areas grow in output and population, their industry mixes can be expected to become more diversified and per capita income differen- 129 tials can be expected to become increasingly smaller. Effects of Urban Economic Growth and Urban Growth Although urban economic growth and urban growth are complimentary dynamic processes, at least for analytical purposes, urban growth is assumed to be a function of urban economic growth rather than vice 1 30 versa. The combined effects of urban economic growth and urban growth are to diversify the urban industry mix, to increase the degree of specialization and division of labor, and to create external effects. 1 32 Beneficial and detrimental external effects of urban growth, tend to stimulate and depress, respectively, urban economic growth through their effects on produc tivity and income. Continued urban economic growth tends to be stabilized by the diversification of the industry mix resulting from earlier growth, and the increase in occupational and employment opportunities and retraining facilities accompanying the population growth helps to reduce structural unemployment. As an urban area grows, the population of cities with geographically fixed poli tical boundaries within the area can be expected to follow a growth trend, such as the logistic, or perhaps, the Gompertz or modified exponential trends. Population can especially be expected to exhibit these trends for cities in metropolitan areas which are old enough to have most of their land areas put to uses which change slowly in response to increasing population pressures. For example, even sustained annual influxes of migrants into a metropolitan area cannot be expected to result in proportionate increases in the population of, say, the central city in the area. Established capital invest ments and land uses, such as streets, parks, railway tracks and facilities,- commercial and industrial buildings, and multiple- and single-family dwelling units, are not 133 going to be radically changed within short, or even con siderably long, periods of time in response to increased demands for urban space. The resultant tendency is for land rents to increase. Furthermore, there may very well be a range of maximum residential and employment densities that most urbanites may tolerate before they change their residence or employment. The general form of the logistic trend for a 131 variable, y, is y (t) = (sit) 1 + be The general form of the Gompertz trend for such a vari- 132 able is y (t) = kab (85) and the general form of the modified exponential trend . 133 is y(t) = k + ab^. (86) The parameter k in all three trends is the upper asymptote of y as time increases without limit, lim y = k t-^oo (87) Population and many variables closely associated with human populations within a defined space tend to have a logistic or Gompertz time trend. Both trends have an S 13^ shape describing time series that increase by a decreasing 1 3k incremental percentage of increase. As the urban population increases, demands for residentiary products, such as food, clothing, housing, 1 35 manufactured products, and urban services, increase. These increased demands tend to increase the prices of consumers' goods and services, which, in turn, increase rents and shift the rent gradient upward. The result is a tendency for urban sprawl to occur as people and firms adjust their locations in response to the higher rents, many away from the high-rent center of the urban area. The increase in the population of an urban area also tends to increase the population density, especially in the core of the area. The increased population density is dampened by urban sprawl and suburbanization, which are facilitated by improved transportation technology embodied in more efficient mass- and/or rapid- transportation systems. Improvements in transportation technology reduce transportation costs and, therefore, reduce the slope of the rent gradient. The decrease in transportation costs of firms in the urban area tends to increase the quantity of goods and services, thereby decreasing prices. The decline in prices shifts down the rent gradient. The result is that people and firms tend 135 to expand away from the center of* the urban area in response to the lower cost of urban transportation as long as the price elasticity of demand for urban services is greater than that for agricultural products. In the United States, the urban sprawl resulting from growing urban population and improved transportation technology takes the form of suburbanization. Typically, those in the middle- and upper-income brackets, who can afford to move, migrate outward from the core and more central subareas of an urban area. This out-migration usually results in residential segregation of the urban population according to income and race, leaving slum areas in the central zone of the city. In the suburbs, communities tend to incorporate into small- or medium sized cities, and cities that at one time had been satellite cities of the central city gradually become engulfed within the expanding urban area. Rigidly established and tenaciously maintained political boun- 1 37 daries tend to politically fragment the urban area. This suburbanization and residential segregation tend to increase journey—to-work distances. As suburbanization takes place, many urban firms that no longer have to maintain central locations for accessibility to the previously concentrated labor force follow their 13 6 employees aiid relocate in the suburbs or in the urban- rural fringe area, away from the high-rent central zone of the urban area. However, the out-migration of the middle- and high-income families and of firms from the core of the urban area helps to produce a financial crisis in the central city(ies) of the urban area. Central cities typically are the home of most of the urban poor who, because of their low productivity and income, and perhaps race, in an environment of urban residential segregation by income and race, must live in slums and/or ghettos or ethnic sections of the central city. The concentration of low-income families in the central cities increases the cost of public services. The result is that central cities are left with a declining tax base in the face of inci'eased costs of public services. Urban economic growth, urban growth, and change in transportation technology not only affect the land use within a city, but the number, size and spacing of cities within a system of cities. Urban population increases result in increased demand for goods and ser vices in urban areas. The resulting increases in prices increase short-run profits and invite entry of firms into urban industries. The threshold, or smallest, size of 137 firms and trade areas would tend to decrease because population density is increased, and the number of first- order places tends to increase. The result is an increase in the number of cities, or shopping areas, closer toge ther . Increases in per capita income have the same effect as increases in population, except that there would be fewer persons served by each first-order place and the number of orders of places would decrease, assuming no change in total population. Industry output of products and resource allocation are affected by changes in per capita income according to the income elasticity of demand for different products. Improvements in transportation technology reduce the cost of transportation. Lower transportation cost reduces the price of goods and services at any given distance from the center of cities, thereby increasing the quantity demanded at each distance from the center. The trade areas of firms expand, increasing the demand for products at the plant (assumed to be located at the center of the city). This shift in demand creates short- run profits which invite entry of firms into the industry until price equals average cost. Given the population and its per capita income, a cost-reducing improvement In transportation technology tends to produce the same results as increases in population or per capita income, ceteris paribus: trade areas decrease in size, and the number of first-order places increases. However, if the increase in demand resulting from improvements in transportation technology allows firms to realize internal economies of large-scale production, the result will be a decrease in the size of places, an increase in the dis tance between them, and an increase in the number of cities, so as to accomodate a given total population. T39 L ilJ6s ^ko Footnotes to Chapter II 1 . The following sources were drawn upon heavily in preparing this section. William J. Baumol, Economic Theory and Operations Analysis (Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1965)> chap. xvi ; James M. Buchanan and William Craig Stubblebine, "Externality," Economica. XXIX (November, 1962), 371-38^-, reprinted in Readings in Microeconomics. ed. by William Breit and Harold M. Hochman (New York: Holt, Rinehart and Winston, Inc., 1968); James S. Duesenberry, Income. Saving and the Theory of Consumer Behavior (New York: Oxford University Press, 1967 ) » chap. vi; Jame s M. Henderson and Richard E. Quandt, Microeconomic Theory (New York: McGraw-Hill Book Company, Inc., 1958), chap. vii; James E. Hibdon, Price and Welfare Theory (New York: McGraw-Hill Book Company, Inc., 1969) ; Ezra J. Mishan, Welfare Economics (New York: Random House, 196^); Jerome F. Rothenberg, The Measurement of Social Welfare (Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1961); Paul A. Samuelson, Foundations of Economic Analysis (New York: Atheneum, 19^5) > chap! viii; Gerhard Tintner, "A Note on Welfare Economics,’1 Econometrica. XIV, 1 (January, 19^-6), 69-78. 2. Ezra J. Mishan, "A Survey of Welfare Economics, 1939-59>" in Surveys of Economic Theory. Vol. I (London: Macmillan & Co., Ltd.”, 19^5) , pp. 156-157. 3. Ibid., p. 155. h. Mishan, Welfare Economics, pp. 2^-25. 5• See Henderson and Quandt, Microeconomic Theory, p. 213. 6. Tibor Scitovsky, "Two Concepts of External Economies," Journal of Political Economy, LXII (April, 195^)> 1^3-151. 7* Ezra J. Mishan, The Costs of Economic Growth (New York: Frederick A. Praeger, Publishers, 1967), pp. 81-82. 141 8. Vilfredo Pareto. Cours d^Economie Politique (Laussane, 1897); Nicholas Kaldor, "Welfare Propo sitions in Economics," Economic Journal. XLIX (1939), 5^-9-552; John R. Hicks, "Foundations of Welfare Economics," Economic Journal, XLIX (1939), 696-712; Tibor Scitovsky, "A Note on Welfare Proposition in Economics," Review of Economic Studies, IX (l94l), 77-88; Abram Bergson, "A Reformulation of Certain Aspects of Welfare Economics," Quarterly Journal of Economics. LII (1938), 310-33^. 9. The following demonstration is from Henderson and Quandt, Microeconomic Theory, pp. 218-219* 10. Kenneth J. Arrow, Social Choice and Individual Values, 2nd ed. (New York: John Wiley & Sons, Inc., 1963)• For criticisms of Arrow's impossibility theorem on the basis of the assumed conditions of Arrow's analysis, see: Julian H, Blau, "The Existence of Social Welfare Functions," Econometrica, XXV, 2 (April, 1957), 302-313; Leo A. Goodman and Harry Markowitz, "Social Welfare Functions Based on Individual Rankings," American Journal of Sociology. LVIII (November, 1952), 257-262; Clifford Hildreth, "Alternative Conditions for Social Orderings," Econometrica. XXI (January, 1953), 81-91. 11. Johann Heinrich von Thunen, Per Isolierte Staat in Beziehung auf Landwirtshaft und Nationalokonomie (Hamburg, 1st vol. , 1 826, 3^d"volTI and new ed . , 1863). 12. Especially see Wilhelm Launhardt, "Die Bestimmung des Zweckmassigsten Standortes einer gewerblichen Anlage," Zeitschrift des Vereins deutschen Ingenieure"! XXVI, 3 ( 1882) and Mathematische Be grundung der Volkswirtschaftslehre (Leipzig: B. G. Teubner, 1885). 13. Alfred Weber, Uber den Standort der Industrien (Tubingen, 1909)» trans. by Carl J. Friedrich as Alfred Weber's Theory of the Location of Industries (Chicago: University of Chicago Press, 1928); 142 August Los ch., Die raumliche Ordnung der Wirtschaft, 2nd ed. (Jena: Gl Pi sc'he'r, 1944) , trans. by William H. Woglom with Wolfgang F. Stolper as The Economics of Location (New York: John Wiley & Sons, Inc., 1967). 14. Walter Isard, Location and Space-Economy (Cambridge, Mass. : The M. iT T\! Press, 1956). 15* For surveys and evaluations of some of the prin cipal contributors to location theory and related topics see: Isard, Location and Space-Economy; Melvin L, Greenhut, Plant Location in Theory and in Practice (Chapel Hill: The University of North Carolina Press, 1956). 16. Weber, Theory of the Location of* Industry. 17. For a cricitism of this approach and an alternative approach based on delivered, rather than source prices of resources, and on a production function with substitutable resources, rather than the linear production function assumed by Weberian location theorists, see Leon N. Moses, "Location and the Theory of Production," Quarterly Journal of Economics. LXXII, 2 (May, 1958), 259-272. Moses shows that the optimum location depends upon source prices of resources, transport rates for resources and the product, location of resources and markets, production function, and demand function. Also for a criticism of Weber, See S. R. Dennison, "The Theory of Industrial Location," Manchester School of Economics and Social Studies. VIII (1937)> 23-47. 18. Edgar M. Hoover, Location Theory and the Shoe and Leather Industries (Cambridge, Mass. : Harvard University Press, 1937); Isard, Location and Space-Economy: Harold W. Kuhn and Robert E. Kuenne, "An Algorithm for the Weber Problem," Journal of Regional Science. W (1962), 21-23. 19. Nourse, Regional Economics. A Study in the Economic ; Structure. Stability, and Growth of Regions (New York: McGraw-Hill Book Company, Inc., 1968), pp. 85-92. i i 1^+3 20. Hoover uses the technique of margin lines to illus trate how a firm at point A in Figure 29 could undersell a competitor at point B, assuming that consumers are uniformly distributed along the line AB. The line BFGIJE is the margin line of the firm at point A; DC is the margin line for the firm at point B. The margin line is the locus of points showing the delivered price of the product at the different distances from the point of pro duction that correspond with different average costs of production. For example, if the radius of the market area of the firm at A is AO, the delivered price of OF at distance AO will exactly cover the average cost of production, AB, plus the cost of transporting the product the distance AO. The transport gradient, BF, shows the delivered price of the product at different distances from A, when average cost of production at A is AB. If internal economies of large-scale production can be realized, such as if average cost of production can be decreased from AB to AK by expanding the scale of production at A, all consumers could be served by the firm at A and industrial production would be concentrated at A, and the firm at B will have to go out of business. On the other hand, if at some point along the line AB the transport gradients of the firms at A and B were to inter sect, that distance at which they intersected would define the joint boundaries of the market areas of the firms at A and B. See Hoover, Location Theory and the Shoe and Leather Industries, pp. 9^-99• Also see Isard, Location and Space-Economy, PP. 173-176. 21. Edward Austin Gossage Robinson distinguishes between mobile and immobile external economies of scale. Mobile external economies of scale are realized regardless of the locations of the firms com prising the industry. Immobile external economies can be realized by firms only by locating at the source of the immobile external economies of scale. See Edward Austin Gossage Robinson, The Structure of Competitive Industry (Chicago: The University of Chicago Press, 1958). 22. 23. 24. 25* 26 . 27. 28 . 29. 30. 144 Richard A. Bilas, Microeconomic Theory; A Graphical Analysis (New York: McGraw-Hill Book Company, Inc., 1967), p p . 170-171. Ibid. Henderson and Quandt, Microeconomic Theory, pp. 92- 97, 169. Isard, Location and Space-Economy, pp. 176-182. For the use of game theory in studying industrial location, see Walter Isard, "Game Theory, Location Theory and Industrial Agglomeration," Regional Science Association Papers. XVIII (1967),1-11 and Walter Isard and Tony E. Smith, "Location Games: With Applications to Classic Location Problems," Regional Science Association Papers. XIX (1967), 45-80. Hoover defines urbanization economies as "economies for all firms in all industries at a single loca tion, consequent upon the enlargement of the total economic size (population, income, output, or wealth) of the location, for all industries taken together." Hoover, Location Theory and the Shoe and Leather Industries, p. 91* Nourse, Regional Economics, pp. 89-90. Isard, Location and Space-Economy, pp. 182-183. Hoover, Location Theory and the Shoe and Leather Industries. chap. vi; Isard, Location and Space- Ec onomy. chap. viii. Isard says that, ". . .with respect to each firm, there are attracting and repelling forces for location in rural areas and in cities of different sizes. When the potential savings of a location shift override the additional costs involved, the firm will shift. In doing so, it will be substi tuting one set of outlays and revenues for another set." Isard, Location and Space-Economy. p. 188. Isard seems to mean that the "attracting and repelling forces" comprise all of the cost savings j and dissavings of moving to a particular location. However, from the general context of the chapter, he j implies that these "forces" refer only to agglomera-: tion economies (diseconomies). Losch, The Economics of Location; Walter Christaller, Die zentra'len Orte in Siiddeutschland (Jena: ~G~. Fischer, 1933)» trans. by C. wl Baskin as Central Places in Southern Ge: ~ (Englewood Cliff's, N. J.: Losch, The Economics of Location. Losch, The Economics of Location, chap. xxiv, The variables, equations, and conditions of the Loschian theory are summarized in Isard, Location and Space-Economy, pp. 45-47- Wolfgang F. Stolper, American Economic Review. XXIII, 3 (September, 1943), 626-636. Isard, Location and Space-Economy, p. 48 (footnote 38) and pp. 271-274. Ibid., pp. 271-274. Ibid., p . 274. Martin J. Beckmann, "City Hierarchies and the Distribution of City Size." Economic Development and Cultural Change, VI (1958), 243-248. This model is also discussed in Nourse, Regional Economics, pp. 40-44. Recently, Jan Tinbergen developed a hierarchy model of the size distribution of cities in which he derived (1) the total income earned in all cities of a given rank or lower as a function of national income. (2) the number of cities of a given rank, and (3) the number of enterprises of a particular rank in each city of a given rank. See Jan Tinbergen, "The Hierarchy Model of the Size Distri bution of Centers," Regional Science Association Papers, XX (1968), 65-68. Beckmann, "City Hierarchies and the Distribution of City Size;" George Kingsley Zipf, National Unity and Disunity (Bloomington, Ind.: Principia Press, 1941) and Human Behavior and The Principle of Least Effort (Cambridge, Mass. : Addison-Wesley Publishing Company, Inc., 1949), chaps, ix and x. Prentice-Hall, Inc., Also see Brian J. L. Berry and ‘ William L. Garrison, "Alternate Explanations of Urban Rank-Size Relation ships," Annals of the Association of American Geographers. XLVIII. 1 (March, 1958), 83-91. Zipf, Human Behavior and The Principle of Least Effort. p. 359- Earlier work with this type of relationship was done by: F. Auerbach, "Das Gesetz der Bevolkungskonzentration," Petermann1s Geographische Mitteilungen. LIX ( 1913*71 H* W. Singer, "Courbes des Population: A Parallel to Pareto's Law," Economic Journal, XLVI (1936), 254-263. For later applications of the rank-size rule, see: John Q. Stewart, "Empirical Mathe matical Rules Concerning the Distribution and Equilibrium of Population," The Geographical Review (July, 19^7), 461-485; G. R. Allen, "The 'Courbe des Populations', A Further Analysis," Bulletin of the Oxford University Institute of Statistics, CLXVT (1954), 179-189 > Rutledge Vining, "A Description of Certain Spatial Aspects of an Economic System," Economic Development and Cultural Change. Ill (1955 ) » 147-195; Edgar M. Hoover, "The Concept of a System of Cities: A Comment on Rutledge Vining's Paper," Economic Development and Cultural Change. Ill (1955), 196-198; Brian J. L. Berry, H. G. Barnum and Robert J. Tennant, "Retail Location and Consumer Behavior," Regional Science Association Papers and Proceedings, IX (1962), 65”106. Also see Isard, Location and Space-Economy, chap. iii. Beckmann, "City Hierarchies and the Distribution of City Size." Beckmann also outlines the application of the bio logical law of allometric growth to the distri bution of cities and mentions Herbert A. Simon's application of the Yule distribution. Herbert A. Simon, "On a Class of Skew Distribution Functions," Biometrika. XLII, Pts. 3 and 4 (1955), 225-240 and included as chapter ix of Simon's Models of Man (New York: John Wiley & Sons, Inc~ 1957) • Also see Brian J. L. Berry, "Cities as Systems Within Systems of Cities," Regional Science Association Papers. XIII (1964), reprinted in Regional Development and Planning, ed. by John Friedmann and William Alonso (Cambridge, Mass.: The M. I. T. Press, 1964), chap. vi. 147 44. See Carl R. Bye, Developments and Issues in the Theory of Rent (New York: Columbia University Press, 1940). 45. Johann Heinrich von Thiinen, Der Isolierte Staat in Beziehung auf Nationalokonomie und Landwirtschaft (Hamburg,1826) , trans. by C. M.Wartenberg as von Thiinen 1 s Isolated State (New York: Pergamon Press , 1966) . For later developments of1 agricul tural location theory, see Edgar S. Dunn, Jr., The Location of Agricultural Production (Gainsville: University of Florida Press", 195^-) 5 Losch., The Economics of Location, pp. 36-67; Hoover, Location Theory and the Shoe and Leather Industries. 46. Dunn, The Location of Agricultural Production. P- 99 • 47. Bertil G. Ohlin, "Some Aspects of the Theory of Rent: von Thiinen vs, Ricardo,” in Carver Festschrift: Economics, Sociology, and the Modern World, ed. by N. Hines (Cambridge, Mass., ' I 935)» Michael Chisholm, "Agricultural Production, Location, and Rent," Oxford Economic Papers, XIII, 3 (October, 1961 ) , 342-359- 48. Losch, The Economics of Location; Hoover, Location Theory and the Shoe and Leather Industries. chap. ii. 49. Von Thiinen, Von Thiinen * s Is plaited State, pp. 7-8; Nourse, Regional Economics, pp. 96-97; Richard F. Muth, "Economic Change and Rural-Urban Land Conversions," Ec onometrica. XXIX (January, 1961), 1 -23 . 50. Dunn, The Location of Agricultural Production, chap. i and appendix A. 51. The terms "bid rent function" and "bid rent curve" are used by William Alonso to denote the maximum rent per unit of land bid for a given use at different distances from the town. William Alonso, Location and Land Use (Cambridge, Mass.: Harvard University Press, 1965)» P* 41. 148 52. Nourse points out that the slope of the bid rent curve of a given industry varies inversely with the degree of substitution of land for nonland resources, making the bid rent curve convex to the origin. Noursej Regional Economics, p. 102. 53. Alonso, Location and Land Use, p. 4. 54. Alfred Marshall, Principles of Economics. 9th ed. (London: Macmillan and Co., Ltd. , 1961 ) , Bk. 5» chap. isi,. pp. 440-454 and appendix G, pp. 794-804. 55- Edward Hastings Chamberlain, The Theory of Mono polistic Competition, 8th e d . (Cambridge, Mass. Harvard University Press, 1962), appendix D. 56. For a summary history of the principal contributors to urban land economics, see Alonso, Location and Land Use, chap. i. Richard M.' Hurd, Principles of City Land Values (New York: The Record and Guild, 1903)J Ernest ¥. Burgess, "The Growth of the City: An Introduction to a Research Project," in Robert Ezra Parks, Ernest W. Burgess, and Rocbrick D. McKenzie, The City (Chicago: University of Chicago Press, 1925) > pp. 47-62; Robert Murray Haig, "Toward an Understanding of the Metropolis," Quarterly Journal of Economics, XL (May, 1926), 179-208, 402-434; Roderick D. McKenzie, The Metropolitan Community (New York: McGraw-Hill Book Company, Inc., 1933); Walter Firey, Land Uses in Central Boston (Cambridge, Mass.: Harvard University Press, 1947); Richard U. Ratcliff, Urban Land Economics (New York: McGraw-Hill Book Company, Inc., 1949); Amos H. Hawley, Human Eco1ogy (New York: Ronald Press, 1950); Lowdon Wingo, Jr., Transportation and Urban Land (Washington, D. C. : Resources for the Future, Inc., 1961); Isard, Location and Space-Economy. See also Nourse, Regional Economics and Edwin von Boventer, "Land Values and Spatial Structure: Agricultural, Urban and Tourist Location Theories," The Regional Science Association Papers and Proceedings, XVIII ( 1967)> pp. 231-242. 149 57* Isard points out that this problem has n variables, n dimensions, and n-1 spaces. If total revenue is a function of, say, distance, and advertising out lay, the curve in Figure 17 would be the total revenue curve, given the advertising outlay. Isard uses effective distance adjusted for travel time and cost, rather than simple distance. Isard, Location and Space-Economy, pp. 200-201. 58. Because anticipated total revenue from a parti cular land use at a given distance from the center of the city is a function of several variables, the bid rent curve in Figure 19 would be only one of perhaps an infinite number of such curves, depending on the combination of values in inde pendent variables. The true bid rent curve would lie above this curve and would be tangent to this curve at at least the point (k, R). See Isard, Location and Space-Economy. p. 203. 59- Nourse, Regional Economics, p. 106. 60. Ibid., pp. 107-110. 61. The composite isocost curves are constructed from the two isocost curves for the central city site and the site at a distance k from the center of the city for given outlays. 62. Colin Clark, "Urban Population Densities," Journal of the Royal Statistical Society, series A, CXIV, pt. 4 (1951), 490-496. 63. Colin Clark, Population Growth and Land Use (New York: St. Martin1s Press, 1967 ) j chap. ix. 64. John F. Kain, "The Journey-to-Work as a Determinant of Residential Location," The Regional Science Association Papers and Proceedings. IX (19^2 ) , 137-160; Louis K. Loewenstein, The Location of Residences and Work Places in Urban Areas (New York: The Scarecrow Press, 1965)■ 65. Bruce E. Newling used Clark’s negative exponential population density function and a negative expo nential trend for b as the axioms of a partial theory of urbanization. See Bruce E. Newling, 150 "A Partial Theory of Urban Growth.: Mathematical Structure and Planning Implications," paper pre sented at the Latin American Regional Conference of the International Geographical Union (Mexico City, Mexico, August 5» 1966). 66. Brian J. L. Berry, James W. Simmons, and Robert J. Tennant, "Urban Population Densities, Structure and Change," The Geographical Review. LIII (1963), 389-^05. 67. H. K. Weiss, "The Distribution of Urban Population and an Application to a Servicing Problem," Operations Research. IX (1961), 860-87^. 68. Brian J. L. Berry, "Cities as Systems Within Systems Pf Cities," The Regional Science Association Papers. XIII (1964), 147-163. 69. The form of the city at the time that the city developed is a major determinant of the future density of the population living at its center. See Hal H. Winsborough, "City Growth and City Structure," Journal of Regional Science. IV (1963)5 35-^9. 70. Berry, "Cities as Systems Within Systems of Cities." 71. Richard F. Muth, "The Spatial Structure of the Housing Market," The Regional Science Association Papers and Proceedings, VII (1961), 207-220; William Alonso, "A Theory of the Urban Land Market," The Regional Science Association Papers and Proceedings"] VI ( 1 960 ) , 1 49- 1 57 and Location and Land Use, chap. iv. Also see,Wingo, Transportation and Urban Land. 72. Nourse, Regional Economics, p. 114. 73* Ibid. 74. Ibid., p. 117. 75* Edwin von Boventer, "Towards a United Theory of Spatial Economic Structure," The Regional Science Association Papers and Proceedings. X (1963), 163-187, esp, 186-187. Isard, Location and Space- Economy. chap. xi. 151 76. 77. 78. 79. 80. 81 . 82. 83. Chauncy D. Harris and Edward L. Ullman, "The Nature of* Cities," The Annals of the American Academy of* Political and Social Science, CCXLII (November, 1945), 7-17. Burgess, "The Growth of the City: An Introduction to a Research Project," pp. 47-62 and "Urban Areas," in Chicago: An Experiment in Social Science Research (Chicago: University of Chicago Press, 1929), PP. 114-123. For a distinction between the implications of the concentric-zone and sector hypotheses for urban renewal policies and those derived through urban land use theory, see William Alonso, "The Historic and the Structural Theories of Urban Form: Their Implications for Urban Renewal," Land Economics (May, 1964), 227-231. Burgess called this aspect of areal expansion succession. Burgess, "The Growth of the City: An Introduction to a Research Piqject," p. 50* M. R. Davie, "The Pattern of Urban Growth," in Studies in the Science of Society, ed. by G. P. Murdock (New Haven, Conn.: Yale University Press, 1937)) PP« 133-161; James A. Quinn, "The Burgess Zonal Hypothesis and Its Critics," American Sociological Review. V (1940), 210-218. Homer Hoyt, The Structure and Growth of Residential Neighborhoods in American Cities (Washington, D . c 7 : U. S. Federal Housing Administration, 1939). For earlier discussion of the axial expansion and extension of cities along transportation routes extending from the center of the city, see Hurd, Principles of City Land Values. For numerous illustrations of theoretical patterns of rent areas in 30 American cities, see Hoyt, The Structure and Growth of Residential Neighborhoods in American Cities, Fig. 28, p. 77* Both the concentric-zone and sector hypotheses imply the "filtering" process in urban housing. "Filtering" refers to the gradual movement over time of all but the wealthiest households into better quality or larger housing units vacated by 152 wealthier households as the wealthiest households buy new housing units. See Hatelit1, Urban Land Economics, pp. 321-324; Ira S. Lowry, "Filtering and Housing Standards," Land Economics. XXXVI (November, i960), 362-370? William G. Grigsby, "The Filtering Process," in Urban Housing, ed. by William L. C. Wheaton, Grace Milgram, and Margy Ellin Meyerson (New York: The Free Press, 1966), pp. 191-201. 84. Hoyt, The Structure and Growth in Residential Neighborhoods in American Cities, pp. 114, 117-119* 85* For criticism of the sector hypothesis, see Firey, Land Use in Central Boston. Also see a series of* discussions of Hoyt's and Firey's ideas in Lloyd Rodwin, "The Theory of Residential Growth and Structure," The Appraisal Journal. XVIII (1950), 295-317; Homer Hoyt, "Residential Sectors Revisited," The Appraisal Journal, XVIII (1950)» 445-450; Walter Firey, "Residential Sectors Re-Examined," The Appraisal Journal, XVIII (1950)> 451-453; Lloyd Rodwin, "Rejoinder to Dr. Firey and Dr. Hoyt," The Appraisal Journal, XVIII (1950), 454-457. Hoyt re-evaluates the sector hypothesis in Homer Hoyt, "Recent Distortions of the Classical Models of Urban Structure," Land Economics {May. 1964), 199-212. 86. Harris and Ullman, "The Nature of Cities." For the earlier presentation of the idea of multiple nuclei, see Roderick D. McKenzie, The Metropolitan Community, p. 198. 87. Harris and Ullman, "The Nature of Cities," Fig. 5> P. 13. 88. For a more recent evaluation of the multiple nuclei hypothesis, see Edward L. Ullman, "Presiden tial Address: The Nature of Cities Reconsidered," The Regional Science Association Papers and Proceedings^ IX (1962) , 7-23• 89- Adam Smith, An Inquiry into the Nature and Causes of the Wealth of Nations (New York: Random”House, Inc . , 1 937)f chaps'. i through iii; George Stigler, "The Dividion of Labor is Limited by the Extent of the Market." Journal of Political Economy. LIX, 3 (June, 1951). 153 90. For a view of* specialization as a culturally deter mined phenomenon, see Eric E. Lampard, "The History of Cities in the Economically Advanced Areas," Economic Development and Cultural Change. Ill fjanuary, 1955)» 81-102. 91. Ibid. Stigler, "The Division of Labor is Limited by the Extent of the Market." 92. Edgar M. Hoover, The Location of Economic Activity (New York: McGraw-Hill Book Company, Inc., 1948), pp. 120-121. 93. Lampard, "The History of Cities in the Economically Advanced Areas," p. 331. 94. Allyn A. Young, "Increasing Returns and Economic Progress," Economic Journal. XXXVIII (December, 1928), 527-5^2. 95* Lampard, "The History of Cities in the Economically Advanced Areas," p. 336 citing P. S. Florence, "Economic Advantages and Disadvantages of Metro politan Concentration," Columbia University Bicentennial Conference I (January, 1954), mimeo. 96. A. G. B. Fisher, "Capital and the Growth of Knowledge," Economic Journal. XLIII (1933)» 379-389. 97* Colin Clark, "The Economic Functions of a City in Relation to Its Size," Econometrica. XIII, 2 (April, 19^5), 97-113. 98. A. G. B. Fisher, "Capital and the Growth of Knowledge;" "Production Primary, Secondary and Tertiary," Economic Record. XV (June, 1939)> 24-38; and The Conditions of Economic Progress (London, 194o7I 99. Morgan D. Thomas, "Regional Economic Growth and Industrial Development," The Regional Science Association Papers and Proceedings. X (1963)> 61-75 154 100. Edgar M. Hoover and Joseph. Fisher, "Research in Regional Economic Growth," in UniversitiesiNational Bureau Committee for Economic Research, Problems in the Study of Economic Growth (New York: National Bureau of Economic Research, 1949), chap. v. The Hoover-Fisher stages of regional economic growth are summarized and discussed in Douglas C. North, "Location Theory and Regional Economic Growth, " Journal of Political Economy. LXIII (June, 1955)» 243-258 and reprinted in Regional Development and Planning, ed. by John Friedmann and William Alonso (Cambridge, Mass.: The M. X. T. Press, 1964), pp. 240-255• 101. Wilbur R. Thompson, A Preface to Urban Economics (Baltimore: The Johns Hopkins Press, 1965)> pp. 15-16. 102. Ibid., pp. 16-18. 103. Ibid., pp. 21-24. 104. Ibid., pp. 22-24 105. Ibid. , p. 27. 106. Nourse, Regional Economics, pp. 155-160; Lloyd A. Metzler, "A Multiple-Region Theory of Income and Trade," Econometrica. XVIII, 4 (October, 1950)» 329-354. 107. Nourse, Regional Economics, p. 160. 108. Werner Sombart, "Der Begriff der Stadt und das Wesen der Stadtebildung," Archiv fur Sozial- wissenschaft und Sozialpolitik. XXV ( 1907)» 1 • 109. Walter Isard, Methods of Regional Analysis (Cambridge, Mass.: The M. I. T. Press, i960), chap. vi; Douglas C. North, "Location Theory and Regional Economic Growth;" Charles Tiebout, "Exports and Regional Economic Growth," Journal of Political Economy. LXIV (April, 1956), See also Rutledge Vining, "Location of Industry and Regional Patterns of Business-Cycle Behavior," Econometrica. XIV, 1 (January, 1946), 37-68 and 155 "The Region, as an Economic Entity and. Certain Variations to be Observed in the Study of* Systems of Regions," American Economic Review, Papers and Proceedings of the American Economic Association (May, 194989- 104-; George Hildebrand and Arthur Mace, Jr., "The Employment Multiplier in an Expanding Industrial Market: Los Angeles County, 1940-47," Review of Economics and Statistics. XXXII, 3 (August, 1950), 241-249. 110. Robert Murray Haig and Roswell C. McCrea, Ma.jor Economic Factors in Metropolitan Growth and Arrangement: A Study of- Trends and Tendencies in the Economic Activities Within the Region of* New York and Its Environs. Vol. I of Regional Study of New York and Its Environs (New York, 1927)* 111. Arthur M. Weimer and Homer Hoyt, Principles of Urban Real Estate (New York: The Ronald Press Company, 1939* 1948, 1954); Homer Hoyt, "Economic Background of Cities," Journal of Land and Public Utility Economics (May, 1941), 188-195 and "Homer Hoyt on the Concept of the Economic Base," Land Economics. XXX (May, 1954), 182-186; The Regional Plan Association, Inc., The Economic Status of the New York Metropolitan Region in 1944 (New York, 1944) ; Charles M^ Tiebout, The Community Economic Base Study. Supplementary PaperNo. 1 6 (New York: Committee for Economic Development, 1962); Thompson, A Preface to Urban Economics and "Internal and External Factors in the Development of Urban Economies," in Issues in Urban Economics, ed. by Harvey S. Perloff and Lowdon Wingo, Jr. (Baltimore: The Johns Hopkins Press, 1968), pp. 43-80. The following articles are reprinted in The Techniques of Urban Economic Analysis, ed. by Ralph W. Pfouts (West Trenton. N\ J.: Chandler-Davis Publishing Company, i960); Richard B. Andrews, "Mechanics of the Urban Economic Base: Historical Development of the Base Concept," Land Economics. XXIX, 2 (May, 1953), 161-167; "Mechanics of the Urban Economic Base: The Problem of Terminology," Land Economics. XXIX, 3 (August, 1953)> 263-268; "Mechanics of the Urban Economic Base: A Classi fication of Base Types," Land Economics. XXIX, 4 (November, 1953)» 343-350? "Mechanics of the Urban Economic Base: The Problem of Base Measurement," 156 Land Economics, XXX, 1 (February, 1954), 52-60; "Mechanics of the Urban Economic Base; General Problems of Base Identification,1 ' Land Economics. XXX, 2 (May, 1954), 164-172; "Mechanics of the Urban Economic Base; Special Problems of Base Identification,V Land Economics, XXX, 3 (August, 1954), 260-269; "Mechanics of the Urban Economic Base: The Problem of Base Area Delimitation," Land Economics, XXX, 4 (November, 1954), 309-319; "Mechanics of the Urban Economic Base; The Concept of Base Ratios," Land Economics. XXXI, 1 (February, 1955)> "Mechanics of the Urban Economic Base: The Base Concept and the Planning Process," Land Economics. XXXII, 1 (February, 1956), 69-84; Hans Blumenfeld, "The Economic Base of the Metropolis," Journal of the American Institute of Planners, XXI (Fall, 1955)> 114-132; John W. Alexander, "The Basic-Nonbasic Concept of Economic Functions,V Land Economics. XXXII, 1 (February, 1956), 69-84; Charles M. Tiebout, "The Urban Economic Base Reconsidered," Land Economics, XXXII, 1 (February, 1956), 95-99 and "Community Income Multiplier: A Casd Study," paper delivered before the Joint Conference of the Econometric Society and The American Statistical Association (Detroit, Mich.j September, 1956); Ralph ¥. Pfouts and Erie T. Curtis, "Limitations of the Economic Base Analysis," Social Forces. XXXYI, 4 (May, 1958), 303-310; Charles E. Ferguson, "Statics, Dynamics and Economic Base," 325-340. 112. Charles M. Tiebout, The Community Economic Base Study, chap. vi. 113. Ibid., p. 70. 114. Ibid., p. 69. 115* Ibid., p. 70; Nourse, Regional Economics, pp. 161- 163. 116. Thompson, A Preface to Urban Economics, p. 37* 117* Although actual dynamic urban economic growth pro cesses are not fully understood, certain hypotheses, principles, and models of economic growth seem to be applicable to the study of urban economic 157 118. 119. 120. 121 . 122 . 123. 124. 1 2 5. growth. The following discussion of some of these topics draws heavily on the following sources: Nourse, Regional Economics, chap. viii; Thompson, A Preface to Urban Economics, especially chap. i; George II. Borts and Jerome L. Stein, Economic Growth in a Free Market (New York: Columbia University Press, 1964), especially chap. vii; Douglas C. North, "Location Theory and Regional Economic Growth," Journal of Political Economy, LXIII (June, 1955)» 243-258; Charles Tiebout, "Exports and Regional Economic Growth," Journal of Political Economy, LXIV (April, 1956), 160-169; Horst Siebert, Regional Economic Growth: Theory and Policy (Scranton, Penn.: International Text book Company, 1969)* Nourse, Regional Economics, pp. 186-187. Ibid., pp. 192-197. Ibid. Thompson, A Preface to Urban Economics, p. 51• Nourse argues that capital stock is considerably immobile and discusses the costs and returns of relocating capital in Nourse, Regional Economics, pp. 205-207. Urban economic growth can be stimulated by invest ment out of increased local saving, but only at the expense of a decrease in local expenditure. Rates of return on capital investment in a parti cular urban economy may be relatively high because of the relatively large stock, or increase in the stock, of other productive resources, such as a large, diversified, and skilled labor force. Here, capital investment can be viewed as a result of urban economic growth stimulated by an increase in the productive capacity of the urban economy resulting from increases in noncapital resources. Nourse, Regional Economics, p. 197. Siebert, Regional Economic Growth: Theory and Policy, pp.119-124. 158 126. 127. 128. 129. 1 30. 131 . 132. 133. 13^. Superscripts refer to the origin and destination of a variable, and subscripts refer to the time period that the variable refers to. For example, „dK^? means the increase in capital in city 1 — ► 1 * f c between time t-1 and t that came from city 2. Siebert, Regional Economic Growth: Theory and Policy, chap. vii. Nourse, Regional Economics, p. 197* Thompson, A Preface to Urban Economics, p. 193. This assumption is all the more reasonable for cities in the United States in the 1960s. With the decline in the rate of rural-to-urban migra tion and the increasing importance of interurban differences in rates of urban growth, urban economic growth should become an increasingly more important determinant of the urban growth. Gerhard Tintner, Econometries (New York: Science Editions, John Wiley & Sons, Inc., 19^5), pp. 208- 211. Frederick E. Croxton, Dudley J. Cowden, and S. Klein, Applied General Statistics, 3^’ d ed. (Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1967), pp. 262-267. Ibid., pp. 267-269. For details on parameter estimation and use of growth trends, especially the logistic trend, see: Raymond Pearl, Studies in Human Biology (Baltimorej 1924), chap. xxiv; Harold Hotelling, "Differential Equations Subject to Error and Population Estimates," Journal of the American Statistical Association. XXII (1927)> 283-31^J 57 Schultz, "The Standard Error of a Forecast from a Curve," Journal . o f * the American Statistical Association. XXY (1930), 139-185; E. C. Rhodes, "Population Mathematics III," Journal of the Royal Statistical Society. CIII (19^0) ; Harold T. Davis, The Analysis of Economic Time Series (Bloomington, Ind. : Principia Press, 19^1), pp. 2^7-251; Tintner, Econometrics. pp. 208-210; Croxton, Cowden, and Klein, Applied General Statistics. 159 135. 136. 137. The remainder of* this section is based on the following works. Thompson, A Preface to Urban Economics. pp. 382-3&3 Nourse, Regional Economics, chap. ix. See John Robert Meyer, John F. Kain, and Martin Wohl, The Urban Transportation Problem (Cambridge, Mass.: Harvard University Press, 1965). For example, in 1969* Los Angeles County included 77 incorporated cities, and Los Angeles County is only part, although the major part, of the Los Angeles - Long Beach Metropolitan Statistical Area. See County of Los Angeles, Regional Planning Commission, Quarterly Bulletin. Population and Dwelling Units. Quarterly Bulletin No. 105 (July 1, 1969). CHAPTER III SOME EXTERNAL DISECONOMIES OF URBAN GROWTH OF THE LOS ANGELES AREA The purposes of this chapter are (1) to study population and economic growth of the Los Angeles area and (2) to study the relationships between (a) population and economic growth and other appropriate variables and (b) selected variables that are treated as external diseconomies of urban growth. Although this study focuses on Los Angeles, data on some variables for Los Angeles County are used either because it is as appro priate or more appropriate to study the variable at the county level or because of data limitations. Following an historical review of the population and economic growth of the Los Angeles area, problems of increased land values, traffic congestion, air pollution, crime, and government expenditure are studied in their relation ship to the population and economic growth of the area. Because of multicollinearity between the inde pendent variables, especially population and per capita personal income in constant dollars, used to study the selected external diseconomies, most statistical analyses 160 161 are limited to bivariate rather than multivariate 1 analysis. The typically few degrees of freedom in these analyses also limit the use of multivariate analysis. Although causality is implied in the analyses, structural parameters cannot be estimated with accuracy because of the presence of multicollinearity. Con sequently, the analyses in this chapter are presented principally to show the degree of association between the specified variables, rather than structural relation ships between them. 2 Population and Economic Growth Two hundred years ago, in 17^9, a party of Spanish explorers led by Gaspar de Portola discovered what is now known as the Los Angeles area. Two years later, Mission San Gabriel was established, and in 1781, the El Pueblo de Nuestra Senora la Reina de Los Angeles was founded by 44 settlers from Sinolca and Sonora, Mexico. Relatively self-sufficient but inefficient ranchos soon developed around the Pueblo, The village grew so that by 1835> Los Angeles was a small city. By 1845, Los Angeles was the capitol of Alta California. In 1848, California became part of the United States under the Treaty of Guadalupe Hidalgo. Two years later, 162 In 1850, Los Angeles was incorporated, with a population of about 4,000 persons. The Gold Rush of the late 1840s brought temporary prosperity to the ranchos, which produced beef for the northern California miners. Competition from cattlemen in Texas and Missouri, higher cost of beef production resulting from the emancipation of the Indians, a sus tained drought and cattle famine, heavily mortgaged rancho property at high interest rates, and new property taxes combined to help produce a serious decline in the Los Angeles economy. During the 1860s, as one ranch after another went bankrupt, the new owners of the ranchos shifted from the previously labor-intensive production of cattle and general agricultural products for a self-sufficient residentiary population to more capital-intensive pro duction of specialized agricultural commodities for which there was a comparative advan. tage in production for export from the Los Angeles area. The era of the ranchos was over, and the agriculture era began. As immigrants came to the Los Angeles area during the 1860s and the 1870s, the demand for farming land increased, and the ranchos were subdivided into small farms. Between 1850 and 1880, the population of 1 63 Los Angeles increased sevenfold from nearly 2,000 persons in 1850 to over 11,000 in 1880; tlie population of Los Angeles County increased over eightfold from 4,000 in 1850 to 33,000 in 1880. (See Table 2.) By the 1880s, Los Angeles was a thriving, prosperous, urban center with a labor force composed of a variety of tradesmen, craftsmen, merchants, and persons in professional occupations. The pre-eminence of Los Angeles as the major urban center in Southern California was ensured in 1876 when the Southern Pacific Railroad line to Los Angeles was completed, connecting Los Angeles to the largest market on the West Coast, San Francisco, and making it the southernmost Pacific-coast terminus of the trans continental railroad system. With the urban growth of Los Angeles came the need for more and better public services, especially police and fire protection, water, streets and public transportation, sanitation and public health, and education. By the late 1880s, police and fire pro tection, sanitation, and education were being provided through local government, whereas water, street rail ways, and public utilities were provided through the private sector. 1 64 TABLE 2.— Population, Los Angeles and Los Angeles County, 1850 to 1968 (Thousands of Persons) Year Los Angeles Los Angeles County Year Los Angeles Los Angeles County 1850 2a 4a 1922 681 • • 1860 4a 1 1a 1923 731 1870 6a 15a 1924 811 • * 1880 1 1a 33a 1925 896 * • 1890 50a 1 01 a 1 926 981 • • 1900 102^ 170a 1927 1 ,063 • • 1901 122 I « • 1928 1 ,139 * + 1 902 146 1 929 1 , 189 • * 1903 169 1930 1 ,238a 2,208a 1904 189 1931 1 ,271 • • • 1905 214 1932 1 ,283 « • • 1906 240 1933 1 ,293 • • • 1 907 250 1934 1 ,299 • • • 1908 283 1935 1,311 • • • 1 909 307 1936 1 ,324 • • • 1910 31 9a 54oa 1937 1 ,351 • • • 1911 346 1938 1 ,401 • • • 1912 376 1939 1 ,449 • • • 1913 399 1940 1,504a 2,786a 1914 426 19^1 1 ,551 2,953 1915 453 1942 1 ,609 3,088 1916 472 19^3 1 ,655 3, 197 1917 482 1944 1 ,693 3,295 1918 510 19^5 1 ,741 3,391 1919 538 1946 1,806a 3,515 1920 377a 936a 19^7 1 ,863 3,695 1921 636 • • 1948 1 ,9 08 3,906 (Cont inued) 165 TABLE 2.— (continued) Year Los Angeles Los Angeles County Year Los Angeles Los Angeles County 19^9 1,9^2 4,062 1959 2,406 5,869 1950 1,970a 4, 152a 1960 2,479a 6,o43a 1951 2,010 4,278 1961 2,525 6,211 1952 2,060 4,479 1962 2,567 6,371 1953 2,105a 4,635 1963 2,620 6,528 19 5^ 2, 150 4,847 1964 2,679 6,702 1955 2, 190 5,032 1965 2,732 6,853 1956 2,244a 5,225 1966 2,783 6,976 1957 2,298 5,451 1967 2,828 7,045 1958 2,358 5,661 1968 2,897 7,103 Q. Census values, except Tor i960 population of Los Angeles County which, includes population omitted in the official census figure of 6,038,771* Source: Los Angeles, "Population Estimate by Communities," Bulletin 1959-1 (January 1, 1959). Los Angeles, City Planning Commission, Research Section, "Population Estimate and Housing Inventory" (April 1 issue, i960 and 1968). County of Los Angeles, Regional Planning Commission, "A Summary Table — Popula tion Growth, Los Angeles County, Los Angeles City, California, and the United States, 1940 to 1968" (September, 1968). County of Los Angeles, Regional Planning Commission, "Population of Los Angeles County, 1965-1985" (August, 1966). U. S. Department of Commerce, Bureau of the Census, Fifteenth Census of the United States. 1930: Population. II (Washington, IL C. : Th s7 Government Printing Office, 1931), pp. 18, 19, 131. 166 However, the great migration of people to the Los Angeles area began in the 1880s. Over the years, waves of migrants, especially from the northeastern, midwestern, and south central states, came to Los Angeles in search of a better life in this frontier paradise with a mild climate, tropical landscape, and suburban living. Negroes from the rural southern and the urban northern states came to Los Angeles in search of better opportunities and equality. Foreign immigrants, especially from Mexico and Japan, also migrated to the Los Angeles area. The sustained immigration of people since the 1880s has made Los Angeles one of the largest cities in the world. Table 2 shows the population of Los Angeles and Los Angeles County for each census year from 1850 to i960 and estimates of population cf Los Angeles for inter- censal years from 1 90 1 to 1968 and of Los Angeles County for intercensal years from 19^2 to 1968. Figure 30 shows the essentially exponential growth of the populations of Los Angeles and Los Angeles County since 185O . However, the population growth rate appears to have declined during the last 10 years. The population growth of Los Angeles tended to lead its economic growth. The migration of people to the Los Angeles area provided a large potential labor Population (Thousands of Persons) 7,200 - I 6,400 ■ 5,600 * 4,800 * 4,000 - 3,200 - 1,600 - 800 - 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 i960 1970 Source: Table 2. _i o\ Fig. 30.--Population, Los Angeles County and Los Angeles, 1850 to 1968 ' ' 3 168 force of* farmers, merchants, tradesmen, artisans, and. professionals, but very few entrepreneural capitalists interested in industrial development. Consequently, compared with, other cities of comparable size, Los Angeles had a higher fraction of its labor force employed in residentiary industries, such as those in the retail trade, transportation, and services sectors, than in export industries, such as those in the manufacturing sector. The lag in industrial development resulted in part from the lack of nearby sources of water and power and the lack of adequate harbor and port facilities. Per capita demand for water in Los Angeles increased faster than the city could supply water. In the 1890s, the Los Angeles River provided enough water for a population of 300,000 persons. To meet the growing demand for water as the population of Los Angeles increased, water was imported first, in 191^> from the Owens River Valley through a 225-mile aqueduct, then from the Colorado River through another aqueduct connecting Los Angeles with Boulder Dam, and then from the Mono Basin north of the Owens Valley. Recently, the Columbia River system has been seriously considered as a future source of water for Los Angeles. 1 69 In 1909, the communities of San Pedro and Wilmington agreed to annex themselves to the City of Los Angeles according to the 1906 "Shoestring Annexation" by the City of Los Angeles, which provided a strip of contiguous land between Los Angeles and San Pedro and Wilmington. With the aid of the United States govern ment, the City of Los Angeles, and railroad companies operating in the harbor area, the Los Angeles Harbor became one of the major ports of the world in the 1910s. Besides the direct and induced new employment resulting from the growth of import and export trade through the Los Angeles Harbor, Los Angeles benefited from two very striking developments: the development of the motion picture industry in Los Angeles and the exploitation of petroleum deposits in the Los Angeles area. The mild climate, abundance of land, variety of nearby natural environments, and a pool of skilled labor were strong inducements for motion picture producers to locate in Los Angeles where they could produce motion pictures virtually year around. Because the value of their motion picture films was high relative to their bulk and weight, the locational isolation of the Pacific coast did not seriously impede the motion picture indus try from locating in Los Angeles. 1 70 Although oil was discovered in Los Angeles in 1892, petroleum production did not expand until the early decades of the twentieth century. Although the motion picture and petroleum industries provided significant increases in direct and induced employment through their expansion of the exports from the Los Ang&les area, Los Angeles still needed a larger and more diversified indus trial sector. The expanding population provided a growing consumer market and a growing labor force. After World War I, some manufacturing and other industrial firms in the East, such as the Ford Motor Company, and Goodrich, Goodyear, and Firestone tire companies, established West-coast branch locations in Los Angeles in order to realize locational advantages in production and distri bution. This "branch location" form of industrialization characterized much of the expansion of the manufacturing and industrial sector of the Los Angeles economy through the 1930s. The modern era of industrial growth in the Los Angeles area began during World War II, especially with the increased importance of Los Angeles Harbor and the growth of the aircraft and related industries. Post war industrial development centered principally around aircraft, electronic, aerospace, and related industries. 171 Table 3 shows the total civilian employment, unemployment, and labor force in Los Angeles County from 1958 to 1968. (See Figure 31*) During this period, the labor force increased by 30 per cent, compared with an increase of about 13 per cent for the United States. Figure 32 and Table A-9 show employment in Los Angeles County by industry group from 19^9 to 1966. Throughout this 18 year period, manufacturing employment increased 28 per cent, whereas employment in transportation and public utilities, retail trade, finance, insurance and real estate, and services and miscellaneous increased 85 per cent. However, despite the slower growth of employment in manufacturing relative to the growth of employment in residentiary sectors, manufacturing employ ment in Los Angeles County between 19^-7 and 19^3 mox,a than doubled and manufacturing establishments more than tripled (Table ^). Value added in manufactures in Los Angeles in constant dollars in 1963 was nearly triple (1.75 times) the 19^-7 level (Table 5)* In Los Angeles County, value added in manufactures in constant dollars increased by a factor of 3.6 in the same 17 year period; between 19^-7 and 19^3> value added in manufactures increased by a factor of 3.8. Capital investment in manufacturing in Los Angeles County in constant dollars 172 TABLE 3.— Total Civilian Employment, Total Unemployment, and Total Civilian Labor Force, Los Angeles County, 195S to 1968 (Thousands of Employees) Year Total Civilian Employment Total Unemployment Total Civilian Labor Force 1958 2,332 1 63 2,495 1959 2 , 446 1 18 2,565 1960 2,488 145 2,634 1961 2 ,504 180 2,684 1962 2,598 151 2,748 1963 2,662 1 62 2 ,824 19 64 2,720 1 67 2,887 1965 2,787 168 2,956 1966 2,930 140 3,069 1967 3,009 142 3,152 1968 3 , 105 137 3,242 Sources Security Pacific National Bank, Economic Research Department, "Civilian Labor Force, Employment, and Unemploy ment in the Los Angeles - Long Beach Metropolitan Area1 1 (March 31» 1969)* Persons (Thousands) 3,200- 3 , 100- Total Civilian Labor Force 3,000- 2,800- Total Civilian Employment 2,600■ 2,200' 2 ,000- 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 Source: Table 3* Fig. 31.— Total Civilian Labor Force and Total Civilian Employment, Los Angeles County, 1958 to 1968 Key: A Manufacturing B Services and Miscellaneous C Retail Trade D Government E Wholesale F Transportation and Public Utilities G Finance, Insurance, and Real Estate H Contract Construction I Mining 174 Employment (Thousands of Employees) 900 - 800 700 ■ 600 500 400 300 - 200 * 100 ■ 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 Source: Table A-9 Fig. 32.— Employment by Industry Group, Los Angeles County, 1949 to 1966 175 TABLE 4.--Manufacturing Employment and Manufacturing Establishments, Los Angeles and Los Angeles County, 1939, 19^7, 1954, 1958, and 1963 Year Employment (Thousands of Employees) Establishments Los Angeles Los Angeles County Los Angeles L,os Angeles County 1939 71 125a 3,847 5,388 1947 167 353 5,445 9, *<-72 1954 269 624 7,502 13,861 1958 289 697 8, 149 16,093 1963 280 746 7,801 17,679 Average number of production workers. Source: U. S. Department of Commerce, Bureau of the Census, County and City Data Book (Washington, D. C.: U. S. Government Printing Office, 1952, 1957, 1962, 1967). 176 TABLE 5»--Value Added in Manufactures and New Capital Expenditures by Manufactures, Los Angeles and Los Angeles County, 1939, 1947, 1954, and 1958 to 1965> Current and Constant Dollars (Millions of Dollars) Value Added in Manufactures New Capital Expenditure s by Manufactures Year Los Angeles Los Angeles County Los Angeles Los Angeles County 1939 $ • • * Current Dollars $ 510 $. . #. . 19^7 930 2,022 • • 175 1954 2,037 4,939 1 16 291 1958 2,738 6,729 109 297 1959 • • • 7,360 • • 332 1960 • • • 7,803 • • • 357 1961 • • • 7,637 • • 310 1962 • • • 8,487 • • 364 1963 3, 167 8,980 1 25 389 1964 • • • 9, 152 • • 4i0 1965 • • • 9,684 • . • 392 1947 $1,146 1957-59 Dollars3- $2,490 $. . $216 1954 2, 192 5,316 1 24 313 1958 2,727 6,703 109 296 1959 « • • 7,316 • • 330 1960 • • * 7,749 • • 355 (Continued) TABLE 5.— (continued) 177 Year Value Added in Manufactures New Capital Expenditures by Manufactures Los Angeles Los Angeles County Los Angeles Los Angeles County 1957-59 Dollars (continued) 1961 $ * . • $7,614 $. • $309 1962 • • • 8,437 • • 361 1963 3,157 8,953 1 25 388 1964 • • • 9, 106 • • 408 1965 • • • 9,448 • • 383 aThe Wholesale Price Index for all commodities for the United States is used to calculate value added in manufacture and new capital expenditures by manu factures in 1957-59 dollars. Sources: U. S. Department of Commerce, Bureau of the Census, Census of Manufactures. Vol. Ill, Area Statistics(Washington, D. C.: U. S. Government Printing Office, 1950, 1957, 1961, 1966). U. S. Department of Commerce, Bureau of the Census, Annual Survey of Manufactures. 1964-1965(Washington, D. C.: U. S. Government Printing Office, 1968). U. S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United StatesT 1968 (Washington, dT cTT U. S. Government Printing Office, 1968). U. S. Department of Commerce, Bureau of the Census, County and City Data Book, 1949 (Washington, D. C.: U. S. Government Printing Office, 1952). 178 has tended to increase as the capital stock increased, as shown in Table 5« Between 1947 and 1968, total personal income in Los Angeles County in constant dollars increased by a factor of 2.6. (Table A-10 and Figure 33). However, during the same period, per capita personal income increased by a factor of only about 1.4 (Table A-11 and Figure 33 )> indicating that population increased faster 3 than total personal income. Throughout this wartime and post-war period of industrial growth, people continued to emigrate to Los Angeles induced by job opportunities, relatively high wage rates, and the amenities of Southern California. As people continued to move to the Los Angeles area, the land in the Los Angeles basin and the adjoining valleys shifted from agricultural uses to residential, commer cial, industrial, and public service uses, as the average population density of Los Angeles and Los Angeles County increased. The average population density in Los Angeles County increased by a factor of 2.6 from 682 persons per square mile in 1940 to 1,740 persons per square mile in 1968 (Table 6). The average population density of Los Angeles increased about 23 per cent from 5>051 persons per square mile in 1957 to 6,244 persons per square mile in 1968. Total Personal Income (Millions of Dollars) 000 J 24,000 1 20,000 1 16,000 ] 12,000 1 Total 8,000 ] 4,000 A 1946 19^8 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 Per Capita Personal Inc ome 3,500 3.000 2,500 2.000 1,500 1 ,000 500 0 Sources: Tables A-10 and A-11. Fig1 * 33*"-Total and Per Capita Personal Income Los Angeles County, 1947 to 1968, 1957-59 Dollars 180 TABLE 6.— Area and Population Density, Los Angeles and Los Angeles County, I850 to 1968 Area (Square Miles) Population Density (Persons per Square Mile )____ Los Year AngeSes Los Angeles County Los Angeles Angeles County .85©a 4,083.3 1 1 860a 4,083.3 3 1876a 4,083.3 4 1880a 4,083.3 8 I890a 4,083.3 25 1900a 4,083.3 42 1910a 4,083.3 123 I920a 4,083.3 229 1930a 4,083.3 541 1940a 4,083.3 682 1941 4,083.3 723 1942 4,083.3 757 1943 4,083.3 783 1944 4,083.3 807 1945 4,083.3 831 1946 4,083.3 861 1947 4,083.3 905 1948 4,083.3 957 194 9q 4,083.3 995 1950 4,083.3 1 ,017 1951 4,083.3 1 ,048 1952 4,083.3 1 ,097 1953 4,083.3 1 , 135 1954 4,083.3 1 , 188 1953 4,083.3 1 ,233 1956 4,083.3 1 ,280 1957 4 55 4,083.3 5,051 1 ,336 1958 456 4,083.3 5, 171 1 ,387 1959 457 4,083.3 5,265 1,438 196oa 457 4,083.3 5,424 1 ,480 1961 456 4,083.3 5,537 1 ,522 1962 458 4,083.3 5,605 1 ,561 (Continued) I 181 TABLE 6, — (continued) Area (Square Miles) Population Density (Persons per Square Mile) Year Los Angeles Los Angeles County Los Angeles Los Angeles County 1963 458 4,083.3 5,721 1 ,599 1964 459 4,083.3 5,837 1 ,642 1965 464 4,083.3 5,888 1,679 1966 464 4,083.3 5,998 1 ,709 1967 464 4,083.3 6,095 1 ,726 1968 464 4,083.3 6,244 1 ,740 a Census year1. Sources: Table 2. County of Los Angeles, Regional Planniig Commission, "The Gross Area, 35 Major Statistical Areas, Los Angeles County" (July 1, 1965). Los Angeles, Police Department, Statistical Digest (1957 through 1967 issues). 182 Recently the Bureau of the Census predicted that the population of the Los Angeles - Long Beach metro politan area (including Orange County) would increase by 25*6 per cent between 1965 and 1975> which is twice the rate of increase of 12.4 per cent for all metropolitan areas combined and of 11.1 per cent for the 10 largest k SMSAs. However, this rate of growth is substantially lower than the 36.3 per cent growth in population of Los Angeles County during the previous ten-year period from 1955 to 1963; the corresponding percentage for Los Angeles during the same period was 24.8 per cent.'* Although there are no available estimates, the rate of growth of population in Los Angeles can be expected to decline in the future, relative to previous periods. Per capita personal income can be expected to vary principally with national business cycles, federal government spending on aerospace and defense in the Los Angeles area, population, and long-term relocation of export industries into and out of the area. Anticyclical fiscal and monetary policy has proven to be effective in dampening business cycles. But shifts in federal govern ment spending on aerospace and defense contracts in the Los Angeles area have introduced a considerable degree of variability into the total and per capita personal income earned in the Los Angeles area and undoubtedly 183 will continue to do so in the future. If the rate of growth in population declines as expected, per capita personal income would tend to increase over time. But the direction and magnitude of the effect of changes in the export base of the Los Angeles area in response to long-term labor and capital market conditions throughout the nation are often difficult to foresee or predict; the decline of the motion picture industry in the Los Angeles area is, however, a somewhat predictable example. On balance, the rate of increase in per capita personal income in Los Angeles can be expected to decrease, if for no other reason than that, given the technology and a relatively limited amount of land, nonland resources can be expected to undergo greater diminishing returns with increases in population and the capital stock of Los Angeles. However, estimates by the California Department of Finance indicate that this effect may not be realized during the 1975 period. They estimate that personal income in Los Angeles County will increase from $24.4 billion in 19^5 to $40 billion in 1975 > an increase of 64 per cent in current dollars.^ Since the population of Los Angeles County can be expected to increase 23*6 per cent during this period, personal income in current dollars will be increasing at a rate of 2.5 times greater than that of the population; during 1 84 the 1955“1965 period, it increased somewhat over 2.4 times as fast as population. As the population density increased with the population and economic growth of Los Angeles and Los Angeles County, especially during the last three decades, external diseconomies of urban growth developed and became increasingly more serious impediments to further population and economic growth and impaired the quality 7 of the environment. External diseconomies of the urban growth of the Los Angeles area, such as increasing land values, traffic congestion, air pollution, crime rates, and government expenditures are discussed in the remaining sections of this chapter. Land Values As the population of Los Angeles and Los Angeles County increased, the demand for land, not only for agri cultural uses, but soon for urban residential, commer cial, industrial, and public uses increased. Increases in population and continued capital investment increased the productivity and value of land. Table A-12 shows the assessed valuation and estimated market value of tangible property in Los Angeles County that is subject to local taxation in current and constant dollars for 1935> 1940, 185 Q 1945 7 1950> and 1955 through 1967- Estimated market value of tangible property in constant dollars increased from $48 billion in 1960 to a peak of $61.5 billion in 1966. Estimated market value of tangible property in constant dollars increased 25 per cent between i960 and 1967. Table 7 shows the assessed valuation and estima ted market value of land in Los Angeles County that is subject to local taxation in current and constant dollars. (Also see Figure 34.) Estimated market value of land in constant dollars increased 55 per cent from $14 billion in i960 to nearly $22 billion in 1967. Because urban land is essentially fixed in quantity, at least for the short term, urban land values are determined in a market economy by the demands for land for alternative uses. Demands for alternative land uses, in turn, are functions of the productivity or utility afforded by the location of a particular plot of land for each particular use, relative to other plots of land for the same and alternative land uses. Land values can be expected to increase with population, per capita income, and capital investment. A statistical analysis was made of the association between the estimated market value of land in Los Angeles County 186 TABLE 7.— Assessed. Valuation and Estimated Market Value of Land Subject to Local Taxation, Los Angeles County, i960 to 1967, Current and Constant Dollars (Thousands of Dollars) Year Current Dollars 1957-59 Dollars3, Assessed Valuation 1 960 $3, 4-22,024 $3,303,112 1961 3,729,1^7 3,55^,95^ 1962 4,002,091 3,786,273 1963 4,061,765 3,760,894 1964 4,46i,229 4,055,663 1965 ^,746,393 4,189,226 1966 5,633,392 4,831,383 1967 6,137,230 5,127,176 Estimated Market Value i960 #1,4,561 ,804 $1^,055,795 1961 16,004,923 15,257,315 1962 16,402,012 15,517,51^ 1963 16,511,240 15,288,185 1964 18,588,454 16,898,595 1965 20,909,220 18,454,740 1966 25,723,251 22,061,107 1967 26,115,872 21,817,771 3 Consumer Price Index for housing in Los Angeles County was used to calculate values in constant dollars: U. S. Department of Labor, Bureau of Labor Statistics, “Consumer Price Index, Los Angeles - Long Beach., California" (May, 1968). Source: California, Economic Development Agency, California Statistical Abstract (1961 to 1968 is sues). 187 Estimated Market Value of Land (Millions of Dollars) 22,000 21, 000- 20,000- 19,000- 18, 000 - 17,000- 16,000- 15,000- 000- 1960 1961 1962 1963 1964 1965 1966 1967 1968 Source: Table 7- Fig. 34.--Estimated Market Value of Land Subject to Local Taxation, Los Angeles County, 1960 to 1967, 1957-59 Dollars 188 in constant dollar’s, Lc , and population of* Los Angeles County, Pc, per capita personal income in Los Angeles County in constant dollar’s, YQ, and new capital expendi tures by manufactures in Los Angeles in constant dollars, lc » Equations (88) through. (92) show the values of the constant and regression coefficients for the simple linear relationships between land values and (1) popu lation, (2) per capita income, and (3) investment by manufactures, estimated by the method of least squares. Equations (89) and (91) show the values of the constant and regression coefficients of the simple linear relation ships between the logarithm of land values and (1) the logarithm of population and (2) the logarithm of per capita income. L„ = -33,584 + 7.738 Pc (88) (1.189) log L = -3-855 + 2.119 log Pc (89) c (0.4478) L = -33,753 + 16.55 Yc (90) (2.115) log L = -3.948 + 2.345 log Y_ (91) (0.3988) Lc = 7,911 + 21.78 I (92) (15.89) Table 8 shows the coefficients of correlation and deter mination obtained from a correlation analysis of these relationships. These results support the proposition that land values vary directly and closely with popula tion and per capita personal income and directly but less closely with investment by manufactures. Land values as simple functions of population and per capita income using the sample data provide better fits than when these functions are fitted to the logarithms of the data. These results imply that there is a constant relationship between land values and population and per capita income. For many persons in Los Angeles County, such as land owners and real estate brokers, increases in land values, brought about in part by increases in population, per capita income, and investment by manu factures, serve as external economies. However, for many business firms and for individuals and families living in rented housing units, increases in land values brought about through the actions of others serve as external diseconomies and tend to redistribute land uses within the county. Traffic Congestion Los Angeles is an automobile-oriented city. Los Angeles has over 143 miles of freeway and 6,300 miles of 190 TABLE 8.— Coefficients of Correlation and Determination, Estimated Market Value of Land and Population, Real Per Capita Personal Income and Real Investment by Manufactures, Los Angeles County Independent Variable r Degrees of Freedom Dates of Annual Data pc 0.917a 0.841 6 1960-1967 log Pc 0.857b 0.734 6 1960-1967 YC 0.940a 0.884 6 1960-1967 log Yc O.900b 0.810 6 1960-1967 lc 0.488° 0.239 4 1960-1965 0^ Significant at the 0.001 level of significance. ■j^ Significant at the 0.01 level of significance. Q Significant at the 0.05 level of significance. 191 9 surface streets. Los Angeles County has more than 1 0 725 miles of freeway. About 95 per cent of travel m 1 1 Los Angeles is done "by automobile. Almost every year since 1950» the number of registered motor vehicles in Los Angeles has increased as fast or faster than the 1 2 population. Between 1957 and 1968, the number of vehicle-miles driven in Los Angeles increased by about ^0 per cent, compared with a population increase of about 26 per cent. (See Table 9 and Figure 35•) Traffic congestion is most serious in downtown Los Angeles during and at the end of daytime business hours, on the freeways, especially those leading into downtown Los Angeles, during morning and late-afternoon hours on weekdays when workers are coming to and from work, and on freeways and surface streets leading to and from such public places as Los Angeles International Airport. With the construction of each new office building in the downtown area, the demand for use of freeways and surface streets for journeys to and from work increases. Since i960, office-building construction 1 3 has average $100 million a year. A private developer who decides to construct a large office building in the downtown area need only consider the private benefits and costs of his decisions. He does not have to consider 192 TABLE 9.— Total Vehicle Miles, Street Miles, and Vehicle- miles per Street Mile, Los Angeles, 1957 to 1967 Total Vehicle Vehicle- Miles Miles per (Thousands Street Street Year of* Miles) Miles Mile 1957 11,694,956 6,049 1 ,933,370 1958 1 1 ,627,553 5,805 2,003,024 1959 12,421,500 5,840 2,126,969 1960 12,967,742 5,952 2,178,720 1961 12,961,800 6,005 2,158,501 1962 12,780,165 6,005 2,128,254 1963 13,556,144 6,005 2,257,476 1964 13,587,230 6,365 2,134,679 1965 14,553,472 6,379 2,281,466 1966 15,206,781 6,386 2,381,269 1967 15,546,065 6,393 2,431,732 1968 16,389,620 • • • ft f t • • • Sources: Los Angeles, Police Department, Traffic Services Section, "City Of Los Angeles, Traffic Statistics 9 1925 to 1968 fl • Los Angeles, Police Department, Statistical Digest (1957 to 1967 issues). 193 Vehicle-mile s per Street Mile (Thousands of Vehicle-miles) 2 ,400 2,200• 2 ,000- 1,900■ 1,800■ Source: Table 9 Fig* 35*— Vehicle-miles Per Street Mile, Los Angeles, 1957 to 19^7 19^ the social costs produced by his decision, such as added congestion, higher land values, street widening or double 1 h decking, and more-expensive parking. However, the Traffic Department of the City of Los Angeles has reported that they have reviewed traffic circulation problems with private developers before such buildings are built so as to make suggestions regarding traffic 1 5 control. A study of traffic congestion around the Los Angeles International Airport predicted that surface street traffic in the airport area in 1985 will be triple 1 f t the traffic in 19^7. Given the public 1s preference for automobile travel, as population and per capita income increase, the number of motor vehicles owned and the number of vehicle-miles driven can be expected to increase to help contribute to traffic congestion, at least in the short term before enough miles of streets and freeways can be built or expanded to accommodate the increased demand for transport services. Traffic congestion is a particularly acute and serious external diseconomy in Los Angeles and Los Angeles County. Although vehicle miles driven in Los Angeles increased by 33 per cent between 1957 and 19^7, vehicle-miles per mile of street in Los Angeles, T, an aggregate measure of traffic 195 congestion, increased only 26 per cent because of increases in number of* miles of street in Los Angeles (Table 9)« The building of new freeways not only increases the number of miles of street in Los Angeles, but also tends to increase the rate of increase in vehicle-miles driven because of the greater capacity of freeways and the faster average speed of motor vehicles on freeways. Widening of older freeways and major sur face streets tends to have similar effects. These effects are not taken into account in using miles of street in the denominator of vehicle-miles per mile of street; all miles of street are considered to be homo geneous. Therefore, vehicle-miles per mile of street may overestimate the degree of aggregate traffic con ges tion. For purposes of analysis, vehicle-miles per mile of street, T, was made a linear function of the population of Los Angeles, P, and of per capita personal income in 17 Los Angeles County in constant dollars, Yc. Linear functions were fitted to the sample data and to the logarithms of the data. The following least-squares estimates of the parameters of these linear relationships were obtained. 196 T = 203.8 + 0.7700 p (93) (0.1047) log T = O.2579 + 0.9036 log P (94) (o.1233) T = 87.72 + 0.6916 Y (95) (0.1279) log T = -0.0123 + 0.9626 log Yc (96) (0 .1889) Table 10 shows the coefficients of correlation and deter mination for the relationships given by equations (93) through (96). Both population and per capita personal income are associated with vehicle-miles per mile of street in Los Angeles in both the data and in the loga rithms of the data. Traffic congestion and population are more closely associated when the logarithms of the data are used than when the sample data are used. This might imply that because the coefficient of log P is positive but less than one, traffic congestion is increasing at a decreasing rate with increases in popu lation. However, the coefficient of log P is not sig nificantly different from 1 at any acceptable level cf significance. Therefore, since traffic congestion and per capita income are more closely associated using the sample data than the logarithms of the data, one might conclude that the functional relationships between traffic congestion and both population and per capita income are 197 TABLE 10.— Coefficients of Correlation and Determination, Vehicle-miles per Mile of Street and Population and Real Per Capita Personal Income, Los Angeles Independent Variable r Degrees of r2 Freedom Dates of Annual Data P 0.801a 0.642 9 1957-1967 log P 0.911b 0.830 9 1957-1967 Yc 0.912b 0.832 9 1957t1967 log Yc 0.838b 0.702 9 1957-1967 aSignificant at the 0.01 level of significance. Significant at the 0.001 level of significance. 198 essentially linear. If population and per capita per sonal income were not closely associated, a multiple correlation and regression analysis undoubtedly would reveal even closer relationships between vehicle-miles per mile of* street and population and per capita personal income. This analysis reflects, in an aggregate fashion, the effects of population growth and overall affluence on the problem of traffic congestion. As the population and per capita personal income of Los Angeles increase, residents can expect to experience increasingly more- severe problems of traffic congestion, not only during peak traffic periods in the downtown area but generally during almost all periods, throughout most of the city, as long as the present rates of growth in population, per capita personal income, and freeway and surface street construction prevail. The rate of increase in aggregate traffic congestion will tend to decrease with decreases in the rate of growth of population in Los Angeles, or in the rate of increase in per capita dis posable personal income or with an increase in the rate of freeway and surface street construction and modifi cation. As suggested in the first section of this chapter, although population and per capita personal income in Los 199 Angeles can be expected to increase over time, the rates of increase in population and per capita personal income can be expected to decrease, thereby tending to decrease the rate of growth of traffic congestion through a decrease in the rate of increase in vehicle-miles driven in Los Angeles. Federal, state, and local government decisions concerning expenditures for new or modified freeways and surface streets in Los Angeles are somewhat unpre dictable. Transportation technology and systems for the Los Angeles area have a great effect upon such decisions. If the past can be relied upon to shed some light on the future, street construction can be expected to lag behind increases in population. Given the exten sive stock of social capital investment in Los Angeles streets, it seems likely that the rate of increase in street miles will decrease over time, although the pro ductivity of new miles of street probably will exceed that of previous miles of streets in terms of the number of motor vehicles served per mile of street per unit time. Consequently, although the rates of increase in population, per capita personal income, and street miles all can be expected to decline, a faster decline in the growth rate of street miles relative to those of 200 population and per capita personal income can be expected to result in an increasingly higher rate of increase in traffic congestion over time. This hypothesis seems to be supported by the results of the statistical analysis of traffic congestion given earlier in this section. The traditional policy measure in Los Angeles to relieve traffic congestion has been to construct more miles of freeway throughout the Los Angeles area so as to accommodate more automobiles per unit time. Efforts to relieve traffic congestion through construction of a $2.5 billion rapid-transit system in the Los Angeles area 18 were defeated at the polls on November 5» 1968. The proposed system consisted of five rapid-transit rail lines or corridors extending out from the downtown area with bus service to and from the planned stations along 1 9 each of the five corridors. Air Pollution The use of advances in science and technology has made it possible for mankind to produce innumerable new products and services and to perform feats never before accomplished in;the entire history of mankind, such as harnessing atomic and nuclear energy and travelling round-trip to the moon. But many are 201 convinced that there has been a misuse of* scientific and technological advances resulting in pollution of natural resources and deterioration of the quality of the 20 environment. These misuses arise in the form of exter nal diseconomies of production and consumption when decision-makers either have not taken fully into account all of the consequences of their decisions or have not had to pay the full costs of their decisions. Although man's environment is polluted by natural causes, such as dust or soil stirred up by the wind, pollen and spores emitted by plants, and ozone produced by lightning, the worst polluter is man himself. Man pollutes his environ ment when he impairs the quality of the air, water, or land resources of his environment, usually by discharging 21 wastes. Wastes have been defined as any material that its producer does not want, or, more precisely, which has 22 ~ a nonpositive price. Wastes can be gaseous, liquid, 23 and solid and can pollute air, water, or land resources. Wastes are not the only pollutants of man’s environment. Noise, vibration, and unaesthetic use of producers’ capital, such as proliferations of signs along commercial strips, or of consumers' capital, such as monotonous replications of unattractive single-family housing units along parallel linear streets in a housing tract, also impair the quality of the human environment. 202 The problem of* environmental pollution becomes especially serious in metropolitan areas where population density is the greatest and where wastes produced and disposed of by one individual or institution have the highest probability of producing disutilities or dis economies for others. As the population of metropolitan areas increases, these problems are intensified many times over. Furthermore, pollution is not necessarily con fined to a particular geographic area. Streams that are polluted by the effluent from a plant may kill fish, cause stench, and ruin recreation areas miles downstream from the plant. Smoke from a plant in one city can harm plants, reduce visibility, and irritate eyes of persons living in cities many miles away. Chemicals, such as insecticides and pesticides, have caused serious dis turbances in ecological balances in some areas and traces of some chemicals have been found in the tissue of fish and birds thousands of miles from the sources of the chemicals. The disturbingly high rates of emission of carbon monoxide and carbon dioxide into the atmosphere from the burning of fossil fuels seems to be affecting the carbon cycle in nature and causing global mean temperatures to 203 rise, -thereby affecting food chains as well as glacial extent, snow in mountains, stream and river levels, and ocean levels. Although gaseous, liquid, and solid wastes are produced by commercial, industrial, and agricultural firms, households, and motor vehicles in Los Angeles, probably the most serious form of environmental pollution in Los Angeles is air pollution. An average of nearly 13>700 tons of air pollutants is being emitted each day in Los Angeles County (Table 1 1). Emissions of air pollutants per day in Los Angeles County by source of pollutant for selected years from 1956 to 1969 are shown in Table 11. Motor vehicles are by far the largest sources of air pollution, producing more than 88 per cent of all pollutants reported in 1969* Although air pollutants from aircraft constitute only somewhat more than two per cent of the total tonnage of pollutants per day on a countywide basis, they do constitute, along with noise, a considerable problem in 24 the vicinity of Los Angeles International Airport. Jet airplane traffic has increased from 80 flights per day in 1959 to about 1,000 flights per day in 19^9 and can be 25 expected to more than double by about 1979* Table 12 shows estimates of motor vehicle emis sions of air pollutants per day in Los Angeles County 5EABLE 11.— Emissions of Air Pollutants Per Day by Source of Pollutant, Los Angeles County, Selected Years from 1956 to 1969 (Tons Per Day) Organic Combus- Motor Solvent Petro- Air- tion of Yeara Vehicles Usage leum craft Fuels Chemical Other Total 1956 6,298 251 725 • • 868 89 2,069 TO 1,300 1959 5,679 436 1,371 • • 705 96 110 8,397 1961 10,569 446 1 ,002 133 218 100 220 12,688 1962 8,210 448 352 • • 697 49 524 10,280 1963 10,342 432 478 133 831 io4 215 12,535 1965 12,847 502 485 203 640 129 41 14,748 19^7 12,465 527 384 203 872 133 36 14,620 1968 12.??30 468 378 269 475 144 37 14,001 1969 11J920 518 354 310 436 90 37 13,665 £L Year data was released. Source: County of Los Angeles, Air Pollution Control District. ro o ■ p- TABLE 12.--Motor Vehicle Emission of Air Pollutants Per Day by Type of Pollutant, Los Angeles County, Selected Years from 1940 to 1968a (Tons Per Day) Year Hydro carbons Oxides of Nitrogen Carbon Monoxide Sulfur Dioxide Parti culates Total 1940 580 125 2,690 12 14 3,421 1950 1 ,160 255 5,390 47 27 6,879 1960 1,870 410 8,680 25 43 11,028 1965 2,220 490 10,375 29 52 13,166 1966 2,290 495 10,675 30 53 13,543 1967 2,335 505 10,880 31 55 13,806 1968 2,395 515 11,130 32 56 14,128 cL Emission figures reflect the amount of air pollution per day with no control program. Source: County of Los Angeles, Air Pollution Control District, ’ ’Profile of Air Pollution in Los Angeles County" (January, 1969), pp. 38-44. o ui 206 with no control program, by type of pollutant for selected years from 19^0 to 1968. Inorganic contami nants— oxides of nitrogen, carbon monoxide, and sulfur dioxide— constitute nearly 83 per cent of the total emission by weight of motor vehicles; carbon monoxide alone constitutes about 79 per cent of the total emission. (Also see Figure 36.) Organic hydrocarbons constitute approximately 17 per cent of total motor vehicle emissions per day, with aerosols of solid and liquid particulates constituting less than 0.3 per cent of the total emissions. The rate of total motor vehicle emissions increased 101 per cent from over 3»^-00 tons per day in 19^0 to nearly 6,900 tons per day in 1950. Between 1950 and i960, total emissions increased about 60 per cent to over 11,000 tons per day in i960. By 1968, the rate of total motor vehicle emissions had increased to over 1h,OOO tons per day. Although the average daily emissions from motor vehicles has been increasing over time, the rate of increase has declined considerably. Daily motor vehicle emissions in Los Angeles County can be expected to increase with increases in the population, per capita personal income, and vehicle- miles driven in Los Angeles County. Estimated parameters Total Daily Emissions (Tons per Day) 15,000 13,OOO 1 2,0 0 0 11,000 10,000 9 ,000 8,000 7 , OOO 6,000 k ,000 3 ,000 1960 Source: Table 12, Fig. 36.— Total Motor Vehicle Emission of Air Pollutants Per Day, Los Angeles County, Selected Years from 19^-0 to 1968 207 I 1970 208 of simple linear functions specifying total daily motor vehicle emissions in Los Angeles County, Ec , in tons per day as a function of (l) population of Los Angeles County, Pc, (2) per capita personal income in Los Angeles County in constant dollars, Yc, and (3) vehicle-miles driven in Los Angeles, M, are shown in equations (97) through (99)* E_ = 3,305 + 2.420 P (97) (0.0383) E_ = 9,490 + 7.055 Y (98) ° (0.4149) Ec = 1,335 + 0.9682 M (99) (0.0231) Table 13 shows coefficients of correlation and deter mination for the three relationships given by equations (97) through (99). The correlation coefficients shown in Table 13 indicate that there is a very close associa tion between motor vehicle emissions per day and popu lation, per capita personal income, and vehicle-miles driven. Some of the correlation between emissions and population and vehicle-miles driven may arise from the Los Angeles County Air Pollution Control District's use of data on population and the number of registered motor vehicles in estimating motor vehicle emissions. The results of this analysis suggest that, with no control programs, as long as the population and per capita personal income of Los Angeles County continue to 209 TABLE 13.— Coefficients of Correlation and Determination, Motor Vehicle Emissions of Air Pollutants per Day and Population, Real Per Capita Per sonal Income, and Vehicle-miles Driven in Los Angeles, Los Angeles County Independent Variable r r2 Degrees of Freedom Dates of Annual Data pc 0.999a 0.998 5 19^0, 1950, 1960, 1965 to 1968 Yc 0.990a 0.980 h 1950, 1960, 1965 to 1968 M 0.998a 0.996 5 19^0, 1950, 1960, 1965 to 1968 Significant at the 0.001 level of significance. 210 increase, automobile emissions will continue to increase. Furthermore, as per capita personal income increases, tlie average number of motor vehicles per family seems to increase, further increasing motor vehicle emissions through the increase in the number of vehicle-miles driven per capita. Fortunately, the Los Angeles County Air Pollution Control District, along with state and federal legisla tive and administrative bodies, has been successful in curbing air pollution in Los Angeles County. Xn 1968, nearly 2,300 tons of air contaminants were prevented from polluting the air of Los Angeles County through the use of state and federal government-approved motor vehicle emission-control systems.^ Hope of an ultimate solution to environmental pollution seems to lie in continued research in the area of environmental pollution, probably using a systems analysis approach, subsequent development of better methods of managing wastes, stringent but reasonable legislation against environmental pollution, and effec tive administration of environmental control programs and waste management systems. Of course, the consensus of public opinion must be strongly enough in favor of improving the quality of the environment to make possible any significant progress in pollution abatement. 2 1 1 One of the most encouraging reports to date on research into environmental pollution is that the Argonne National Laboratory in Chicago and an association of 30 major universities, called the Argonne Users Association, are planning the largest pollution control study ever 27 conducted. The program would study problems of managing all types of wastes from all sources in a selected major metropolitan area, probably Chicago, and would aim to design a comprehensive waste management system for the area. Special attention would be directed at studying the compound effects of different types of pollution on human life. Crime Population and income growth of the United States have been accompanied by a disturbing increase in crime pQ rates per 100,000 population. Table and Figure 37 show that, while population increased 11 per cent between 19^0 and 1968, percentage increases in crime rates for the more serious crimes— burglary, robbery, larceny, auto theft, homicide, forcible rape, and aggravated assault— ranged from 36 per cent for homicide to 125 per 29 cent for larceny. Crime rates for crimes of theft (crimes against property)— burglary, robbery, larceny, and auto theft--increased by more than those for crimes 212 TABLE 14.— Number of Crimes and Crime Rates and Percen tage Changes by Type of Crime, United States, 1968 Crime Estimated 1968 Crime, Percentage Change over I960 Number Ratea Number Rate Burglary 1 ,828,900 915 104$ 83$ Robbery 261,730 131 1 44 1 19 Larceny 1,271,1O0 636 151 125 Auto Theft 777,800 389 139 1 14 Homicide 13,650 7 52 36 Forcible Rape 31,060 16 84 65 Aggravated Assault 282.400 1 41 86 67 j Total 4,466,600 2,235 122$ 99$ aCrimes per 100,000 population. Source: U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States. 1968 (Washington, EL C. : XL S*I Government Printing Office), p. 5» Percentage Change over 1960 213 Larceny Robbery » Auto Theft 120 IOO 90 Burglary 80 Aggravated Assault ► Forcible Rape 70 60 50 Homicide 30 20 Population 10 -10 i960 1961 1962 1963 1964 1965 1966 1967 1968 Source: U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States, 1968 (Washington, dT C. : U. S. Government Printing Office). Fig. 37.— Percentage Change in Crimes per 100,000 Population and Population Relative to i960 by Type of Crime, United States, 1960 to 1968 214 against persons— homicide, forcible rape, and aggravated assault. Burglary, robbery, larceny-theft, and auto theft are considered as crimes against property in the sense that the principal motivation for committing these crimes is assumed to be the securing of property by theft; homicide, forcible rape, and aggravated assault are treated as crimes against persons in the sense that the focus of these crimes is direct attacks against persons. The estimated gross national loss from theft in current dollars more than tripled from $261,500,000 in 1957 to $818,700,000 in 1968 (Table A-14). Table A-14 and Figure 38 show the gross and net values of stolen property in the United States from 1957 to 1968; Table A-14 also shows the estimated value of recovered pro- 30 perty. Table A-15 shows the average loss per offense and the estimated total national loss from each of the four crimes of theft in cities with populations of 25 9OOO or more from 1957 to 1968. Crime rates for cities of 250,000 persons or more are higher than those for the United States as a whole, those for the suburban population, and those for the rural population (Table 15)* Table 16 shows that crime rates for all major crimes increase with population. Value of Stolen Property (Mill ions of Dollars) Stolen 800 700 600 500 Net Stolen 400 300 200 100 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Source: Table A-14. Pig. 38.--Gross and Net Values of Stolen Property, United States, 1957 to 1968, Current Dollars £ IZ 216 TABLE 15.— Crime Rates by Type of1 Crime, United States, Cities over 250,000, Suburban, and Rural, 1968 (Crimes per 100,000 Population) Crime Rate Crime United States Citie s Over 250,000 Suburban Rural Burglary 9t 5 1,666 761 387 Robbery 131 433 45 12 Larceny, $50 and over 636 1 ,081 565 217 Auto The ft 389 934 237 67 Homicide 7 1 4 3 6 Forcible Rape 16 32 12 9 Aggravated Assault 14i 295 85 81 Total 2,235 4,453 1 ,799 780 Source: U. S. Department of* Justice, Federal Bureau of Investigation, Uniform Crime Reports for the Unites Sates, 1968 (Washingt on, dT C . : XL sT Government Printing-Office), p. 5. TABLE 16.--Crime Rates by Type of Crime, Cities by Population Size, 1968 (Crimes per 100,000 Population) Population of Cities Burglary Larceny- 150 and Robbery Over Auto Theft Homi- cidea For cible Rape Aggra vated Assault Total Over 1,000,000 1,769 550 1 ,220 919 14 34 339 4,844 500,000 to 1,000,000 1,590 398 945 1,060 16 32 283 4,324 250,000 to 500,000 1,576 264 1 ,002 800 12 28 229 3,910 100,000 to 250,000 1 ,233 130 827 1,780 8 17 171 2,947 50,000 to 100,000 935 88 769 422 4 12 116 2,346 25,000 to 50,000 751 51 686 291 4 9 88 1,878 10,000 to 25,000 656 31 506 200 3 7 86 1,488 Under 10,000 524 18 425 134 2 6 85 1 ,194 c l Includes murder and nonnegligent manslaughter. Source: U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States. 1968 (Washington, C.: Ul Si Government Printing Office), Table9• 218 Table 17 shows the 1$>68 crime rates of1 the 30 standard metropolitan statistical areas with populations of 1,000,000 or more persons by types of crimes. The burglary rate for the Dos Angeles - Long Beach SMSA (Los Angeles County) is second only to that of the San Francisco - Oakland SMSA. In robbery, Los Angeles County ranks eighth after New York, Baltimore, Washington, D. C., Detroit, San Francisco - Oakland, Miami, and Chicago SMSAs. Los Angeles County ranks second only to the New York SMSA in its larceny rate and third only to San Francisco - Oakland and Boston - Lowell - Lawrence SMSAs in its auto theft rate. The homicide rate in Los Angeles County ranks thirteenth among the largest SMSAs. But Los Angeles County leads all other SMSAs in the country in its rate of forcible rapes followed not too closely by Newark, Kansas City, and Denver SMSAs. Los Angeles County ranks third after the Baltimore and Miami SMSAs 32 in aggravated assaults per 100,000 population. Table 18 contrasts crime rates for all major crimes combined for Los Angeles, Los Angeles - Long Beach SMSAj California, and the United States from 1958 to 1968. Ratios of the crime rates of Los Angeles to those of the Los Angeles - Long Beach SMSA, California, and the United States tend to decline over time TABLE 17.— Crime Rates by Type of Crime, Standard Metropolitan Statistical Areas with Population of 1,000,000 or More, 1968 (Crimes per 100,000 Population) Standard Metropolitan Larceny - For- Aggra- Statistical $50 or Auto Homi- cible vated Areaa Burglary Robbery More Theft cide k Rape Assault Total New York, N. Y. 1,708 485 1,485 77 2 9 17 258 4,734 Los Angeles - Long Beach, Cal, 1,932 273 1,280 847 9 45 320 4,705 Chicago, 111. 760 304 538 595 11 21 228 2,458 Philadelphia, Pa, 653 115 337 329 7 14 114 1,569 Detroit, Mich, 1,403 378 918 674 11 34 193 3,612 Boston - Lowell - Lawrence, Mass. 832 97 572 936 4 10 83 2,534 San Francisco - Oakland, Cal. 2 , 119 377 973 966 8 28 197 4 ,666 Washington, D, C, - Md. - Va, 1,358 379 736 726 10 21 188 3,416 St, Louis, Mo. - 111. 1,238 220 536 690 12 27 177 2,900 Pittsburg, Pa. 730 150 533 589 3 13 88 2,106 Cleveland, 0. 611 186 506 838 10 11 90 2,251 Baltimore, Md. 1,676 455 974 787 14 38 506 4,449 Newark, N. J, 1,455 266 868 726 8 20 177 3,520 Houston, Tex. 1,322 232 687 542 15 21 202 3,022 Minneapolis - St. Paul, Minn. 1,254 167 868 640 4 20 82 3,034 (Continued) TABLE 1 7 (continued) Standard Metropolitan Statistical Areaa Burglary Robbery Larceny - $50 or More Auto Theft Homi cide For cible Rape Aggra vated Assault Total Dallas, Tex. Cincinnati, 0. - 1 ,008 86 542 429 16 16 216 2,312 Ky. - Ind. 680 75 448 258 5 14 90 1,570 Milwauke e, Wi s. Patterson - Clifton - 525 68 675 377 4 9 62 1,719 Passaic, N. J. 702 56 617 392 4 5 52 1 ,828 Buffalo, N. Y. 733 107 574 448 4 13 84 1,964 Atlanta, Ga. 1,015 79 786 422 17 16 97 2,431 Seattle - Everett, Wash. 1,376 197 1,144 470 5 25 112 3,328 Kansas City, Mo.,- Kan. Anaheim - Santa Ana - 1,249 210 728 558 10 37 119 2,990 Garden Grove, Cal. 1,420 66 1,072 290 2 17 84 2,951 San Diego, Cal. 728 66 958 352 4 15 78 2,199 Miami, Fla. 1,501 360 1,219 519 12 20 386 4,018 Denver, Colo. 1 ,200 145 948 634 6 37 162 3,133 (Continued) ro ro o TABLE 17•--(c ontinued) Standard Metropolitan Statistical Areaa Burglary Robbery Larceny - $30 or More Auto Theft Homi cide13 For cible Rape Aggra vated Assault Total San Bernardino - Riverside - Ontario, Cal. 1 ,526 76 937 353 h 28 -\kk 3,069 Indianapolis, Ind. 1,136 199 517 666 8 28 99 2,653 New Orleans, La. 1,173 2 38 980 699 11 34 264 3,399 c L Standard Metropolitan Statistical Areas are listed in the decreasing order of their population. *1_ Includes murder and nonnegligent manslaughter. Source: U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States. 1968 (Washington, C.: U\ T. Government Printing Office), Table5• 222 TABLE 18.--Crime Rates for All Major Crimes Combined, Los Angeles, Los Angeles - Long Beach. SMSA, California, and United States, 1958 to 1968 (Crimes per 100,000 Population) Year Los Angeles Los Angeles - Long Beach SMSA California United States 1958 33,499 2,508 1 ,797 a 1959 30,736 2,237 1,636 a i960 35,349 2,679 1 ,976 1 ,123 1961 33,853 2,657 1 ,928 1 , 138 1 962 35,329 2,682 2,01 1 1 ,191 1963 37,289 2,935 2, 1 64 1 ,292 1964 39,623 3,263 2,424 1 ,44o 1965 44,421 3,567 2,644 1 ,512 1966 47,303 3,780 2,826 1 ,667 1967 50,990 4,117 3,208 1 ,922 1968 56,321 4,705 3,764 2,235 aDifferent reporting practices make rates for 1958 and 1959 incomparable with later data. Source: U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States (Washington, C. : U.S.Government Printing Office, 1958 to i960 issues). 223 indicating that the crime rates for Los Angeles are increasing at a slower rate than those of the SMSA, the 3 3 state, and the nation. Table A-16 shows crime rates by types of crime for the United States from i960 to 19^8 and for California and the Los Angeles - Long Beach SMSA from 1958 to 1968. As shown in footnote 32, Los Angeles has one of the highest crime rates in the United States. Tables 19 and 20 show crimes and crime rates for Los Angeles by types of crime from 1957 to 1968. (Also see Figure 39•) The overall crime rate in Los Angeles might be expected to increase with population and per capita income. As population increases, population density increases resulting in a more crowded, congested, and complex environment. As people and things become increasingly crowded together, stresses and tensions can be expected to develop among the population. Because the private marginal disutility of an individual moving (crowding) into a given space is less than the social marginal disutility resulting from his move, the number of crimes against persons, resulting, perhaps, from the tensions and stresses of urban life, might be expected to increase faster than population. As per capita income increases, opportunities for crimes against property probably increase faster than population. TABLE 19.--Crimes, Los Angeles, 1957 to 1968 (1) (2) (3) (4) ( 5) (6) ( 7) For (8) Aggra (9) (10) Larceny- Auto Total Homi cible vated Total Total Year Burglary Robbery Theft Theft (i)-(4) cide Rape Assault (6)-(8) fe)A(9) 1957 26,887 4,269 50,173 13,203 94,532 119 1,271 5,786 7,176 101,708 1958 31,123 4,622 55,139 51,204 13,215 104,099 136 1,028 6,354 7,518 111,617 1959 29,305 36,256 4,371 12,469 97,349 134 1,057 6,687 7,878 105,227 1960 6,068 57,738 15,085 115,147 154 1,085 7,565 8,804 123,951 120,671 1961 35,409 5,729 55,383 14,862 111,383 159 1,156 976 7,973 9,288 1962 37,665 6,111 57,053 16,092 116,921 160 8,177 8,655 9,313 126,234 1963 41,011 6,325 59,455 16,855 123,646 200 952 9,807 133,453 1964 43,362 6,740 67,355 19,532 136,989 177 987 8,900 10,064 147,053 1965 50,771 8,016 72,308 22,136 153,231 249 1,268 9,211 9,887 10,728 163,959 1966 55,959 7,941 76,073 23,152 163,125 226 1,345 11,458 174,583 1967 60,052 9,966 80,386 25,358 175,762 281 1 ,421 11,253 12,955 188,717 1968 63,487 11,304 87,012 31,809 193,612 349 1,735 13,748 15,832 209,444 Source: Los Angeles, Police Department, Statistical Digest (1957 to 1968). fu - P - TABLE 20.--Crime Rates by Type of Crime, Los Angeles, 1957 to 1968 (Crimes per 100,000 Population) (1) (2) (3) W (5) (6) (7) For (8) Aggra (9) (10) Larceny- Auto Total Homi cible vated Total Total Year Burglary Robbery Theft Theft (1)-(4) cide Rape Assault (6) — (8) (5) & (9) 1957 11,700 1,858 21,833 5,745 41,137 52 553 2,518 3,123 44,259 1958 13,199 1,960 23,384 5,604 44,147 4o,46l 58 436 2,695 3,188 47,335 1959 12,180 1,817 2,448 21,282 5,182 56 439 2,779 3,274 43,735 1960 14,625 23,291 21,934 6,085 46,449 62 438 3,052 3,551 50,000 1961 14,023 14,673 2,269 5,886 44,112 63 458 3,158 3,678 . 47,790 1962 2,381 22,226 6,269 45,548 62 38O 3,185 3,628 49,176 1963 15,653 2,414 22,693 6,433 47,193 76 363 3,303 3,743 50,936 1964 16,186 2,516 2,934 25,142 7,291 51,134 66 368 3,322 3,767 54,891 1965 18,584 26,467 8,102 56,087 91 464 3,372 3,927 60,014 1966 20,107 2,853 27,335 28,425 8,319 58,615 81 483 3,553 4,117 62,732 1967 21,235 3,524 8,967 62,151 99 502 3,979 4,581 5,465 66,732 1968 21,914 3,902 30,035 10,980 66,832 120 599 4,746 72,297 Sources: Tables 2 and 19. fo j\ j Ur Crime Rate (Crimes per 100,000 Persons) 35,000 30,000 25,000 20,000- 15,000 10,000- 5 ,000- Larceny-Theft Burglary Auto Theft Aggravated Assault Robbery Homicide and Forcible Rape i 1 1 1 i -------------- 1 -------------- 1 ----------------1 — -- - - - - - r 1 1 ------------ 1 — 1957 1958 1959 1960 1961 1962 1963 19^4 1965 1966 1967 1968 1969 Source: Table 20. Fig. 39.--Crime Rates by Type of Crime, Los Angeles, 1957 to 1968 226 227 Equation (100) shows the estimated values of the parameters for the linear multiple regression relation ship between the logarithm of the overall crime rate per 10,000 population in Los Angeles, log C, and the loga rithm of the population of Los Angeles, log P, and the logarithm of time, log t (t = 1 for 1957)> based on annual data for the years 1957 to 1968 (n = 12). log C = -11.70 + 3.976 log P - 0.19^8 log t (100) ( 0 . 5 3 6 8 ) ( 0 .0 5 2 9 ) The coefficients of log P is significant at the 0.001 level of significance. Furthermore, the coefficient of log P is significantly greater than 1 at the 0.01 level of significance, indicating that, after taking the time trend into consideration, log C increases much faster than log P. The negative coefficient of log t is significant at the 0.02 level of significance. This result implies that, given the population, the overall crime rate in Los Angeles is decreasing over time. Standard partial regression coefficients of log P and log t indicated that log P was relatively more important than log t in accounting for the variation in log C. Collectively, log P and log t account for nearly 98 per cent of the variation in log C, and the F statistic is significant at the 0.01 level of significance. However, values 228 of the coefficients of log P and log t cannot be taken very seriously because of strong correlation between log P and log t (r- \ 2 ~ °*9575). In order to endure that the negative value of the partial regression coefficient of log t in equation (100) was not a chance result, the parameters of a function similar to equation (100) were estimated using data for the United States. Equation (101) shows the estimated values of the parameters of the logarithm of the overall crime rate in the United States, log C-^g, as a linear function of the logarithm of the population of the United States, log Pfjs* an<^ the logarithm of time, log t (t = 1 for i960), based on annual data for the years 1960 to 1968 (n = 9) • log CTTC; = - 23.54 + 11.79 log PTT„ US (2.629) US -0.2818 log t (o.1319) (101) The coefficient of log P-jjg is significant at the 0.01 level of significance, and the coefficient of log t is significant at the 0.1 level of significance. The coefficient of multiple determination is 0.947, and the F statistic is significant at the 0.01 level of signi ficance. The significance of the negative coefficient of log t in equation (lOl) indicates that, just as in Los 229 Angeles, the overall national crime rate tends to decrease over time once the effect of population is taken into account. An analysis similar to that of equation (lOO) was made of the overall crime rate in Los Angeles using the data in linear rather than logarithmic form. However, the regression coefficients were not significant at any acceptable level of significance. Because of multicollinearity, the overall crime I rate in Los Angeles was specified simply as a function of I i the population of Los Angeles. Estimated values of the parameters of this function are shown in equations (102) and (103) for fits to annual data for the years 1957 to 1968 (n - 12) in the linear and in logarithmic form respectively. C = -63.26 + 0.0452 P (102) (0.0047) log C = -5.408 + 2.091 log P (0.2128) (103) The regression coefficients in both equations are signi ficant at the 0.001 level of significance. Furthermore, the coefficient of log P in equation (103) is signifi cantly different from 1 at the 0.001 level of signifi cance. The coefficients of correlation and determination between C and P are 0.940 and 0.884, respectively; those 230 for log C and log P are slightly higher at 0.943 and 0.889 respectively. Equation (103) shows that C can be expected to increase faster than P because the coeffi cient of log P is greater than 1. The overall crime rate per 10,000 population in Los Angeles, C, was also specified as a multiple regres sion function of per capita personal income in Los I j Angeles County in 1957-59 dollars, Yc, and time, t. | Equations (104) and ( 1 05 ) show the estimated parameters j i of this function fitted to the sample data and to the | ! logarithms of the data, respectively. j C = -14.93 + 0.02 Y_ + 1 . 14 t (104) ' ■ (0.01) ° ( 0. 60) log C = -4.309 + 1.722 log Y + 0.0461 log t (105) (0.4829) (0.0386) In equation (104), the coefficient of Y_ is significant at the 0.1 level of significance whereas that of log Yc in equation (105) is significant at the 0.01 level. The coefficient of t in equation (104) is significant at the 0.1 level of significance. The coefficient of log t was not significant at any acceptable level of significance. In equation (104), Yc and t have the same relative importance in explaining variations in C, whereas in equation (105)» log Yc is relatively much more important than log t in explaining variations in log C. The 231 coefficient of multiple determination of 0.92 for equa tion (104) is somewhat larger' than that of 0.875 for equation (105). The F statistic for both equations are significant at the 0.01 level of significance. However, because multicollinearity is a serious problem in both equations, the estimated values of the regression coefficients cannot be taken very seriously. Because of this multicollinearity, the overall crime rate in Los Angeles was specified as a simple function of real per capita personal income. Equations (106) and (107) show the estimated values of the constant and regression coefficients using annual data for the years 1957 to 1967 (n = 11) in the numbers and in the logarithms, respectively. C = -65.85 + 0.0391 Yc (106) (0.0044) log C = -5.908 + 2.190 log (107) (0.2720) The regression coefficients in both equations are both significant at the 0.001 level of significance. The coefficient of log Yc in equation (107) is significantly greater than 1 implying that the overall crime rate is increasing faster than per capita income. The coefficients of correlation and determination between C and Yc are 0.936 and O.876, respectively, and 232 those between log C and log Yc are 0.925 and 0.855* respectively. These analyses Indicate that population and per capita personal income are significant factors in explain ing variations in the overall crime rate in Los Angeles, even when the effects of time are taken into account. The overall crime rate seems to be increasing faster than the population and per capita income. The major com ponents of the overall crime rate in Los Angeles, the rate of crimes against property and the rate of crimes against persons, are analyzed in the remainder of this section. Crimes against property can be expected to increase with population, the volume of retail trade, and retail trade employment. Equation (108) shows the estimated parameters of the specified linear relationship between the logarithm of the rate of crimes against property per 10,000 population in Los Angeles, C-j, and the logarithm of the population of Los Angeles, P, based on data for the years 1957 to 1968 (n =s 12). log C-, = -5.^82 + 2.103 log P (108) (0.2173) Equation (109) and (110) show the values of the estimated parameters of the linear relationship between the rate of crimes against property per 10,000 population in Los 233 Angeles, , and (l) self-assessed transactions of retail firms in Los Angeles in 1957-59 dollars, S, (Table A-17) and (2) retail trade employment in Los Angeles County, Nr, (Table 4). CL = -3.869 + 0.0185 S (109) (0.0044) C-, = -16.29 + 0.184-5 Nr (110) ( 0. 0221) Table 21 shows the coefficients of correlation and deter mination for the variables shown in Equations (108), (109), and (110). Equation ( 1 1 1 ) shows estimated values of the parameters of the specified linear relationships between the logarithm of the rate of crimes against persons per 10,000 population in Los Angeles, , and the logarithm of the population of Los Angeles, P, based on annual data for the years 1957 to 1968 (n = 12). log C2 = -6.150 + 1.971 log P (Hi) (0.2321 ) The coefficients of correlation and determination between 2 log C2 and log P are r = O.926 and r = 0.857; ** is sig nificant at the 0.001 level (D. F. = 10). The results of this analysis indicates that there is an association between crime rates in Los Angeles and the population of Los Angeles, between the overall crime rate in Los Angeles and per capita personal income in Los TABLE 21.— Coefficients of Correlation and Determination, Crimes Against Property Per Capita and Population, Real Retail Trade Transactions, and Employment in Retail Trade in Los Angeles County, Los Angeles Dependent Variable Independent Variable r r2 Degrees of Freedom Dates of Annual Data log Ci log P 0.9^1^ 0.885 10 1957 to 1968 Cl S 0.830b 0.690 6 1958, 196O to 1§66 C1 Nr 0.935a 0.87^ 8 1957 to 1966 g Significant at the 0.001 level of significance. ^Significant at the 0.02 level of significance. to • P * 235 Angeles County, and between the rate of crimes against property in Los Angeles and both retail trade transactions in Los Angeles and retail trade employment in Los Angeles County. This analysis supports the hypothesis that popu lation and economic growth of Los Angeles contribute to the increase in the crime rates in the city. No attempt is made here to fully explain the causes of crime in Los j Angeles but rather to show how and to what degree crime j j rates in Los Angeles are related to the population and j i 35 economic growth of the city. ! t | Government Expenditures ! Population and economic growth of the United States during the last few decades has been accompanied by relatively rapid increases in governmental expendi tures. Between 1950 and 19^0 while the gross national product increased about 77 per cent, expenditures at all levels of government increased approximately 125 per cent, over 1.6 times faster than the gross national o / C product. The fastest average rate of growth in govern ment expenditures has occurred in local government expenditures. Between 1950 and 1966, local government expenditures in 1957-59 dollars increased about 164 per cent, compared with growth rates of 133 per cent for state government expenditures and 126 per cent for the 236 federal government expenditures (Table A-18 and A-19 and Figure 4o). During this same period, expenditures by the State of California in 1957-59 dollars increased nearly 210 per cent (Table A-20). With per capita income in the United States increasing and government expenditures increasing faster than gross national product, it is not surprising to find government expenditures increasing faster than population. Figure 41 and Tables A-19» A-20, 22, and 23 show the growth in per capita expenditures of the federal govern ment, State of California, County of Los Angeles, and City of Los Angeles in 1957-59 dollars. Estimated parameters of simple linear relation ships between per capita expenditures of the County of Los Angeles in 1957_59 dollars, G , and (l) the popu- C * lation of Los Angeles County, Pc, and (2) per capita personal income in Los Angeles County in 1957-59 dollars, Yc, are shown in equations (112) and ( 113) • G = 153.1 + 0.0384 P- (112) C (0.0022) G = 184.3 + 0.0919 Y (113) C / \ C \ / (0 .0075) Table 24 shows the coefficients of correlation and deter mination for the relationships given by equations (112) and (113). 237 Government Expenditure (Millions of Dollars) $130, 000. 120,000. Federal 110,000- 100,000. 90, 000. 80,000- 60, 000- Local 40,000- State 30, 000- 20,000 10, 000- 1930 1952 1954 1956 1958 1960 1962 1964 1966 1968 Source: Table A-14. Fig. 40.--Total Federal, State, and Local Government Expenditures, 1950 to 1966, 1957-59 Dollars Per Capita Government Expenditures 238 Federal 400 - 350 ■ 300 State of California 200 ‘ County of Los Angeles 100 ■ City of Los Angeles 50 ■ 1950 1952 195^ 1956 1958 1960 1962 1964 1966 1968 19/0 Sources: Tables A-l4, A-1 6, 16, and 27* Fig. 41.--Per Capita Government Expenditures, United States, California, Los Angeles County, and Los Angeles, 1950 to 1968, 1957-59 Dollars 239 TABLE 22.— Total and Per Capita Expenditures, County of Los Angeles, Fiscal Years 1959--60 to 1966-67, Current and Constant Dollars Fiscal Year Total Ending (Thousands Per June 30 of Dollars) Capita3 Current Dollars 1960 $488,470 $ 82 1961 522,524 85 1962 563,657 90 1963 645,703 100 1964 724,047 109 1965 824,050 122 1966 870,752 126 1967 955,244 136 1 9 57- 59 Dollars13 1960 $473,553 $ 79 1961 498,830 81 1962 531,752 '85 1963 601,213 93 1964 663,047 100 1965 740,054 1 10 1966 766,507 111 1967 822,423 117 Population figure used to calculate each per capita expenditure is the average of the populations for’ the beginning and ending years of each fiscal year. ^Price index used for a given fiscal year is the average of the Bureau of Labor Statistics' Consumer■ Price Index for Los . Angeles - Long Beach, California, for the beginning and ending years of the fiscal year Sources: California, Economic Development Agency, California Statistical Abstract (1961 through 1968 issues TJ. S. Department of Labor, Bureau of Labor Statistics, "Consumer Price Index, LoS Angeles - Long Beach, California" (May, 1968). 240 TABLE 23?— Total and Per Capita Expenditures, City of* Los Angeles, Fiscal Years 1947-48 to 1966-67, Current and Constant Dollars Fiscal Year Ending June 30 Total3 Per Capita, 1957-59 Dollars0 Current Dollars 1957-59 Dollars 1948 $235,755,948 $297,108,945 $157 1949 295,916,437 360,873,704 187 1950 294,315,292 358,265,724 183 1951 277,657,095 323,232,939 1 62 1952 295,231,801 325,503,639 1 60 1953 308,134,347 333,478,730 164 1954 357,917,729 385,895,126 181 1955 37^,217,032 403,686,119 186 1956 391,476,478 419,139,698 189 1957 426,152,469 445,533,162 196 1958 474,395,400 479,671,790 206 * * * * 1961 233,9^5,729 223,337,211 89 1962 25^,835,9^7 240,411,271 94 1963 263,710,208 245,540,023 95 1964 281,235,878 257,542,013 97 1965 302,326,700 271,510,283 100 19 66 319,144,528 280,937,084 102 1967 344,941,555 296,979,384 106 aBecause of* changes in reporting procedures and accounting definitions, total expenditures for fiscal years 1957-58 and earlier cannot be compared with those for fiscal years 1958-59 and later. bprice index used for a given fiscal year is the average of the Bureau of Labor Statistics' Consumer Price i Index for Los Angeles - Long Beach for the beginning and ending years of the fiscal year. cPopulation estimate used to calculate the per | capita expenditure for a given fiscal year is the average | of the annual estimates given in Table 2 for the beginning and ending years of the fiscal year. I Sources: California Office of the State Con troller, "Annual Report of Financial | Transactions Concerning Cities in California" (1946-47 to 1966-67 issues). U. S. Department of Labor, Bureau of j Labor Statistics, "Consumer Price Index, | Los Angeles - Long Beach, California" I (May, 1968). j TABLE 2k.— Coefficients of Correlation and Determination, Real Per Capita Expenditures of the County of Los Angeles and the Population and Real Per Capita Personal Income, Los Angeles County Independent p Degrees of Dates of Variable r r Freedom Fiscal Dataa Pc 0.987b 0.974 6 19^0 to 1967 Yc 0.974b 0.949 6 1960 to 1967 aFiscal year ending June 30 of* dates shown. Significant at the 0.001 level of significance. 242 Comparable estimates of parameters of simple linear relationships between per capita expenditures of the City of Los Angeles in 1957-59 dollars, G, and (l) the population of Los Angeles, P, and (2) per capita personal income in 1957-59 dollars in Los Angeles County, Y , are shown in equations (114) and (115)- G- = 33.74 + 0.0495 P (11*0 (0.0033) G = 17.39 + 0.0372 Y (115) (0.0024) ° Table 25 shows the coefficients of correlation anddeter- mination for the variables shown inequations (114) and (115). The coefficients of correlation shown in Tables 24 and 25 indicate that both county and city government expenditures are associated with population and per capita personal income. As the population and per capita per sonal income of Los Angeles increase, more is spent on each person in the county and city by the County of Los Angeles and by the City of Los Angeles, respectively. But the relationship between per capita expendi tures of local governments and population should be interpreted carefully. Per capita expenditures by local governments might be thought of as a measure of the average benefit of government services per person. 2k3 TABLE 25.— Coefficients of Correlation and Determination, Real Per Capita Expenditures of tlie City of Los Angeles and Population and Real Per Capita Personal Income, Los Angeles Independent Degrees of Dates of Variable r r 2 Freedom Fiscal Dataa P 0.984b 0.968 5 1961 to 1967 Y c 0.986b 0.972 5 1961 to 1967 aFiscal year ending June 30 of dates shown. ^Significant at the 0.001 level of significance. 244 However, such, an interpretation should be used cautiously because of the income-redistribution effects of govern ment expenditures and the related problem of interpersonal comparisons of utility that are associated with aggregate averages such as this. On the other hand, per capita expenditures of local government might be used as a measure of the average cost of local government per per son. However, one must be careful here again because of the income-distribution aspects of taxation and the underlying problem of interpersonal comparison of utility in questions of tax incidence. Increasing per capita expenditures of local government with increases in population might be thought of as an increasing average cost if population were used as a surrogate for aggregate output of local govern- 37 ment, Basicdly, it is in this sense that these vari ables have been related so as to indicate the effect of increasing population on the average cost of local govern ment per person potentially served. One might argue that, in this sense and from the point of view of local govern ments, equations (112) and (114) show more the "internal1 *, effects of increased scale of operation. However, from the viewpoint of individuals in the local population, increases in the population are associated with increased 2k5 per capita expenditure of local governments, thereby resulting, on the average, in external effects to indi viduals in the population. 246 Footnotes to Chapter III 1. Using data on population and per capita income in 1957-59 dollars in Los Angeles between 1947 and 1968 (n = 22), a simple correlation coefficient of 0.961 was obtained, which, is significant at the 0.001 level of significance. 2. The following sources were drawn upon heavily in preparing the historical sketch of the growth of Los Angeles and Los Angeles County: William Wilcox Robinson, Los Angeles from the Days of the Pueblo (San Francisco: California Historical Society, 1959); Robeft M. Fogelson, The Fragmented Metropolis, Los Angeles. 1850-1930(Cambridge, Mass.? Harvard University Press, 1967)> Robert A. Futterman, The Future of Our Cities (Garden City, N. Y.: Doubleday & Company, Inc., 1961); Jane Jacobs, The Economy of Cities (New York: Random House, Inc., 1969) 9 pp. 151-54. 3. U. S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States (Washingt on, IU C . : U. s"! Government Printing Office, 1964 and 1968 issues). 4. "Rapid Growth of Population Expected Here," Los Angeles Times, March 2, 1969» sec. F, p. 2. 5. From Table 2. 6. Ernest A. Schonberger, "The California Story: People, People, People," Los Angeles Times. August 6, 1967 sec. F, p. 1. 7. Ray Herbert, "Rapid Growth of Southland Called Economic Peril," Los Angeles Times, November 20, 1969. 8. Assessment ratios shown in Table A-13 were used to estimate the market values shown in Table A-12 and 7. 2k 7 9. Los Angeles, California, Police Department, Traffic Statistics, 1925-1968. 10. Herbert, "Rapid Growth, of Southland Called Economic Peril." 11. Jane Jacobs, The Death and Life of Great American Cities (New York: Random House, Inc.,1961), p. 35k. 12. By 1968, the ratio of population to registered motor vehicles in Los Angeles had decreased to 1.73* 13. Ray Herbert, "Downtown Traffic, Normal Monday - Slow, Congested," Los Angeles Times, February 18, 1969, Pt. II, p. 1. 14. Ezra J. Mishan, The Costs of Economic Growth (New York: Frederick A. Praeger, Publishers, 1967)* p. 76. 15. Herbert, "Downtown Traffic, Normal Monday - Slow, Congested. 1 1 16. "Crippling of Ground Traffic at L. A. Airport by 1985 Predicted," Los Angeles Times, October 27 > 1967, Pt. II, p. 1. 17. Per capita personal income in Los Angeles County in constant dollars is used as a measure of the per capita personal income in Los Angeles in this and some of the following sections of this chapter. 18. Ray Herbert, "Survey Explains Defeat of Rapid Transit Plan," Los Angeles Times. February 19» 1969, Pt. I, p. 3. 19. Southern California Rapid Transit District, Southern California Rapid Transit District Final Report (Los Angeles: Southern California Rapid Transit District, May, 1968). 20. Irving S. Bengelsdorf, "Man Must Develop New Respect for His World," Los Angeles Times. February 2, 1969* sec. G. p. 1. 248 21. Aerojet-General Corporation, California Waste Management Study. Report No. 3056 (Final) (Azusa, California: Aerojet-General Corporation, August, 1965), p. II—2. 22. Ibid., p. II-1. 23. Radioactive wastes are a special case. 24. "New Laws Sought to Control Exhaust Emissions of Airport," Los Angeles Times . January 6, 1969* Pt. II, p. 1. 25. Ibid. 26. Los Angeles County, California, Air Pollution Control District, Profile of Air Pollution in Los Angeles County (January, 1969),P*1» 27* Eh J. R. Bruckner, "World's Biggest Drive to Curb Pollution Begun," Los Angeles Times. October 26, 1969, sec. E . p . 1. 28. Henceforth, "crime rate" will refer to crimes per 100,000 population. 29* For definitions of these major crimes, see U. S. Department of Justice, Federal Bureau of Investi- gation, Uniform Crime Reports for the United States. 1968 (Washington, D . C . : U.sT Government Printing Office), pp. 55~5&* 30. Estimated net value of stolen property is estimated gross value of stolen property minus the estimated value of recovered property. 31. Table 15 shows that in 1968 the only case in which a crime rate for the rural population exceeded that of the suburban population was homicide. For all major crimes, crime rates for the suburban popu lation were lower than those for the national population. 249 32. In 1965, Los Angeles ranked as follows among cities with, populations of over 250>000 persons: Crime Rate per Crime 100.000 Population Rank Burglary 1 ,859 2 Robbery 293 6 Larceny, $50 and over 1 ,088 1 Auto Theft 810 6 Homicide 9 20 Forcible Rape 46 1 Aggravated Assault 337 4 Source: The President’s Commission on Law Enforce ment and Administration of Justice, Task Force Report: Crime and Its Impact - An Assessment (Washingt on, d" I C. : XL S. Government Printing Office, 1967)» appendix F. 33* The rate of decline in the three series of ratios is greatest for Los Angeles and the United States principally because of the much closer interdepen dence between (1) the rate of increase in the crime rate for Los Angeles and (2) those for the SMSA and the state. 34, Annual overall crime rate data for the United States are from Table 18. Annual data on the population of the United States are from U. S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States. 1968 (Washington, D . C . : U.S.GovernmentPrinting Office, 1968), p. 5, Table 2. 35. The Federal Bureau of Investigation lists 11 factors that; are believed to affect the amount and type of crimes committed: Density and size of the community population and the metropolitan area of which it is a part. Composition of the population with reference particularly to age, sex, and race. 250 36. 37. Economic status and mores of the population. Relative stability of population, including commuters, seasonal, and other transient types. Climate, including seasonal weather conditions. Educational, recreational, and religious characteristics. Effective strength of the police force. Standards governing appointments to the police force. Policies of the prosecuting officials and the c ourts * Attitude of the public toward law enforcement problems. The administrative and investigative efficiency of the local law enforcement agency, including the degree of adherence to crime reporting standards. From U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States. 1968 (Washington, D. C.: U. S. Government Printing Office), p. vi. U. S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States. 1962 (Washingt on, dT C. : U. s\ Government Printing Office, 1962), Table 421. For a more detailed discussion of the production, cost, and supply of individual urban public ser vices, see Werner Z. Hirsch, *'The Supply of Urban Public Services,” in Issues in Urban Economics, ed. by Harvey S. Perloff and Lowdon Wingo, Jr. (Baltimore: The Johns Hopkins Press, 1968), pp. 477-525. CHAPTER IV SOME EXTERNAL DISECONOMIES OF CROWDING IN LOS ANGELES, i960 The purpose of tills chapter is "to present the results of cross-sectional multiple regression and correlation analysis of (1) population density and over crowding, (2) commercial employment density and unemploy ment, and (3) selected measures of external diseconomies associated with intraurban differences in population density and overcrowding in Los Angeles in i960. The selected external diseconomies include substandard housing, crime, communicable disease, and separation and divorce. Except for the analysis of crime and communi cable disease, data for all variables are by i960 census tracts; for the i960 Census of Population and Housing, Los Angeles was divided into 628 census tracts. For the analysis of crime, i960 data are aggregated, where necessary, in terms of the 361 census tracts comprising Los Angeles in 1950- The 1950 census tracts were used for the analysis of crime rates because they are the smallest geographic units into which both i960 census tract data and crime statistics from police reporting districts could be aggregated. Selected communicable 251 252 diseases are studied at the level of the 61 statistical areas that the Los Angeles Department of City Planning had divided Los Angeles into in 19^0 because these are the smallest geographic units in which statistics on communicable diseases in i960 are available. Figure 42 shows the statistical areas of Los Angeles. except that for communicable diseases were made on an IBM 36O computer using a slightly modified version of 1 the Biomedical multiple-regression program BMD03R. Symbols used in multiple-regression equations in this The independent variables in each analysis are presented in their order of decreasing relative importance according to the value of the standard partial regression coeffi cient for the analysis. All multiple regression and correlation analyses chapter are shown in equation (116). (116) n Population Density and Overcrowding Population Density While the population of the Los Angeles area increased, the distribution of the population within Los 253 J C H A T IW O N T H IR AN AD A HILLS VAN NUY9 NORTH \ BURBANK HOLLYWOOD WOODLAND HILLS PACIFIC PALISADES H IL L S ■ILtHInC B O Y L E WEST ADAMS S A N T A M O N IC A \ . C U LV E R c t r r *VAL 0 H 5 ‘ wmww i\ VENICE H U N T IN G T O N P A R K t IN G L E W O O D S O U T H C A T E LY N W O O D E L S E G U N D O C O M P T O N T O R R A N C E Source: Los Angeles, California Department of City Planning i r i - T " ! Pig. 42.— Statistical Areas, Los Angeles Angeles changed as the population density of central Los Angeles increased and as transportation and communication systems were extended from the central section. The Los Angeles area population first spread to the south and west throughout much of the Los Angeles basin, then into the San Fernando Valley to the north and San Gabriel Valley to the east, and more recently into Orange County to the southeast and over the San Gabriel mountains into the desert communities of Lancaster and Palmdale. This sprawl of population, people’s predominant preference for single-family housing, and building code limitations on the height of buildings have resulted in low population densities throughout the county, relative to other large cities. Of the 21 cities with populations of over 500,000 in i960, only Houston, Dallas, New Orleans, San Antonio, and San Diego had lower population densities (Table A-2l). Of these five cities, only San Diego had a lower population density than Los Angeles in 19^-0. Between 19^-0 and i960, the land area of New Orleans decreased slightly, but the land area of San Diego increased about 102 per cent, that of Houston and San Antonio about 350 per cent, and that of Dallas about 590 per cent, compared with an increase in the land area of Los Angeles of only 1.5 per cent (Table A-22). The 255 ratio of the percentage change in land area to the per centage change in population of Los Angeles between 194-0 and i960 of 0.02 contrasts sharply with comparable ratios of 4-. 5 for Dallas, 2.7 for San Antonio, 2.4 for Houston, and 0.6 for San Diego (Tables A-22 and A-23). In other words, of the 21 cities with populations of over 500,000 in i960, only New Orleans had a population density that was less than that of Los Angeles and whose land area had not increased faster than its population. Despite the rapid growth of Los Angeles, over 30 per cent of the total land area of Los Angeles in i960 was either vacant or was being used for agriculture (Table 26). In i960, over one-half of the developed acreage of Los Angeles was in residential land use. Nearly another quarter of the total developed acreage of Los Angeles was used for streets and other transportation uses. Less than 7 per cent of the developed land in Los Angeles was used for industrial purposes. Table 27 shows the residential population, gross area, and population density of the statistical areas of Los Angeles in i960. Population densities range from 0.9 persons per acre in Pacific Palisades to 29*6 persons per acre in Westlake. The average population density of the Central Los Angeles section of 15*6 persons per acre 256 TABLE 26.— Land Use Acreages and 1960 Percentages, Los Angeles, Percentage of Total Percen tage of Type of Developed Total Land Use Acres Acreage Area Residential 106,221 52.5# 36.2$ Commercial 12,396 6.1 4.2 Community Services 21,125 10.4 7.2 Industrial 13,775 6.8 4.7 Transportation 5,780 2.9 2.0 Military 1 , 106 0.5 0.4 Streets 42,130 20.8 100.0$ 14.4 Vacant 77,731 26.5$ Agricultural 12,770 293,034 4.4 100.0$ Source: Los Angeles, Department of City Planning, Background Information for the Los Angeles Comprehensive Plan, Vol. 2: Analysis of the Land Use Characteristics. Research. Monograph. RM-SD-40041-01 (March. 1, 1968), Appendix I. 257 TABLE 27.— Population, Gross Area, and Population Density by Section and Statistical Areas, Los Angeles, April 1, i960 Section and Statistical Area Population Gross Area (Acres) Population Density (Persons per Acre) San Fernando Valiev Canoga Park 56,840 9,609 5.9 Chatsworth 21 ,837 10,645 2. 1 Encino - Tarzana 32,065 10,066 3.2 Granada Hills 41,744 6,514 6.4 North Hollywood 97,955 8,576 11.4 Northridge 16,678 3,792 4.4 Pacoima 69,050 8,438 ! 8.2 Reseda 66,397 5,980 11.1 Sepulveda 32,466 4,507 7.2 Sherman Oaks 28,334 4, 194 6.8 Studio City 25,677 4,705 5.5 Sunland 18,111 6,522 2.8 Sun Valley 46,292 12,123 .3.8 Sylmar 33,970 14,804 2.3 Tujunga 16,277 5,983 2.7 Van Nuys 112,118 13,322 8.4 Woodland Hills 23,759 7,858 3.0 Central Los Angeles Atwater Avalon Baldwin Hills Boyle Heights Central Downtown Eagle Rock El Sereno Elysian Park Exposition Park Glassell Green Meadows Griffith Park Highland Park 10,^90 52,486 23,404 84,733 23,367 20,295 20,249 29,477 24,459 70,488 21,44o 97,220 12,010 33,716 (Continued) 1,218 2,293 1 ,286 4,251 1,310 1 ,004 2,272 3,087 2,341 3, 183 2,000 5,076 4,792 2,683 8.6 22.9 18.2 19.9 17.8 20.2 8.9 9.5 10.4 22. 1 10.7 19.2 2.5 12.6 TABLE 27.— (continued) 258 Sect!on and Statistical Area P opula t i on Gross Area (Acres) Population Density (Persons per Acre) Central Los Angeles (cont •) Hollywood 130,133 9,293 1 4 .O Leimert 43,289 2,573 16.8 Lincoln Heights 31,396 2,276 13.8 Mt. Washington 15,147 1 ,495 10. 1 Santa Barbara 59,045 2,458 24.0 Silver Lake 40,696 2,333 17.4 South Vermont 63,242 3,673 17.2 University 21,623 1 ,277 16.9 Watts 34,001 1 ,255 27. 1 West Adams 69,677 3,484 20.0 West Hollywood 18,838 3, 130 6.0 Westlake 58,680 1 ,983 29.6 West Wilshire 39,750 1 ,968 20.2 Wholesale Industry 9,690 2, 153 4.5 Wilshire 79,654 3,5 40 22.5 Wilshire ~ West Pico 46,702 2,237 20.9 Western Los Angeles Bel-Air 7, 193 • * 9 • • Beverly Crest 7,379 5,084 1.5 Brentwood 22,342 1 , 137 19.6 Del Rey 23,607 1 ,342 17.6 Del Rey Palisades 4,839 1 ,252 3.9 Mar Vista 54,029 3, 199 16.9 Pacific Palisades 22,939 26,932 0.9 Palms 46,789 3,104 15.1 Venice 38,365 2,144 17.9 Westchester 51,141 7,051 7.3 West Los Angeles 30,928 2,393 12.9 Westwood 29,782 2,488 12.0 (Continued) TABLE 2 7 (continued) 259 Section and Statistical Area Population Gross Area (Acres) Population Density (Persons per Acre) Southern Los Angeles Dominguez • • • 290 • • Gardena 13,095 1 ,783 7.3 Harbor City 8,988 1 ,367 6.6 San Pedro 59,27*1 6,117 9.7 Torrance 9,792 1 ,088 9.0 Wilmington 31 ,547 6,701 4.3 San Fernando Valley 739,570 137,638 5.4 Central Los Angeles 1 ,279,795 81 ,924 15.6 Western Los Angeles 339,333 56,126 6.0 Southern Los Angeles 122,696 17,346 7.1 Los Angeles 2,*181 ,39*1 293,034 00 • Sources: Los Angeles, City Planning Commission, Research Section, Population Estimate and Housing Inventory (April 1968). Los Angeles, Department of City Planning, Background Information for the Los Angeles Comprehensive Plan. Vol. 2: : Analysis of the Land Use Characteristics. Research Monograph RM*-SD~40041 -01 (March 1 , 1968), Appendix II. 260 Is nearly triple (2.9 times) that of the Western Los Angeles section and 2.2 times that of the Southern Los Angeles section. Analysis of population density of 597 census tracts in Los Angeles indicated that much of the differ ences in population density can be explained by economic variables. Population density was made a linear function of employment density, median family income, median price of housing, and median rental rates. Population density generally can be expected to be greater in census tracts in which there is a high employment density because people can be expected to want to live relatively close to their place of employment so as to reduce the monetary and other costs of trips to and from work, However, because land use for business and industrial purposes is not available for residential use and because technology and preferences limit high employment and population densities that people will generally tolerate, there is a substitution effect between employment and population densities. Population density can generally be expected to vary inversely with median family income. Because most families prefer to reside in single-family housing units with a surrounding yard rather than in a multiple-family 261 housing unit, the prices of single-family housing units on limited urban land are relatively high. The higher the family income, the more the family can spend on housing and space; housing can be expected to be a normal good. However, at very high levels of median family income, population density can be expected to become an increasing function of median family income, as exemplified by high income families without small children living in densely populated luxury apartments and condominiums. Population density can be expected to vary inversely with the median price of housing and median rents. Estimates of the parameters of this population 2 density function are shown in equation (T17)• PD = 45.63 + 1.116 N - 0.0024 Y (4.280) (0.0550) (0.0004) - 0.0297 H + 0.0074 R (117) (0.0137) (0.02758) where PD = residential population per acre of residential land in the census tract N = employment per acre of land in the census tract Y = median family income in the census tract H = median price of housing in the census tract 262 R = median monthly rental rate in the census tract Table 28 shows statistics caloulcated from the sample data used in the multiple regression and corre lation analysis of population density as well as the levels of significance of the regression coefficients. The coefficients of N, Y, and H in equation (117) have the expected signs and are significant, but the coeffi cient of R does not have the expected sign and is not significant at any acceptable level of significance. Although the values of the coefficients in equation (117) cannot be taken too seriously because of multicollinearity among median income, median price of housing, and median rental rates, collectively the independent variables account for 60 per cent of the variation of population density among census tracts, and the F statistic is sig nificant at the 0.01 level of significance. The standard partial regression coefficients show that employment density and median family income are relatively more important than the median price of housing and median rental rate in explaining the variation in population density among census tracts. Overcrowding Population density is a limited measure of crowding because it relates the number of persons in a TABLE 28.--Statistics and Significance Tests, Population Density Function Variable X . J sx. j Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi ficance Of bj X = PD 0 30.619 17.444 * * * • • • » • • X = N 5.851 8.823 0.6408 0.5647 0.001 7 , 243.581 2,761.326 -0.2631 - 0.3736 0.001 X3 = H 170.102 49.002 -O.O891 - 0.0835 0.05 Xk = R 86.116 32.777 0.0110 0.0139 a n = 597 se = 11.07 r = 0.7744 R2 * 0.5997 F = 221.7 (D. F. = 4 , 592) (Significant at the 0.01 level of significance.) ®-Coefficient of R is not significant at any acceptable level of significance. 263 264 region to the land area of the region but does not reflect the degree of crowding within housing units, places of work, or other structures where people function. In Los Angeles, there are many relatively low-density sections that have many small housing units containing relatively large families. Crowding within housing units is commonly called overcrowding. The U. S. Bureau of the Census measures overcrowding in terms of the number of persons per room in a housing unit. Serious overcrowding is usually considered to exist when a housing unit contains an average of 1.01 or more persons per room. Like the analysis of population density, an analysis of overcrowding in 59^ census tracts in Los Angeles indicates that overcrowding also is predominantly a function of economic variables. Overcrowding, measured by the percentage of housing units in a census tract with 1.01 or more persons per room, was made a linear function of the median price of housing, median family income, percentage of housing units that are renter- occupied, and median rental rates. Overcrowding can be expected to vary inversely with the price of housing if for no other reason than that, for a given family size, higher priced housing units can be expected to have 265 more area (and rooms), thereby tending to reduce the overcrowding index. Xt follows that, given the size of families, overcrowding can be expected to vary inversely with income because increases in income allow families to spend more on housing, thereby tending to reduce the ratio of persons in the family to the number of rooms in the housing unit. Overcrowding also can be expected to vary inversely with the percentage of total housing units that are renter-occupied. Low-income families typically are not real-property owners but must purchase housing services through rental of single- or multiple-family housing units. Low income is the constraint on large families that results in overcrowding. Finally, over crowding, viewed as a price effect of intensive use of housing capital, can be expected to vary directly with rental rates. Equation (118) shows the estimates of the con stant and regression coefficients and their standard 3 errors. O' =30.1 - 0.1044 H - 0.0005 Y (2.358) (0.0073) (0.0002) + 0.0232 R - 0.0250 RO (118) (0.0145) (0.0129) 266 where O' = percentage of occupied housing units in the census tract that have 1.01 or more persons per room R0 — percentage of housing: units in the census tract that are renter-occupied The regression coefficients have the expected signs and are all significant at generally acceptable levels of significance (Table 29)* But, again, the values of the regression coefficients cannot be taken too seriously because of correlation among the independent variables. However, the regression equation accounts for nearly 70 per cent of the variation among census tracts in the percentage of housing units that are overcrowded, and the F statistic is significant at the 0.01 level of significance. Data from 71 census tracts in which at least 400 families with nonwhite heads-of-h.ouseh.old resided were used to study overcrowding in nonwhite housing units. Equation (119), which is similar to equation (118), shows the estimated values of the constant and regression 4 coefficients of the nonwhite overcrowding function. O' = 49.54 - 0.0044 Y - 0.1228 H n (1 6 .9 8 ) ( 0 .0 3 8 6 ) 11 ( o . 0386)n - 0.1530 RO + 0.1675 R (119) (0.0680) n (0.1804)n TABLE 29•--Statistics and Significance Tests, Overcrowding Function Variable X. 3 sx. J Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi ficance Of bj X 0 1 1 0 9.262 7.993 • • « • • • • • • X1 = H 170.388 48.544 -O.5056 -0.6338 0.001 X2 = Y 7,243.852 2,763.638 -0.1140 -o.1867 0.01 X3 = R 86.101 32.802 O.O656 0.0953 0.02 Xh = RO 44.425 23.248 -0.0791 -0.0726 0.01 n = 596 se = 5.803 R = 0.6902 R2 s: 0,^764 F = 134.4 (D. F. = 4, 591) (Significant at the 0.01 level of significance.) 267 268 where O* = percentage of occupied housing units n in the census tract with nonwhite heads-of-household that have 1.01 or more persons per room Y = median income of* nonwhite families in the census tract H = median price of housing units with n nonwhite heads-of-household in the census tract RO = percentage of the housing units with nonwhite heads-of-household in the census tract that are renter-occupied R = median rental rate of housing units with nonwhite heads-of-household in the census tract All regression coefficients have the expected signs and, except for Rn, are significant at acceptable levels of significance (Table 30). In general, multicollinearity is not as serious among the independent variables in equation (119) as among those in equation (118). Further more, equation (119) explains differences among census tracts in overcrowding in housing units with nonwhite heads-of-household somewhat better than equation (118) does for differences in overcrowding for all housing p units (R = 0.5123 for equation (119) compared with 9 R = 0.4764 for equation (118)), and the F statistic associated with the analysis of overcrowding in nonwhite housing is significant at the 0.01 level of significance. TABLE 30*— Statistics and Significance Tests, Nonwhite Overcrowding Function Variable X . 3 sx. j Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi ficance Of bj X 0 1 1 0 15.663 7.390 • • • • • • • • * 1 1 T — X 4,995.225 891.262 -0.3139 -0.5318 0.01 X = H 2 n 123.493 24.841 -0.3642 -0.4126 0.01 X 1 1 W 59.985 12.250 -0.2668 -0.2536 0.05 X. = R 4 n 74.535 7.008 0.1135 0.1588 a n = 71 se = 5.315 R = 0 .7 1 5 7 R2 = 0.5123 F = 17.33 (d. f . = 4, 66) (Significant at the 0.01 level of significance.) ^Coefficient of R^ is not significant at any acceptable level of significance. 269 270 In both, equations (118) and (119)» the median price of housing was relatively more important than the percentage of occupied housing units that are renter- occupied and the median rental rate. The median price of housing also was relatively more important than median family income in explaining differences in overcrowding for all housing units, but median family income is relatively more important for explaining differences in overcrowding in housing units with nonwhite heads-of- household . Commercial Employment Density and Unemployment Commercial Employment Density In studying population density, the location of residences was assumed to be a function of the loca tion of employment because it was assumed that people tend to live relatively close to where they work so as to reduce the costs of trips to and from work. Although this line of reasoning may be appropriate for studying the concentration of residential population relative to the location of total employment, a different approach must be used to explain the density of commercial employ ment. Commercial establishments can be expected to locate in greater density in accessible, usually central, 271 locations where population density is the greatest so as to minimize the distance between the establishments and as large a number of potential customers as possible, thereby maximizing the total quantity of goods and ser vices demanded from each establishment. Commercial employment also might be expected to be greater in areas where the median family income is high because the larger volume of commercial business transactions with higher- income families can be expected to be accompanied by greater commercial employment. Equation (l20) shows estimated values of the constant and regression coefficients and their standard errors for the regression of commercial employment density 5 on population density and median family income. N = -1.372 + 0.1322 PD + 0.0001 Y (120) ° ( 0. 8 1 5 3) ( 0. 0 0 7 8) ( 0. 0 0 0 1) where Nc = commercial employment per acre of land in the census tract Although the coefficient of PD and Y have the expected signs, only the coefficient of PD is significant; commercial employment density is not associated with median family income (Table 31)• However, the F statistic is significant at the 0.01 level of significance. TABLE 31*— Statistics and Significance Tests, Commercial Employment Density Function Variable X. J s x . J Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi- ficance Of bj X = N 0 c 3.823 7.717 • 1 • • • • • t 1 X = PD 1 34.189 34.932 O.5632 0.5982 0.001 X2 = Y 7,175.400 2,780.149 0.0386 0.0324 a n =618 se = 6.263 R = 0.5860 R2 = 0.3434 F = 160.8 (D. F. = 2, 615) (Significant at the 0.01 level of significance.) Coefficient of Y is not significant at any acceptable level of significance. 272 273 Unemployment Male unemployment in urban areas has been iden tified as a contributing factor in some urban problems, such as crimes against property and broken homes and marriages. An exploratory analysis was made of the rate of male unemployment as a function of the percen tage of the population that is nonwhite, median family income, population density, and employment density. Causality was not implied in formulating this relation ship; correlation is the more important aspect of analysis. Nonwhite population as a percentage of total popu lation was related to the rate of male unemployment because nonwhite male workers tend to be among the first workers to be laid off whenever market conditions dictate a reduction in production. Family income can be expected to vary inversely with the rate of male unemployment. Since relatively high rates of male unemployment can be expected among low-income families and low-income families can be expected to be living in high-density neighborhoods, high rates of unemployment should be expec ted to be more prevalent in low-income, high-density neighborhoods. Finally, the rate of male unemployment might be expected to be relatively higher in census 274 tracts with, high employment densities, because the rate of male unemployment can be expected to be greater among low-income families, which, in turn, typically live in the densely populated areas in or near areas of high commercial and industrial employment. The results of multiple regression and corre lation analysis of this function collaborated these hypotheses. Equation (121) shows the estimated values of the parameters of the unemployment function.^ U = 8.011 + 0.0464 B - 0.0005 Y (0 .4330) (0.0044) (0 .00005) + 0.0329 PD + 0.0213 N (121) (o.oo48) (0.0100) where U = unemployed males (in the labor force) as a percentage of the labor force in the census tract B = percentage of the population of the census tract that is nonwhite Although the coefficients of all the independent variables have the expected signs and are all significant, the presence of some multicollinearity, especially between population density and employment density, tends to reduce somewhat the confidence that can be placed in the accuracy of the estimated parameters. (See Table 32.) But the regression equation accounts for over one-half TABLE 32.--Statistics and Significance Tests, Unemployment Function Variable X . J s x . 3 Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi ficance of bj X = u 0 6.736 4.090 • • * • • • • 4 • X1 = B 17.456 29.076 O.3936 0.3301 0.001 x2 = Y 7,175.400 2,780.149 - 0.3622 -0.3195 0.001 X3 = PD 34.189 34.932 0.2681 0.2813 0.001 1! X 7.307 15.965 0,0859 0.0830 0.05 n = 6l8 se = 2.821 R = O.7263 R2 = 0.5276 F s 171.1 (D. F. = 4, 613) (Significant at the 0.01 level of significance.) SLZ 276 of tiie total variation in unemployment among census tracts, and the F statistic is significant at the 0.01 level of significance. The percentage of the population that is nonwhite and median family income are relatively somewhat more important than population density and considerably more important than employment density in explaining differ ences in the rate of male unemployment among census tracts. Substandard Housing Substandard housing in the form of deteriorated or dilapidated housing units is present to one degree 7 or another in every large city in the nation. An analysis of substandard housing in 62^- census tracts in Los Angeles indicated that the degree of substandard housing is associated with median price of housing, overcrowding, and population density. When housing units are over crowded because families residing in them do not have large enough incomes to be able to afford roomier quarters, then the physical condition of the housing units can be expected to deteriorate because incomes are not large enough for such families to adequately main tain the housing units. Often housing units that are rented by low income families are not maintained by the 277 landlord if the often-absentee landlords of such housing units do not enter into rigorous price competition. External diseconomies arise when housing units are allowed to deteriorate or to become dilapidated because the value of individual housing units is in part a function of the quality of the neighborhood environ ment. Consequently, substandard housing can be expected to be associated with the median price of housing. The degree of substandard housing also can be expected generally to vary directly with population density because they can both be viewed as effects of low income. Equation (122) shows estimates of the constant and regression coefficients of the substandard housing g func tion. D = 14.02 - 0.0648 H + 0.4390 O' (0.6444) (O.OO87) (0.0566) + O.O563 PD (122) (0.0070) where D = percentage of occupied housing units that are either deteriorated or dilapidated Not only do the regression coefficients have the expected signs and are all significant at the 0.001 level of significance, but there is no strong multicollinearity among the independent variables (Table 33). The inde pendent variables in the regression equation collectively TABLE 33*— Statistics and Significance Tests, Substandard Housing Function Variable X . J s x . J Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi ficance Of bj X = D o 9.506 12.552 • • • • • • • • • II a 163.143 58.876 -0.2858 -0.3039 0.001 x 2 = O' 9.376 8.358 0.2976 0.2923 0.001 X3 = PD 37.800 61.367 0.2836 0.2506 0.001 n = 624 se = 9*622 R s 0.6444 R2 = 0.4152 F = 146,7 (d. F. B 3, 620) (Significant at the 0,01 level of significance.) 278 279 account for over 40 per cent of the variation in the degree of substandard housing among census tracts, and the F statistic is significant at the 0.01 level of significance. A similar analysis was conducted of substandard housing units in census tracts in which the heads of the households were nonwhite. Data were available only for census tracts with at least 400 such households; there were 75 such census tracts in Los Angeles. Equation (123) shows the estimated values of the constant and regression coefficients for the nonwhite substandard housing 9 10 function. * D = 42.02 - 0.2273 H 11 (8.791) (0.0631)11 + 0.1224 O' (123) (0.2234) n where O 1 = percentage of housing units in the census tract with nonwhite heads-of- household that are either deteri orated or dilapidated Table 34 shows that although the regression coefficient of H is significant at the 0.001 level of significance, the regression coefficient of 01 is not significant at any acceptable level of significance. Furthermore, and O' are moderately correlated. Although only a little more than one-quarter of the variation in the TABLE 34.— Statistics and Significance Tests, Nonwhite Substandard Housing Function Variable X . J SX . J Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi- ficance Of bj X = D 0 n 15.448 12.957 • t • • • • • • » a B I I T— X 125.387 26.661 -0.3906 -0.4677 0.001 x 0 = 0 2 n 15.756 7.533 0.0644 0.0711 a n = 75 se = 11,26 R = 0.515^ R2 = 0.2656 F = 13.02 (D. F. = 2, 72) (Significant at the 0.01 level of significance.) aCoefficient of 0n is not significant at any acceptable level of significance. 280 281 degree of* nonwhite substandard housing among census tracts is explained by the median price of nonwhite housing and overcrowding in nonwhite housing units, the F statistic is significant at the 0.01 level of significance. The price of housing is relatively the most important variable in both equations (122) and (l23)» However, overcrowding is virtually as relatively impor tant as the price of housing for explaining differences in all substandard housing, whereas overcrowding in non white housing units is not associated with substandard housing units with nonwhite heads of household. Popu lation density is also a relatively important factor in explaining differences in all substandard housing units. Crime As the population of a city increases, the people in the city typically are forced to interact, on the average, more frequently in an increasingly more com plex, interrelated, and congested social and physical environment. Many of the detrimental social and psycho logical effects of this crowding phenomenon can be traced to underlying economic factors or to demographic factors that are closely associated with economic factors. Increases in urban crime rates are one of the more disturbing effects of increases in urban population 282 and the typically corresponding increases in population density. Table 16 shows that the nates of all of the serious crimes per 100,000 population tend to be higher the larger the population of the city. In Los Angeles, crime rates are among the highest in the nation and are tending to rise every year (Tables 17j 18, and 20 and Figure 39). Two analyses were made of crime rates in Los Angeles, the first dealing with crimes against property— burglary, robbery, larceny and auto theft— and the second with crimes against persons--homicide, forcible rape, and aggrevated assault. The rate of crimes against property per 1,000 population in a census tract might be expected to vary directly with the rate of male unemployment, population density, and commercial employment density and inversely with the percentage of families with annual family incomes of $10,000 or more and median family income. The rate of crimes against property could be expected to increase with the rate of male unemployment because curtailed income caused by unemployment tends to exclude people from markets, and theft is an alternative to market exchange for obtaining goods and services. The rate of crimes against property can be expected to increase with 283 population density for several reasons. In densely popu lated sections of a city, temptations and opportunities to steal are more abundant. Also, densely populated sections usually contain predominantly low-income families. Some members of low-income families living in a generally affluent society may be expected to revert to theft as a means of supplementing the family income des pite the potentially high penalty costs of stealing. For some people living in low-income, high-density sections of a city, theft may serve as a psychological escape from the depression of poverty and, in a sense, provide a form of recreation. The rate of crimes against property can be expected to increase with increases in commercial employ ment density because of the increased temptations and opportunities afforded by the proximity and concentration of consumer goods and money that are usually associated with concentrations of commercial employment. The rate of crimes against property can be expected to vary inversely with the percentage of families in the census tract with annual incomes of $10,000 or more and with increases in median family income because both income variables are measures of the ability of the resi dents of the census tract to adequately satisfy their wants through market exchange without resorting to theft. 284 Equation (124) shows the estimated, values of the constant and regression coefficients of the rate of 1 1 crimes against property function. C1 = 31.88 + 5.054 U + O.O76O PD (15-84) (1.576) (O.0409) - 0.5569 Y + 0.5551 Nc (0.3720) (0.5008) - 0.0107 Y (124) (0.0133) where C.j = crimes against property per 1,000 population of the census tract Yu = percentage of the families in the census tract with annual family incomes of $10,000 or more The coefficients of all the independent variables have the expected signs, however, only TJ, PD, and Yu are sig nificant at acceptable levels of significance (Table 35). None of the partial correlation coefficients have values close to 1 or -1, and the linear combination of all the independent variables in the regression equation accounts for only 15 per cent of the variation in the rates of crime against property among census tracts. However, the F statistic is significant at the 0.01 level of signi ficance. Multicollinearity is not serious except between TJ and Y (r = -0.6314) and between PD and N„ u ' ' c (*2,4 = °-7554). TABLE 35•--Statistics and Significance Tests, Rate of Crimes Against Property Function Variable X . J sx. 3 Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi ficance of bj X = Ci 0 1 61.815 90.634 • • « • 1 • • • • x1 = U 7.434 3.719 0.1683 0.2074 0.01 X, = PD 54.945 166.889 0.0983 0.1399 0.1 >? I t I c - ' X! 19.666 15.426 -0.0794 -0.0948 0.2 X,( = N 4 c 5.592 13.576 0.0589 0.0831 a X„ = Y 5 370.897 336.653 -0.0429 -0.0397 a n = 359 se = 83.98 R =0.3916 R2 = 0.1534 F = 12.79 (d. F. = 5, 353) (Significant at the 0.01 level of significance.) Coefficient for Nc and Y are not significant at any acceptable levels of significance. 285 286 In the second analysis, the rate of crimes against persons was specified as a function of the rate of male unemployment, overcrowding, population density, and median family income. The rate of crimes against persons can be expected to vary directly with the rate of male unemployment. Because unemployment interrupts the normal inflow of buying power of the family, it tends to disrupt family living patterns, to cancel or to modify many family plans, and, in general, to product anxieties, fears, and antagonistic and irritable attitudes among the members of the family and the community. Psycho logical tensions, worries, and feelings of depression and despair can lead to physical outbursts of violence in the form of assault, battery, forcible rape, or even murder. The rate of crimes against persons within a census tract can be expected also to vary directly with overcrowding. Experiments with animals have indicated 1 2 that overcrowding leads to abnormally violent behavior. Somewhat similar behavior might be reasonably expected of humans under overcrowded conditions. Similar reasons can be used to support the hypothesis that the rate of crimes against persons can be expected to vary directly with population density. Finally, the rate of crimes against persons can be expected to vary inversely with 287 the median family income of the census tract because many of the previously mentioned effects of unemployment can also be expected to prevail in low-income census tracts and to diminish in intensity with increases in median family income. An analysis of the rate of crimes against persons among 358 census tracts as a function of these variables provided the estimates of values of the constant and regression coefficients of the independent variables 1 3 shown in equation (125). C = -3-7^7 + 1.066 U + 0.0925 O' (0.9800) (0.0981) (0.04l6) + 0.0029 PD - 0.0001 Y (125) (0.0019) (0.0009) where = crimes against persons per 1,000 population of the census tract The regression coefficients have the expected signs and, except for Y, they are all significant at acceptable levels of significance. The coefficient of multiple correlation of 0.387^- and the significance of the F statistic at the 0.01 level of significance indicates that much of the variation in the rate of crimes against persons among census tracts is accounted for by the independent vari ables in equation (125). TABLE 3^.— Statistics and Significance Tests, Rate of Crimes Against Persons Function Variable X. a sx . j Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi- ficance Of bj “ Co O 2 5.155 7.272 • • « • ♦ • • • • x1 0 U 7.413 3.702 0.5010 0.5430 0.001 X2 = 0. 9.633 8.487 0.1174 0.1079 0,05 Q ft I I 54.908 167.121 0.0803 0.0657 0.2 X4 s Y 370.904 337.124 -0,0081 -O.OO65 a n = 358 se = 5.724 R = 0,6224 R2 = 0.3874 F = 55.81 (D. F. = 4, 353) (Significant at the 0,01 level of significance.) ^Coefficient of Y is not significant at any acceptable level of significance. 288 289 Although, in general, these two analyses pro duced expected results, a few unexpected results suggest interesting inferences. In both analyses, the partial correlation coefficients for U (with and respec tively) were greater than those for any other independent variables, and the absolute value of the standard partial regression coefficient for U in both equations was larger than those for the other independent variables in the equations. Also, the regression coefficient of Y in both equations (124) and (125) were not significant at any acceptable level of significance; correspondingly, the partial correlation coefficient and the standard partial regression coefficient for Y in both analyses were the smallest of all the independent variables in each analysis. Table 32 shows that the rate of male unemploy ment and median family income are associated. But these analyses of crime rates indicate that high crime rates are associated with unemployment but not median family income. In other words, crime rates are high not so much because of relative poverty but because of unemploy ment. These conclusions suggest that crime rates might be reduced through effective policies and programs to reduce the rate of male unemployment. 290 Communicable Diseases As population density and overcrowding increase with, the growth of an urban population, the incidence of communicable diseases per 10,000 population can be expected to increase because of the greater degree of proximity of people to one another within the community and the greater number of overcrowded housing units. However, advances in medical science and technology, more extensive and more effective public health programs, an increasingly better-educated population, rising per capita personal income^, and other factors generally tend to more than offset the effects of increased population density and overcrowding. None of the 37 communicable diseases for which there are data on the rate of cases per 100,000 population in Los Angeles and Los Angeles County had any definite positive trend in the disease 1 4 rate. The rates of most communicable diseases have generally declined since 1920; the rates of several diseases have decreased to or virtually to zero. Among the 61 statistical areas of Los Angeles in 1960, tuberculosis, venereal disease, mumps, and measles had the greatest incidence. However, of the four diseases, tuberculosis, mumps, and measles are relatively more relevant than venereal disease in the study of the 291 effects of crowding1 on the rates of communicable disease. The rates of each of these three diseases were analyzed as functions of population density and overcrowding. The estimated values of the constants and regression coeffi cients in linear regression equations for the rates of these three diseases are shown in equations (126) through MU = cases of mumps per 10,000 population of the statistical area ME = cases of measles per 10,000 population of the statistical area Tables 37 through 39 show statistics and the results of significance tests for tuberculosis, mumps, and measles functions respectively. TB a = -6.529 + 0.3579 PD + 0.1680 O' (0.0356) (0.2008) (126) MU a = k.k-Ok + O.3562 O' - 0 .03^8 PD (0.0861) a (0 .0153) a (127) ME a = 11f. 15 + 0.6855 O' - 0.0292 PD (0.2057) a (O.O365) a (128) where TB = cases of tuberculosis per 10,000 population of the statistical area PD = population density of the statistical area O' = percentage of occupied housing units in the statistical area with 1.01 or more persons per room 292 TABLE 37*— Statistics and Significance Tests, Tuberculosis Rate Function Variable X . J SX. 3 Standard Partial Regres sion Coefficient Level of Signi ficance of bj X = TB 0 a 6.4i5 15.475 • • « • • • X1 = PDa 32.215 34.554 0.7993 0.05 X2 = °'a 8,41 6 6.142 O.O667 d n = 6 1 se = 8.929 R = 0.8266 R2 = 0.6833 F = 62.57 (D. F. = 2, 58) (Significant at tlie 0.01 level of significance.) ^Coefficient of 0'a is not significant at any acceptable level of significance. % 293 TABLE 38.— Statistics and Significance Tests, Mumps Rate Function Variable X . J sx. J Standard Partial Regression Coefficient Level of Signi ficance Of bj X = MU 0 a 6.280 4.267 • • • • • • X1 = °'a 8.416 6.142 0.5129 0.05 X2 = PDa 32.215 34.554 -0.2824 0.05 n = 61 se = 3.830 R = 0.4836 R2 = 0.2339 F = 8.854 (D. F. = 2, 58) (Significant at the 0.01 level of significance.) 294 TABLE 39.— Statistics and Significance Tests, Measles Rate Function Variable X . 3 sx . 3 Standard Partial Regression Coefficient Level of Signi ficance of b j X = ME 0 a 18.975 9.754 • • • « • • X1 = 0' a 8 .416 6. 1^2 0.4317 O • O X2 = PDa 32.215 34.554 -0.1038 a n = 61 s© = 9.148 R = 0.4043 R2 = O.1635 F = 5-668 (D. F. = 2, 58) (Significant at the 0.01 level of significance.) ^Coefficient of PDa is not significant at any accept able level of significance. 295 Population density is much, more important than overcrowding in explaining the variations in the rate of" tuberculosis among statistical areas (Table 37). In fact, the regression coefficient of O' is not signifi- Si cant at any acceptable level of significance. However, collectively, population density and overcrowding account for nearly 70 per cent of the variation in the rate of tuberculosis among the 61 statistical areas, and the F statistic is significant at the 0.01 level of significance. By contrast, overcrowding is more important than population density in explaining the variation in the rates of mumps and measles among statistical areas (Table 38 and 39). The regression coefficients for PDa and O1^ are both significant at the 0.05 level of significance in the mumps rate function. But only the regression coeffi cient of O' is significant at the 0.05 level of signi- el ficance in the measles rate function; that of PB& is not significant at any acceptable level of significance. Although population density and overcrowding collectively account for only a little more than 23 per cent and 16 per cent of the variation in the mumps rate and measles rate, respectively, among the statistical areas, the F statistic for both the mumps and flieasles rates functions are significant at the 0.01 level of significance. 296 Multicollinearity in equations (126) through ( 128) is weak in that the simple correlation coefficient for population density and overcrowding is only 0.3757* Separation and Divorce Economic problems associated with low family income and/or the threat of extended periods of low income caused by unemployment have long been known to be among the leading causes of marital separation and divorce. Separation and, especially, divorce can be expected generally to have detrimental external effects upon those other than the husband and wife, such as children, other relatives, and the people in the community generally. In an analysis of the degree of separation and divorce among 616 census tracts in Los Angeles, the degree of separation and divorce was made a function of the rate of male unemployment, median family income, and two income-related demographic indices of crowded living-- population density and overcrowding. The degree of separation and divorce can be expected to vary directly with the rate of male unemployment. Much of the rationale for hypothesizing the relationship between the rate of male unemployment and the rate of crimes against persons applies to the relationship between the rate of male 297 unemployment and separation and divorce. One might view separation and divorce and crimes against persons as substitute reactions or intended solutions for mitigating some of the problems that arise in part from unemployment. The degree of separation and divorce can be expected to vary inversely with the median family income of a census tract because of the hardships of family living with relatively low incomes. The degree of separation and divorce might be expected to vary directly with population density. Families in census tracts having relatively high popula tion densities live, on the average, closer to other families, individuals, and institutions that may result in greater irritations, such as increased noise and dirt, and more extra-familial attractions that over time may distract members of families away from one another. Some extra-familial relationships, including for example, extra-marital relations of husbands or wives, juvenile relationships that tend to facilitate crime, or relation ships related to illegal drug transactions, can be expected either to cause or to facilitate the dissolution of the family through separation or divorce. The relationship between the degree of separation and divorce and overcrowding in a census tract cannot be stated a priori with much certainty. On the one hand, 298 expect that the degree of separation and divorce would vary directly with overcrowding because overcrowding and its previously mentioned associated problems can be viewed as causal factors of family strife, which can lead to separation or divorce. On the other hand, overcrowding is closely associated with large families. At least in a quantitative sense, the greater the number of children in a family, the greater is the task of raising the children. Since child-raising by parents is a quite strongly held value in the United States, one might expect that the degree of separation and divorce would vary inversely with overcrowding to the extent that over crowding reflects the size of the family. In a multiple regression and correlation analysis of the degree of separation and divorce among census tracts in Los Angeles, the percentage of females 14 years old or older in the census tract who are either separated or divorced was used as a measure of the degree of separation and divorce in the census tract. The rationale behind using this statistic was that when a couple in Los Angeles are separated or divorced, the woman generally can be expected, more often than the man, to remain in the census tract with the house, furniture, and children, if any, and to be tied to the house in part, because any school-age children usually are established in the local 299 schools. Consequently, the census count of1 separated or divorced women as a percentage of1 the total number of women in the census tract seems to be a reasonable measure of the degree of separation and divorce. Equation (129) shows the estimated values of the 17 parameters of the separation and divorce function. SD = 7.757 + 0.7044 U - 0.0004 Y (O.6551) (0.0468) (0.00007) + 0.0135 PD - 0.0365 O' (129) (0.0046) (0.0199) where SD = percentage of females 14 years old or older in the census tract who are either separated or divorced The coefficients of all of the independent variables are significant (Table 4o). However, the values of these coefficients should not be taken too seriously because of multicollinearity among several independent variables. The standard partial regression coefficients in Table 40 show that the rate of male unemployment is relatively much more important than the other indepehdent variables in explaining the variation in the degree of separation and divorce among the census tracts, followed in the order of decreasing relative importance by median family income, population density, and overcrowding. The regression coefficient of O’ indicates that the degree of separation and divorce varies inversely TABLE 40.--Statistics and Significance Tests, Separation and Divorce Function Variable X. J sx. J Partial Correlation Coefficient Standard Partial Regression Coefficient Level of Signi ficance Of bj X = S 0 9.837 5.052 • • • • • • « • • x - , - U 6.757 4.079 0.5200 0.5687 0.001 X2 = Y 7,182.556 2,773.337 -0.2310 -0.2141 0.001 X^ = PD 34.236 34.978 0.1170 0.0937 0.01 xk = O' 9.350 8.326 -0.0742 -0.0602 0.1 n =616 se = 3.392 R = 0.7430 R2 = 0.5521 F = 188.3 (D. P. =4, 611 ) (Significant at the 0.01 level of significance.) 300 301 with, overcrowding, This result might be interpreted as supporting the hypothesis that the greater the number of children in a family, the less likely that husband and wife will separate or become divorced. Collectively, the independent variables in equation (129) account for over 55 cent of the varia tion in the degree of separation and divorce among census tracts, and the F statistic is significant at the 0.01 level of significance. 302 Footnotes to Chapter IV 1. Wilfrid J. Dixon, ed., BMP Biomedical Computer Programs (Berkeley and Los Angeles: University of California Press, ^^68). 2. Data used in this analysis were from the following sources: U. S. Department of Commerce, Bureau of the Census, County and City Data Book. 1967 (Washington, D. C.: U. S. Government Printing Office); Employment data from the Los Angeles Rapid Transit Study (LARTS) were obtained from the Los Angeles, California, Department of City Planning; Land area data are from the Los Angeles, California, Department of City Planning. 3. Data used in this analysis were from U. S. Department of Commerce, Bureau of the Census, County and City Data Book. 1967 (Washington, D. C.: U. S. Government Printing Office). 4. See footnote 3» 5. See footnote 2. 6. See footnote 2. 7. The U. S. Bureau of the Census defines a deteri orated housing unit as one that needs more repair than would be provided in the course of regular maintenance and has one or more defects of an intermediate nature that must be corrected if the unit is to continue to provide safe and adequate shelter, A dilapidated housing unit is defined as one that does not provide safe and adequate shelter because it has one or more critical defects, or has a combination of intermediate defects in sufficient number to require extensive repair or rebuilding, or iS of inadequate original construc tion. See U.„ S. Department of Commerce, Bureau of the Census, U. S. Census of Population and Housing: 1960. Census Tracts: Los Angeles - Long Beach. California (Washington, D^ C•: U.Government Printing Office, 1962), p. 6. 303 8. Data used In this analysis were from U. S. Department of Commerce, Bureau of the Census, County and City Data Book. 1967 (Washington, D. C.: U. S. Government Printing Office); Land area data from the Los Angeles, California, Department of City Planning. 9. See footnote 3* 10. Population density was not included as an inde pendent variable in equation ( 123), whereas it had been in equation (122), because population density data for sub-populations were not available by census tracts. Although data on, say, the non white population is available by census tract, the corresponding data on the residential land used by the nonwhite population in each census tract was not available. 11. Data used in this analysis were from Los Angeles, California, Police Department; U. S. Department of Commerce, Bureau of the Census, County and City Data Book. 1967 (Washington, D. C.: U. S. Government Printing Office); Los Angeles, California, Department of City Planning. 12. Edward Twitchell Hall, The Hidden Dimension (Garden City, N. Y.: Doubleday & Company, Inc., 1966), chap. iii. 13* See footnote 11. 14. Based on data from the Los Angeles County, California, Health Department. 15 • Data used in these analyses were obtained from the following sources: Los Angeles County, California, Health Department; XJ. S. Department of Commerce, Bureau of the Census, County and City Data Boole. 1967 (Washington, D. C.: U. S. Government Printing Office); Land area data are from the Los Angeles, California, Department of City Planning. 30k 16. Data on disease are reported by the statistical area in which, the medical doctor or health agency is located, not necessarily by the statistical area in which the disease was contracted nor in which the patient lives. 17* See footnote 8. CHAPTER V EVALUATION AND CONCLUSIONS The purposes of this chapter are to evaluate the general results of this study and to discuss some con clusions that might be inferred from it. Avenues of further research and some general policy guidelines are mentioned. The purposes of this dissertation, as stated in Chapter I, are: (1) To summarize economic theoretical concepts relating to external economies of urban economic growth, urban growth, urbanization, and crowding. (2) To study the relationships between economic, demographic, and social variables that are believed to be associated with selected external diseconomies of urban growth in Los Angeles and Los Angeles County. (3) To study the relationships between economic, demographic, and social variables that are believed to be associated with differences in the degree of selected external disecono mies among census tracts and statistical areas in Los Angeles. A chapter is devoted to each of these objectives. In Chapter II, the summary of theoretical con cepts from welfare economics, location theory, land use theory, and urban growth theory that relate directly or 305 306 indirectly to external effects of urban growth, and crowd ing is the only known comprehensive treatment of these theoretical topics within the context of the external effects of urban growth and crowding. Most of the further theoretical work on the external effects of urban growth and crowding undoubtedly will be done in static and com parative static utility, production, and welfare economic theories within the general context of urban economic and population growth. One of the more promising develop ments in the theoretical analyses of external effects in the theory of the firm seems to be in a more intensive and integrated theoretical treatment of transfer econo mies, economies of large scale production, localization economies, and urbanization economies. An initial attempt at this task is presented in the second section of Chapter II. Because external effects of urban growth and crowding arise otit of the dynamic processes of urban economic and population growth, these effects ultimately must be analyzed through the study of the urban economic and population growth processes themselves. Further work in the theory of urban economic growth might be made more realistic and more accurately predictable through the incorporation of growth trends or other curvilinear functions having diminishing marginal 307 increases that reflect the psychological and techno logical limitations of crowding. The empirical portions of this study presented in Chapters III and TV are essentially correlation analyses of the degree of association between selected external diseconomies of urban growth and crowding and economic, demographic, and social variables believed to be causally related to the external diseconomies. None of these analyses are intended to be exhaustive or to fully explain these external diseconomies. Specific policy recommendations for any particular external dis economies will necessitate further in-depth research and analysis beyond the scope of this study. Analyses in Chapter III of selected external dis economies believed to have resulted from the population and economic growth of the Los Angeles area show highly significant degrees of association between these external diseconomies and population and per capita income. Traffic congestion, daily automobile emissions by weight, and per capita local government expenditures increase directly and linearly with both population and per capita personal income in constant dollars. Land values in constant dollars also vary directly with population and per capita personal income in constant dollars. Although 308 land values are more closely correlated with, population and per capita income when linear functions are fitted to the data on these variables rather than to the logarithms of the data, still, when logarithms are used, the coefficients of the logarithm of population and of the logarithm of per capita income are both significantly greater than 1. These results indicate that there is a tendency for land values to increase somewhat faster than population and per capita personal income. More definite curvilinear relationships are indicated between overall crime rates per 10,000 popu lation of Los Angeles and population and per capita personal income. Both population and per capita income are significantly related to the overall crime rate, even when time is taken into account. However, because time is closely correlated with both population and per capita personal income, simple linear relationships between the overall crime rate and population and per capita income were studied. Even though the overall crime rate in Los Angeles is closely correlated with both population and per capita income, nevertheless, when the relationships are studied using the logarithms of the data, the coefficients of the logarithms of population and per capita income indicate that the overall crime rate is 309 increasing faster than population or per capita income. Furthermore, the rates of crimes against property and against persons are also increasing faster than the population. Interestingly, when population is taken into account, there is a significantly negative trend in the overall crime rate in Los Angeles, as well as nationally. The analyses in Chapter III show the close association between the population and economic growth of the Los Angeles area and the external diseconomies of increased land values, traffic congestion, air pollution, crime rates, and per capita government expenditures. Public policies designed to reduce the rate of growth of population in the Los Angeles area and to pro mote the productivity of the local labor force through education and training coupled with labor-saving capital investment could be expected to reduce the rate of increase in these external diseconomies of urban growth. However, policies affecting the industry mix and indus trial diversification of the area, as well as the overall level of economic activity, can affect the rate of econo mic growth of the area. Consequently, before labor- saving capital investment policies are promoted, public and private, urban and regional economic development agencies should first carefully consider the income level, 310 stability, and. growth implications of* such policies and weigh the benefits of planned economic growth and deve lopment against the costs of increased external disecono mies of population and economic growth. Close coordinatkn between private and public agencies is important if significant improvements are to be realized at the county or city levels. Cross-sectional analyses in Chapter IV among the census tracts and statistical areas of Los Angeles show the close association between economic variables and crowding and between economic, demographic, and social variables and the degree of selected external disecono mies. The population density of a census tract depends principally upon the employment density and median family income and, to a lesser extent, upon the median price of housing in the tract. The principal determinant of differences in overcrowding among all census tracts is the median price of housing, although median family income, median rental rates, and the percentage of occupied housing units that are renter-occupied are also significant determinants. In housing units with nonwhite heads-of-household, both median family income and the median price of housing are the most important deter minants of overcrowding; the percentage of occupied 311 housing units that are renter-occupied is also a signi ficant factor. Commercial employment density is the greatest where population density is the highest; however, commer cial employment density is not significantly associated with the median family income of the census tract. These results may have been obtained partly because people working in commercial establishments can be expected to live near their place of work and because the incomes of retail trade and many service employees are relatively lower than those of employees in other industrial sectors. However, this factor cannot be seriously accepted as a significant explanation of the results obtained in the analysis. Commercial employment density depends upon the density of the population, not so much upon the income earned by that population. The rate of male unemployment is closely associ ated with the percentage of the population that is non white, median family income, population density, and, to a lesser extent, with employment density. These results agree with other studies which indicate that unemployment is greatest among low-income, nonwhite males who typically live in high-density areas near the central city among or near industrial and commercial centers. 312 Studies of* differences in external diseconomies of substandard housing, crime rates, communicable disease, and separation and divorce among the census tracts or statistical areas of Los Angeles produced some interesting results. Substandard housing in Los Angeles is associated with low-priced housing, overcrowding, and high population density. However, substandard housing units with non white heads-of-household are associated with low-priced housing units but not with overcrowding in these housing units. Differences in the rate of crimes against property among the census tracts of Los Angeles are directly associated with differences in the rate of male unemploy ment and population density and, to a lesser extent and inversely, with differences in the percentage of families with incomes of $10,000 or more. The rate of crimes against property is not associated with commercial employment density nor with median family income. Differ ences in the rate of crimes against persons are closely associated with differences in the rate of male unemploy ment and, to lesser extents, with overcrowding and popu lation density. The rate of crimes against persons is not associated with median income. Crime rates, then, 313 tend to be highest in census tracts where there is a high rate of male unemployment, high population density, overcrowding, and a low percentage of upper-level income families. Therefore, crime rates might be reduced in the short term through policies and programs designed to reduce the rate of male unemployment. However, in the long term, problems of high-density living in overcrowded housing units probably will be relieved only through effective manpower development and employment programs aimed at increasing the productivity and improving the employment opportunities of low-income workers. Public health programs in Los Angeles have been very effective in reducing the rates of nearly all communicable diseases despite increases in the population density. An analysis of tuberculosis indicates that the rate of tuberculosis cases per 10,000 population is associated with population density but not with over crowding. Similar analyses indicate that the rate of mumps is associated with both population density and overcrowding but that the rate of measles is associated only with overcrowding. The index of marital separation and divorce is highest in those census tracts with a high rate of male unemployment, low median family income, high population 31 4 density and, to a lesser extent, with, a low percentage of overcrowded housing units. The policy goals of reducing unemployment and increasing productivity and income men tioned for reducing crime rates apply also to reducing the rate of separation and divorce because these problems are associated with common economic and demographic variables. The inverse relationship between the index of separation and divorce and overcrowding may reflect the effect of the size of the family on the rate of separation and divorce. «5 Most of the external diseconomies studied in Chapter IV are either functions of economic variables or of demographic variables that are closely associated with economic variables. The underlying economic causes of many of these problems can be traced to low produc tivity as reflected in unemployment and low incomes and in the environmental problems of high population density and overcrowded living that are associated with low income. Private and public policies and programs to reduce many of these external diseconomies should be directed at the underlying causes of these problems. Previously mentioned short-term employment programs by ! both private and public agencies and long-term education, vocational training, and improved employment opportunity 315 programs undoubtedly would reduce the seriousness of many existing external diseconomies of crowding. However, employment and manpower development programs are not enough. The way Los Angeles, or any other large city, is to develop, grow, and change can be and should be con trolled through urban and regional planning. Successful planning requires the mutual cooperation of private groups, individuals, and the city and county planning commissions and departments. Several statistical problems were encountered in this study. In Chapter III, autocorrelation of time series data and multicollinearity made it impossible to take estimates of multiple regression coefficients seri ously. Multicollinearity presented the same problem, although to a considerably lesser extent, in the cross- sectional analyses in Chapter IV. These problems are common in econometric analysis and can be expected to be even more pronounced than usual in urban economic analysis because of the high degrees of interdependence among urban economic, demographic, and social variables. An extensive set of data on economic, demographic, and social variables, especially for the Los Angeles area, were collected and used in this study. Much of this data are included in tables in Chapter III and the appen dix. Data on economic, demographic, and social variables 316 for the 632 census tracts and 61 statistical areas of Los Angeles used in Chapter IV were not included because of the large number of variables and the large number of census tracts and statistical areas. The bibliography at the end of this dissertation contains a relatively comprehensive set of references to the principal literature on location theory, land use theory, and urban and regional growth theory. APPENDIX SUPPLEMENTARY TABLES 317 318 TABLE A-1.— Brftan Population of* the United. States, Regions, and States, Census Yeans 1900 to 1940 (Urban Population in Thousands of Persons) 1900 1910 1920 1930 1940 United States 30,380 45,614 54,158 68,955 74,424 New England 4,053 4 ^ 8 5.620 6,312 6.421 Maine 233 262 300 322 34 3 New Hampshire 226 255 250 273 283 Vermont 76 99 1 10 1 19 123 Massachusetts 2,567 3,125 3,469 3,831 3,859 Rhode Island 408 525 555 635 653 C onne cticut 544 732 936 1 , 132 1 , 158 Middle Atlantic 10.076 13,7,23 .16,783 20,395 21 .148 New York 5,298 7, 185 8,589 10,522 11,166 New Jersey 1 ,329 1,907 2,522 3,339 3,395 Pennsylvania 3,449 4,631 5,672 6,534 6,587 East No. Central 7.220 9,617 13,050 ,16,795 17.444 Ohio 1 ,998 2,665 3,677 4,507 4,613 Indiana 863 1 ,144 1,483 1,796 1 ,888 Illinois 2,616 3,^77 4,404 5,636 5,810 Michigan 952 1,327 2, 242 3,302 3,4 55 Wisconsin 790 1,004 1 ,245 1,554 1 ,679 West No. Central 2,947 3,874 4.726 5,556 ■5.993 Minnesota 598 850 1,052 1,258 1 ,390 Iowa 572 680 875 979 1 ,084 Missouri 1 , 128 1,399 1,587 1 ,859 1 ,961 North Dakota 23 63 88 113 132 South Dakota 4i 77 102 131 158 Nebraska 253 311 405 486 514 Kansas 331 494 616 730 754 (Continued) 319 TABLE A-1.--(continued) 1900 1910 1920 1930 1940 South. Atlantic 2.233 3,092 4,336 5,6 98 6. 922 Delaware 86 97 121 123 139 Maryland 591 658 869 975 1 ,080 Dist. of Columbia 279 331 438 487 663 Virginia 340 477 674 786 945 West Virginia 125 228 369 492 534 North Carolina 187 318 490 810 974 South Carolina 171 225 294 371 466 Georgia 3 46 539 728 895 1 ,074 Florida 107 219 354 760 1 ,046 East So. Central 1.131 1,574 1 j.994 2.779 3., 1 65 Kentucky 468 555 634 799 849 Tennessee 327 44l 611 897 1 ,027 Alabama 217 370 509 744 856 Mississippi 120 207 240 339 433 West So. Central JU.Q5Z 1 .957 4.427 5,203 Arkansas 1 12 203 290 383 432 Louisiana 366 497 628 834 980 Oklahoma 58 320 538 822 880 Texas 521 938 1 ,513 2,389 2,911 Mountain 541 £48 1.218 ,1,458 1,772 Montana 85 133 172 181 212 Idaho 10 70 1 19 130 177 Wyoming 27 43 57 70 94 Colorado 261 405 453 520 591 New Mexico 27 47 65 107 176 Arizona 19 63 121 150 174 Utah 105 173 216 266 305 Nevada 7 14 15 34 43 (Continued) 320 TABLE A-1.— (continued) 1900 1910 1920 1930 1940 Pacific Washington Oregon California 1 . 122 21 1 133 778 2,382 606 307 1 ,470 3,460 74 3 390 2,327 883 490 4,161 ^, 35.6 922 532 4,902 Sources: Data for 1900 and 1910: U. S. Bureau of the Census, Statistical Abstract of the United States, 1930 (Washington, 5T C. : U. S. Government Printing Office, 1930), Table 39. Data for 1920 through 1940: U. S. Bureau of the Census, Statistical Abstract of the United States. 1949 (Washington, Dl C. : U. S. Government Printing Office, 19^9)» Table 48. 321 TABLE A-2.— Urban Population of the United States, Regions, and States, Census Years 1950 and 1960 (Urban Population in Thousands of Persons) 1950 1960 (New Definition) 1950 1960 United States 90,128 113,056 96,847 125,284 New England . 6.970 7.888 7, 102 Maine 375 387 472 497 New Hampshire 312 363 307 354- Vermont 138 144 138 150 Mas sachusetts 4,066 4,471 3,959 4,303 Rhode Island 689 773 667 743 Connecticut 1 ,391 1 ,750 1 ,559 1 ,986 Middle Atlantic 22.811 24,654 24.272 27.810 New York 11,907 12,221 12,682 14,333 New Jersey 3,918 5,013 4, 186 5,374 Pennsylvania 6,985 7,420 7,403 8, 103 East No, Central 20,166 .24,377 21,286 26.439 Ohio 5,346 6,538 5,578 7 , 124 Indiana 2,217 2,650 2,357 2,910 Illinois 6,487 7,651 6,759 8,141 Michigan 4,166 5,086 ^,503 5,741 Wisconsin 1 ,949 2,452 1 ,988 2,523 West No. Central 1*918 8.617 7,505 9,047 Minnesota 1 ,607 2 ,081 1 ,625 2,121 Iowa 1 ,229 1 ,440 1 ,251 1 ,463 Missouri 2, 290 2,647 2,433 2,878 North Dakota 165 222 165 223 South Dakota 216 265 217 267 Nebraska 607 734 622 7 66 Kansas 903 1 ,229 993 1 ,329 South Atlantic 9,276 ..12,755 10.391 14,853 Delaware 148 145 199 293 Maryland 1 ,426 1,742 1, 61 6 2,254 Dist, of Columbia 802 764 802 764 Virginia 1 ,375 1 ,932 1 ,560 2,205 West Virginia 641 666 694 71 1 North Carolina 1 ,238 1 ,647 1 ,368 1 ,802 South Carolina 653 818 778 981 Georgia 1 ,426 1 ,963 1 ,559 2, 180 Florida 1 ,567 3,078 1,814 3,663 (Continued) 322 TABLE A-2 . (continued) 1950 1960 (New Definition) 1950 1960 East So. Central 4.080 5,253 4j 485 5,834 Kentucky 986 1 ,145 1 ,084 1,3 53 Tennessee 1 ,264 1 ,632 1 ,^53 1 ,865 Alabama 1 ,228 1 ,689 1 ,341 1,795 Mississippi 602 788 607 821 West So. Central 7.717 J10*258 8.080 11.479 Arkansas 617 743 631 765 Louisiana 1 ,380 1 ,832 1 ,472 2,061 Oklahoma 1 ,107 1 ,420 1 , 139 1 ,465 Texas 4,613 6,963 4,838 7,188 Mountain 2.497 4,145 2,786 4.600 Montana 253 312 258 338 Idaho 234 276 253 317 Wyoming 145 188 145 188 Colorado 760 1 ,090 831 1 ,293 New Mexico 315 588 342 625 Arizona 274 910 416 971 Utah 433 592 450 667 Nevada 84 189 92 201 Pacific 14.409 11.241 17.190 Washington 1 ,274 1 ,667 1 ,503 1 ,943 Oregon 732 ^44 819 1 , 100 California 7,209 11,274 8,539 13,577 Alaska 34 86 34 86 Hawaii 3^5 439 345 484 Puerto Rico 895 951 895 1 ,039 Sources: Data for 1950 and 1960 (old definition): U. S. Bureau of the Census, Statistical Abstract of the United States, 1962 (Washingt on, dT C. : U\ sT Government Printing Office, 1962), Table 12. Data for 1950 and i960 (current definition): U. S. Bureau of the Census, Statistical Abstract of the United States. 1968 (Washington. dT C.: U. S. Government Printing Office, 1968), Table 15. 323 TABLE A-3.— Urban Population as a Percentage of the Population of the United States, Regions and States, Census Years 1900 to 1940 Percentage 1900 1910 1920 1930 1940 United States 40.0 45.8 51 .2 56.2 56.5 New England 72.5 76. 3 75-9 77 *3 76. 1 Maine 33.5 35.3 39.0 40.3 40.5 New Hampshire 55.0 59.2 56.5 58.7 57.6 Vermont 22. 1 27.8 31 . 2 33.0 34.3 Massachusetts 91.5 92.8 90.0 90.2 89.4 Rhode Island 95.1 96.7 91.9 92.4 91 .6 Connecticut 59.9 65.6 67.8 70.4 67.8 Middle Atlantic 65.2 71.0 75.4 77-7 76.8 New York 72.9 78.8 82.7 83.6 8 2.8 New Jersey 70.6 75.2 79.9 82.6 81 .6 Pennsylvania 54.7 60.4 65. 1 67.8 66.5 East No. Central 4^.2 52.7 60. 8 66.4 65.5 Ohio 48. 1 55.9 63.8 67.8 66.8 Indiana 34.3 42.4 50.6 55.5 55.1 Illinois 54.3 61.7 67.9 73.9 73.6 Michigan 39.3 47.2 61.1 68.2 65.7 Wisconsin 38.2 43.0 47.3 52.9 53.5 West No. Central 28. 5 33-3 37.7 41 .8 44. 3 Minnesota 34. 1 41.0 44.1 49.0 49.8 Iowa 25. 6 30.6 36.4 39.6 42.7 Missouri 36.3 42.5 46.6 51 .2 51.8 North Dakota 7.3 11.0 13.6 16.6 20.6 South Dakota 10.2 13.1 16.0 18.9 24. 6 Nebraska 23.7 26.1 31 .3 35.3 39. 1 Kansas 22.5 29.2 34.8 38.8 41.9 South Atlantic 21 .4 23.4 31 .0 36.1 38.8 Delaware 46.4 48.0 54.2 51 .7 52.3 Maryland 49.8 50.8 60.0 59.8 59.3 Dist. of Columbia 100.0 100.0 100.0 100.0 100.0 Virginia 18.3 23.1 29.2 32.4 35.3 West Virginia 13.1 18.7 25.2 28.4 28. 1 North Carolina 9.9 14.4 19.2 25.5 27.3 South Carolina 12.8 14.8 17.5 21.3 24.5 Georgia 15.6 20.6 25. 1 30.8 34.4 Florida 20.3 29.1 36.5 51 .7 55. 1 (Continued) 324 TABLE A-3.— (continued) 1 900 Percentage 1910 1920 1930 1940 East So. Central 15.0 18„_7 22 .4 28. 1 29.4 Kentucky 21.8 24.3 26. 2 30.6 29 .8 Tennessee 16.2 20. 2 26 . 1 34.3 35.2 Alabama 11.9 17.3 21.7 28. 1 30. 2 Mi s s i s s ippi 7.7 11.5 13.4 16.9 19.8 West So. Central 16.2 22,3. 29.0 36.4 35?.8 Arkansas 8.5 12.9 16.6 20. 6 22 . 2 Louisiana 26.5 30.0 34.9 39.7 41.5 Oklahoma 7.4 19.3 26.5 34.3 37.6 Texas 17-1 24. 1 32 .4 41 .0 45.4 Mountain 32.3. 36.0 36.5 39.4 42.7 Montana 34.7 35.5 31 .3 33.7 37.8 Idaho 6.2 21.5 27.6 29. 1 33-7 Wyoming 28.8 29.6 29.4 31.1 37.3 Colorado 48.3 50.7 48. 2 50.2 52.6 New Mexico 1 4.0 14.2 18.0 25.2 33.2 Arizona 15.9 31.0 36. 1 34.4 34.8 Utah 38. 1 46.3 48.0 52.4 55.5 Nevada 17.0 16.3 19.7 37.8 39.3 Pacific 46.4 56.8 62.2 §7 *.5, 65., 3 Wa shingt on 40.8 53.0 54.8 56.6 53. 1 Oregon 32. 2 45.6 49.8 51.3 48.8 California 52.4 61.8 67.9 73.3 71.0 Sources: Data for 1900 and 1910: U. S. Bureau of the Census, Statistical Abstract of the United States, 1930 (Vashington, D. C.: U. S. Government Printing Office, 1930), Table 39. Data for 1920 through 1940: U. S. Bureau of the Census, Statistical Abstract of the United States. 1949 (Washington, EL C.: U. S. Government Printing Office, 1949)* Table 48. 325 TABLE A-4.— Urban Population as a Percentage of the Population of the United States, Regions and States, Census Years 1950 and i960 (New Definition) 1950 1960 1950 1960 United States 59.6 63.O 64.0 69.9 New England 74.8 75.1 7 6.2 76.4 Maine 41.0 39.9 51 .7 51 .3 New Hampshire 58.5 59.8 57.5 58.3 Vermont 36.5 37.0 36.4 38.5 Massachusetts 86.7 86.8 84.4 83.6 Rhode Island 87.0 89.9 84.3 86,4 Connecticut 69.3 69.O 77.6 78.3 Middle Atlantic 75.6 71 .8 80. 5 81 .4 New York 80.3 72.8 85.5 85.4 New Jersey 81.0 82.6 86.6 88.6 Pennsylvania 66.5 65.6 70.5 71 .6 East No. Central 66-3 67.3 69.7 73-0 Ohio 67.3 67.4 70.2 73.4 Indiana 56.4 56. 8 59.9 62.4 Illinois 74.5 75.9 77.6 8O .7 Michigan 65.4 65.O 70.7 73.4 Wisconsin 56.7 62. 1 57.9 63.8 West No. Central 49.9 36.0 52.0 58.8 Minnesota 53.9 61 .0 5^.5 62. 1 Iowa 46.9 52.2 ^7.7 53. 1 Mis s ouri 57.9 61 .3 61 .5 66.6 North Dakota 26.6 35. 1 26.6 35.2 South Dakota 33. 1 39.0 33.2 39.3 Nebraska 45.8 5 2.0 46. 9 5^.3 Kansas 47.4 56.4 52. 1 61 .0 South Atlantic 43.8 49. 1 49. 1 57.2 Delaware 46.5 32.6 62. 6 65.6 Maryland 60.9 56.2 69 .0 72.7 Dist. of Columbia 100.0 100.0 100.0 100.0 Virginia 41 .4 48 .7 47.0 55.8 West Virginia 32.0 35.8 3 4.6 38.2 North Carolina 30.5 36.2 33.7 39.5 South Carolina 30.8 3 4.3 36.7 4i .2 Georgia 41.4 49.8 ^5.3 55.3 Florida 56.5 62.2 65.5 7^.0 (Continued) 326 TABLE A-4.--(continued) 1950 1960 (New Definition) 1950 1960 East So. Central 35.* 5. 43.6 35LO - 3 - * 00 - 3 - Kentucky 33.5 37-7 36.8 44.5 Tennessee 38.4 45.7 44.1 52.3 Alabama 4o. 1 51 .7 43.8 55-0 Mis sis sippi 27.6 36.2 27.9 37.7 West So. Central 53-1 64.6 55.6 67.7 Arkansas 32.3 41 .6 33.0 42.8 Louisiana 51.4 56.2 54.8 63.3 Oklahoma 49 .6 61 .0 51 .0 62.9 Texas 59.8 72.7 62. 7 75.0 Mountain 49 . 2 60. 5 54.9 67. 1 Montana 42.8 46.3 43.7 50.2 Idaho 39.7 41.4 42.9 47.5 Wyoming 49.8 56.8 49.8 56.8 Colorado 57.4 62.1 62 .7 73.7 New Mexico 46.3 61 .8 50.2 65.7 Arizona 36.5 69.9 55.5 74,5 Utah 62.8 66.5 65.3 74.9 Nevada 52.5 66 . 3 57.. 2 70.4 Pacific £3.*5. 68.0 74.4 81.1 Washington 53.6 58.4 63 .2 68. 1 Oregon 48.1 53-4 53.9 62.2 California 68. 1 71.7 80.7 86.4 Alaska 26 .4 37.9 26.6 37.9 Hawaii 69.O 69.3 69.0 76.5 Puerto Rico 40.5 40.5 40.5 44.2 Sources: Data for 1950 and i960 (old definition): U. S. Bureau of the Census, Statistical Abstract of the United States, 1962 (Washington, D. C. : U. S. Government Printing Office, 1962), Table 12. Data for 1950 and 1960 (current definition) : U. S. Bureau of* the Census, Statistical Abstract of* the United States. 1968 (Wa shington, EL C. : EL £L Govern- ment Printing Office, 1968), Table 15. 327 TABLE A-5.--Number of* Urban Places in the United States by Population of1 Place, Census Years 1790 to 1960 Number of Urban Places Population of Place 1790 1800 1810 1820 1830 1,000,000 or more 500.000 to 1,000,000 250.000 to 500,000 100.000 to 250,000 50.000 to 100,000 1 2 1 2 1 3 25,000 to 50,000 2 2 2 2 3 10,000 to 25,000 3 3 7 8 16 5,000 to 10,000 7 15 17 22 33 2,500 to 5,000 12 12 18 26 34 24 33 46 61 90 1840 1850 1860 1870 1880 1,000,000 or more 500,000 to 1,000,000 1 2 2 1 3 250,000 to 500,000 1 1 5 4 100,000 to 250,000 2 5 6 7 12 50,000 to 100,000 2 4 7 1 1 15 25,000 to 50,000 7 16 19 27 42 10,000 to 25,000 25 36 58 116 146 5,000 to 10,000 48 85 136 186 249 2,500 to 5,000 46 89 1 63 309 467 131 236 392 663 939 1890 1900 1910 1920 1930 1,000,000 or more 3 3 3 3 5 500,000 to 1,000,000 1 3 5 9 8 250,000 to 500,000 7 9 11 13 24 100,000 to 250,000 17 23 31 43 56 50,000 to 100,000 30 40 59 76 98 25,000 to 50,000 66 82 119 143 185 10,000 to 25,000 230 280 369 465 606 5,000 to 10,000 340 465 605 715 851 2,500 to 5,000 654 832 1,060 1,255 1 . 332 1 ,348 1 ,737 2,2 62 2,722 3,165 (Continued) 328 TABLE A-5«— (continued) Population of Place Number of Urban Places 1940 1950 1 960 (New Definition) 1950 I960 1,000,000 or more 5 5 5 5 5 500,000 to 1,000,000 9 13 16 13 16 250,000 to 500,000 23 23 30 23 30 100,000 to 250,000 55 67 80 65 81 50,000 to 100,000 107 129 203 126 201 25,000 to 50,000 213 283 427 252 432 10,000 to 25,000 665 831 1 , 146 778 1 , 134 5,000 to 10,000 965 1 , 129 1 ,326 1 ,176 1 ,394 2,500 to 5,000 1 ,422 1 ,574 1 ,789 1 ,846 2, 152 Less than 2,500 457 596 3,464 4,054 5,022 4,741 6,041 Sources: Data for 1790 through. 1940: U. S. Bureau of the Census, Historical Statistics of the United States. Colonial Times to 19 57 (Washingt on, C . : XL s"I Government Printing Office, i960), Series A 181-191. Data for 1950 and 1960: U. S. Bureau of the Census, Statistical Abstract of the United States, 1962 (Wa shingt on, d" I C. : U. S. Government Printing Office, 1962), Table 13. 329 TABLE A-6,— Percentage of United States Population in Urban Places by Population of Place, Census Years 1790 to i960 Percentage of U. S. Population Population of Places 1790 1800 1810 1820 1830 1,000,000 or more 500.000 to 1,000,000 250.000 to 500,000 100.000 to 250,000 50.000 to 100,000 1 . 1 2.1 1.3 1 .3 1.6 1.7 25,000 to 50,000 1 .6 1.3 1 . 1 .7 .8 10,000 to 25,000 1 .2 1 .0 1.5 1.3 1.9 5,000 to 10,000 1 .2 1.8 1.6 1 .6 1 .8 2,500 to 5,000 1 . 1 .9 1 .0 1 .0 1 .0 Total Urban 5.1 6.1 7.3 7.2 00 • 00 1 840 1850 1860 1870 1880 1,000,000 or more 500,000 to 1,000,000 2.2 4.4 4.1 2.4 3.8 250,000 to 500,000 1.8 • • .8 3.8 2.6 100,000 to 250,000 1 .2 2.8 3.2 2.5 3.6 50,000 to 100,000 1 . 1 1 .2 1 .4 1.9 1.9 25,000 to 50,000 1 .4 2.6 2.1 2.3 2.9 10,000 to 25,000 2.4 2.4 2.8 4.3 4.4 5,000 to 10,000 1 .9 ' 2.6 3.1 3.2 3.4 2,500 to 5,000 1 .0 1 .4 1.9 2.7 3.2 Total Urban 10.8 15.3 19.8 24.9 28.2 1890 1900 1910 1920 1930 1,000,000 or more 5.8 8.5 9.2 9.6 12.3 500,000 to 1,000,000 1.3 2.2 3.3 5.9 4.7 250,000 to 500,000 3-9 3.8 4.3 4.3 6.5 100,000 to 250,000 4.4 4.3 5.3 6.2 6.1 50,000 to 100,000 3.2 3.6 4.5 5.0 5.3 25,000 to 50,000 3.6 3.7 4.4 4.8 5.2 10,000 to 25,000 5.5 5.7 6.0 6.7 7.4 5,000 to 10,000 3.8 4.2 4.6 4.7 4.8 2,500 to 5,000 3.6 3.8 4.1 4.1 3.8 Total Urban 35. 1 39.7 45.7 51.2 56.2 (Continued) 330 TABLE A-6.— (continued) Population of Place Percentage of U. S. Population 1 940 1950 ( n. i960 ew Definition) 1950 i960 1,000,000 or more 12, 1 11.5 9.8 11.5 9.8 500,000 to 1,000,000 4.9 6,1 6.2 6.1 6.2 250,000 to 500,000 5.9 5.5 6.0 5.5 6.0 100,000 to 250,000 5.9 6.5 6.4 6.3 6.5 50,000 to 100,000 5.6 6.1 7.8 5.9 7.7 25,000 to 50,000 5.6 6.6 8.2 5.8 8.3 10,000 to 25,000 7.6 8.5 9.9 7.9 9.8 5,000 to 10,000 5.1 5.2 5.2 5.4 5.5 2,500 to 5,000 3.8 3.7 3.5 4.3 4.2 Less than 2,500 0.4 0.4 Unincorporated parts of urbanized areas 4.9 5.5 Total Urban 56.5 59.6 63.O 64.0 69.9 Sources: Data for 1790 to 1900: U. S. Bureau of the Census, Historical Statistics of the United States, Colonial Time s to 1957 (Wa shingt on , IK C. : IK s " I Government Printing Office, i960), Series A 20 and A 195-205. Data for 1910 to 1960: U. S. Bureau of the Census, Statistical Abstract of the United States, 1 9 6 2 (Washington,IKC.: U. S. Government Printing Office, 1962), Table 13- TABLE A-7.--Population of Standard Consolidated Areas and the Fort^f Largest Standard Metropplitan Statistical Areas in i960 and Their Central Cities, Census Years 1900 to i960 (Population in Thousands of Persons) Standard Consolidated Area 1900 1910 1920 1930 1940 1950 1960 New York, N. Y. - Northwestern N. J. 5,049 7,049 8,491 10,859 11,661 12,912 14,759 Central Cities 3,890 5,382 6,333 7,689 8,186 8,630 8,463 New York, N. Y. 3,437 4,767 5,620 6,930 7,455 7,892 7,782 Jersey City, N. J. 206 268 298 317 301 299 276 Newark, N. J, Percentage Urban 246 347 415 442 430 (93.4) 439 (96.3) 405 (96.9) Chicago, 111. - Northwestern Ind. 6,794 Central Cities • • • • • • • • • * » # 3,634 3,897 3,898 Chicago, 111. 1,699 2, 185 2,702 3,376 3,397 3,621 3,550 Gary, Ind. 112 134 178 Hammond, Ind. 70 88 112 E. Chicago, Ind. 55 54 58 Percentage Urban (92,2) (Continued) TABLE A-7(continued) Standard Metropolitan Statistical Areas 1900 1910 1920 1930 1940 1950 1960 New York, N. Y. Central City- Percent age Urban 3,437 4,767 5,620 6,930 7,455 7,892 10,695 7,782 (97.4) Chicago, 111. Central City Percentage Urban 2,093 1 ,699 2,753 2,185 3,522 2,702 4,676 3,376 4,826 3,397 (93.7) 5,495 3,621 (95.0 6,221 3,550 (95.1) Los Angeles - Long Beach, Cal. Central Cities Los Angeles Logg Beach Percentage Urban 190 102 539 319 998 577 2,327 1,238 2,916 1 ,668 1,504 164 (84.0) 4,368 2,221 1,970 251 (96.0) 6,039 3,823 2,479 344 (98.8) Philadelphia, Pa. - N, J, Central City Percentage Urban 1 ,892 1 ,294 2,268 1,549 2,714 1,824 3,137 1,951 3,200 1,931 (84.1) 3,671 2,072 (87.2) 4,343 2,003 (89.7) Detroit, Mich. Central City Percentage Urban 427 286 614 466 1,306 994 2,177 1,569 2,377 1,623 (89.2) 3,016 1,850 (92.0) 3,762 1,670 (94.7) (Continued) TABLE A-7(continued) Standard Metropolitan Statistical Areas 1900 1910 1920 1930 1940 1950 1960 San Francisco - Oakland, Cal, Central Cities San Francisco Oakland Percentage Urban 543 410 343 67 774 1 567 417 150 ,009 723 507 216 1,348 918 634 284 1,462 937 635 302 (87.7) 2,241 1 , 160 ’ 775 385 (92.0) 2,649 1 ,208 740 368 (95.5) Boston, Mass. Central City- Percent age Urban • • « 561 1 • • • 671 748 • • • 781 2,178 771 ' (97.5) 2,370 801 • • • 2,595 697 (93.9) Pittsburg, Pa. Central City- Percent age Urban 1,084 452 1,472 1 534 ,760 588 2,023 670 2,083 672 (73.2) 2,213 677 (78.9) 2,405 6o4 (81.8) St. Louis, Mo. - 111. Central City- Percent age Urban 801 575 1,004 1 687 , 140 773 1,360 822 1,432 816 (81.3) 1,681 857 (89.6) 2,105 750 (87.5) Washington, D. C. - Md. -Va. Central City Percentage Urban 379 279 445 331 572 438 672 487 968 663 (80.8) 1,464 802 (88.7) 2,002 764 (91.6) Cleveland, Ohio Central City Percentage Urban 461 382 660 561 972 797 1,243 900 1,267 878 (95.3) 1,466 915 (96.0) 1,909 876 (94.0) (Continued) V j J u TABLE A-7. — (c ont inue d) Standard Metropolitan Statistical Areas 1900 1910 1920 1930 1940 1950 i960 Baltimore, Md. 639 720 852 985 1,083 1,337 1,727 Central City- 509 558 734 805 859 950 939 Percent age Urban (83.2) (88.0) (85.0) Newark, N. J. 1,689 Central City 246 3^7 415 442 430 439 405 Percentage Urban (9 5.7) Minneapolis - St. Paul, Minn. 432 595 705 858 941 1,117 1,482 Central Cities 366 516 615 7 36 780 833 796 Minneapolis 203 301 381 464 492 522 483 St. Paul 163 215 235 272 288 311 313 Percentage Urban (90.6) (89.4) (94.3) Houston, Texas 64 116 187 359 529 807 1,418 Central City 4 5 79 138 292 385 596 938 Percentage Urban (77.7) (90.0) (88.8) Buffalo, N. Y. 509 621 753 912 958 1,089 1,307 Central City 352 424 507 573 576 580 533 Percentage Urban (82.4) (86.1) (85.1) Cincinnati, 0. - Ky. - Ind. 527 590 629 756 787 904 1,268 Central City 326 364 401 451 456 504 503 Percentage Urban (85.7) (91.1) (82.1) (Continued) uj - F r TABLE A-7 •--( continued.) Standard Metropolitan Statistical Areas 1900 1910 1920 1930 1940 1950 i960 330 433 539 725 767 871 1,233 285 374 457 578 587 637 741 (92.0) (94.9) (94.5) 1,187 140 139 144 (99.1) 110 285 389 464 505 733 1,107 81 237 315 366 368 468 557 (75.7) (86.9) (84.3) 305 422 529 666 68 7 814 1,093 164 248 324 400 399 457 476 (80.4) (88.5) (88.2) 83 136 211 326 399 615 1,084 43 92 159 260 295 434 680 (80.2) (89.8) (92.1) 35 62 1 12 210 289 557 1,033 18 40 74 148 203 335 573 (82.6) (82.0) (88.9) 179 252 326 441 518 672 1,017 90 155 201 270 303 331 487 (70.5) (78.6) (82.3) (Continued) 0 U) Ui Milwaukee, Wis. Central City Percentage Urban Patterson - Clifton - Passaic, N. J. Central City Percentage Urban Seattle - Everett Wash, Central City Percentage Urban Kansas City, Mo, - Kan, Central City Percentage Urban Dallas, Texas Central City Percentage Urban San Diego, Cal. Central City Percentage Urban Atlanta, Ga. Central City Percentage Urban TABLE A-7(continued) Standard Metropolitan Statistical Areas 1900 1910 1920 1930 1940 1950 1960 Miami, Fla. 5 12 43 143 268 495 935 Central City « • • 5 30 111 172 249 292 Percentage Urban (80.5) (94.1) (95.6) Denver, Colo. 162 247 299 353 408 564 929 Central City 134 213 236 288 322 416 494 Percentage Urban (84.1) (90.7) (93.3) Xndianap o1i s, Ind. 197 264 348 423 461 552 917 Central City 169 234 314 364 387 427 476 Percentage Urban (84.8) (91.0) (78.4) New Orleans, La. 307 363 414 505 552 685 907 Central City 287 339 387 459 495 570 62 8 Percentage Urban (92.4) (97.1) (94.6) Portland, Ore. - Wash. 151 304 373 455 501 705 822 Central City 90 207 258 302 305 374 373 Percentage Urban (67.5) (75.2) (82.0) Providence - Pawtucket - Warwick, R. I. - Mass. 372 478 337 616 634 682 821 Central City 176 224 238 253 254 249 207 Percentage Urban (95.7) • • • (87.5) (Continued) o\ TABLE A-7.--(continued) Standard Metropolitan Statistical Areas 1900 1910 1920 1930 1940 1950 1960 San Bernardino - Riverside - Ontario, Cal. 28 57 73 134 161 282 810 Central Cities 79 1 10 223 San Bernardino 6 13 19 37 44 63 92 Riverside 35 47 84 Ontario 47 Percentage Urban (59.6) (63.1) (71.8) Tampa - St, Petersburg, Fla. 36 78 117 216 272 409 772 Central Cities 16 42 66 142 169 221 456 Tampa 16 38 52 101 108 125 275 St. Petersburg • • • 4 14 4o 61 97 181 Percentage Urban (69.9) (79.7) (85.3) Columbus, Ohio 164 222 284 361 389 503 755 Central City 126 182 237 291 306 376 471 Percentage Urban (85.0) (87.8) (86.6) Rochester, N. Y. 218 283 352 424 438 488 733 Central City 163 218 296 328 325 33 2 319 Percentage Urban (82.9) (86.0) (76.2) Dayton, Ohio 162 193 241 307 331 457 727 Central City 85 117 153 201 211 244 262 Percentage Urban (71.6) (80.7) (80.4) f (Continued) 337 TABLE A-7»-“(continued) Standard Metropolitan Statistical Areas 1900 1910 1920 1930 1940 1950 1960 Louisville, Ky. - Ind. 295 323 346 421 451 577 725 Central City 205 224 235 308 319 369 391 Percentage Urban (78.8) (82.8) (85.7) San Antonio, Texas 69 120 202 293 338 500 716 Central City 53 97 161 232 254 408 588 Percentage Urban (76.8) (89.8) (91.6) Anaheim - Santa Ana - Garden Grove, Cal. 704 Central Cities 32 46 288 Anaheim 104 Santa Ana 32 46 100 Garden Grove 84 Percentage Urban (95.9) Memphis, Tenn. - Ark. 154 191 223 306 358 482 675 Central City 102 131 162 253 293 396 498 Percentage Urban (81.8) (85.1) (84.5) (Continued) VJ 00 TABLE A-7.— (continued) Standard Metropolitan Statistical Areas 1900 1910 1920 1930 1940 1950 1960 Phoenix, Ariz. 20 3k 90 151 186 332 664 Central City 6 11 29 48 65 107 439 Percentage Urban (43.2) (71.7) (86.5) Included Orange County until i960. Included in the Los Angeles-Long Beach. SMSA until i960. Sources: D. J. Bogue, Population Growth in Standard Metropolitan Areas, 1900 - 1950 (Washington, D. C.: Housing and Home Finance Agency, December, 1953)» Appendix Table 1. U. S* Bureau of the Census, County and City Data Book (Washington, D, C, : U. S. Government Printing Office, 19^-9> 1956, and 1967). VO TABLE A-8.--Land Area and Population Density of Standard Consolidated Areas and the Forty Largest Standard Metropolitan Statistical Areas in 1960 and Their Central Cities, Census Years 1940 to i960 Land Area Population Density Standard (Square Miles) (Persons per Square Mile) Consolidated Areas IjhO 1950 i960 1940 1950 i960 New York, N, Y. - Northwestern N, J. 3,924 3,939 3,930 2,972 3,278 3,756 Central Cities 337 352 354 24,291 24,517 23,907 New York, N. Y. 299 315 315 24,933 25,046 24,697 Jersey City, N. J. 14 13 15 21,061 23,001 18,285 Newark, N. J. 24 24 24 18,220 18,592 17,170 Chicago, 111, - Northwestern Ind. • • • • • • 4,657 • • f • • • 1,459 Central Cities 281 284 300 12,932 13,722 12,993 Chicago, 111. 207 208 224 16,434 17,450 15,836 Gary, Ind. 4o 42 41 2,772 3,219 4,403 Hammond, Ind. 24 24 23 2,987 3,727 4,921 E. Chicago, Ind. 10 10 12 5,254 5,218 4,887 (Continued) ■ ( = - o TABLE A-8continued.) Standard Metropolitan Statistical Areas Land Area (Square Miles) 1940 1950 196O Population Density (Persons per Square Mile) 1940 1950 i960 New York, N. Y. Central City 299 315 Chicago, 111, Central City 3,617 207 3,617 208 Los Angeles - Long Beach, Cal, Central Cities Los Angeles Long Beach 4,853 479 448 31 4,853 486 451 35 Philadelphia, Pa. - N, J. Central City 3,550 127 3,550 127 Detroit, Mich. Central City 1,965 138 1,965 i4o San Francisco - Oakland, Cal. Central Cities San Francisco Oakland 3,314 98 45 53 3,314 98 45 53 2,136 • • • 1 • • 5,007 315 24,933 25,046 24,697 3,720 1,334 1,519 1,672 224 16,434 17,450 15,836 4,069 601 900 1,484 501 • t • • • • « • • 455 3,355 4,370 5,451 46 5,290 7,227 7,498 3,553 901 1,034 1 ,222 127 15,181 16,286 15,743 1,952 1 ,210 1,535 1,927 140 11,769 13,249 11,964 2,478 441 676 1,069 98 • • • • • « • • « 45 14,238 17,385 15,553 53 5,720 7,256 6,935 (Continued) • P - TABLE A-8. — (c ont inue d) Standard Metropolitan Statistical Areas Land Area (Square Miles) 19^0 1950 1960 Population Density (Persons per Square Mile) 1940 1950 1960 Boston, Mass. Central City Pittsburg, Penn. Central City St. Louis, Mo. - 111 Central City Washington, D. C, - Central City Cleveland, Ohio Central City Baltimore, Md. Central City Newark, N, J, Central City Minneapolis - St. Paul, Minn. Central Cities Minneapolis St. Paul 721 770 986 3,020 3,078 46 48 48 16,725 16,767 3,053 3,P53 3,049 682 725 52 54 54 12,898 12,487 2,520 2,520 4,119 568 667 61 61 61 13,377 14,046 Md. - Ya,1,488 1,488 1,485 650 984 61 61 61 10,798 13,000 688 688 1,519 1,842 2,130 73 75 81 12,011 12,197 1,106 1,106 1,802 980 1,209 79 79 79 10,915 12,067 • * • • • • 701 • • # « • • 24 24 24 18,220 18,592 1,721 1,721 2,107 547 649 106 106 109 • • • • * • 54 54 57 9,145 9,697 52 52 52! 5,517 5,965 (Continued) 2,632 14,586 789 11,1?1 511 12,296 1, 3^8 12,442 1,257 10,789 958 11,886 2,410 17,170 703 8,546 6,004 ■ p* ro TABLE A-8. --(continued) Land Area Population Density Standard Metropolitan (Square Miles) (Persons per Square Mile) Statistical Areas 1940 1950 i960 1940 1950 i960 Houston, Texas 1,747 1,730 6, 286 303 466 226 Central City 73 160 328 5,288 3,726 2,860 Buffalo, N. Y. 1,587 1,587 1 ,591 604 686 821 Central City 39 39 39 14,619 14,724 13,522 Cincinnati, 0. - Ky. - Ind. 731 730 2, 150 1,077 1,239 590 Central City 72 75 77 6,298 6,711 6,501 Milwaukee, Vis. 239 239 1,028 3,209 3,645 1,199 Central City 43 50 - 91 13,525 12,748 8,137 Patterson, Clifton - Passaic, N. J. • • • • • t 427 • • • • • • 2,780 Central City 8 8 9 17,241 17,202 16,705 Seattle - Everett, Wash. 2, 136 2,134 4,229 236 34 3 262 Central City 68 71 88 5,372 6,6o4 . 6,295 Kansas City, Mo, - Kan, 1,643 1,643 2,767 418 496 395 Central City 59 81 130 6,809 5,665 3,664 Dallas, Texas 893 893 3,603 446 688 301 Central City 41 112 280 7,266 3,879 2,428 (Continued) CJ ■ p- TABLE A-8,— (continued) Land Area Population Density- Standard Metropolitan (Square Miles) (Persons per Square Mile) Statistical Areas 1940 1950 i960 1940 1950 i960 San Diego, Cal. Central City Atlanta, Ga. Central City Miami, Fla. Central City Denver Colo. Central City Indianap o1i s, Ind. Central City New Orleans, La. Central City Portland, Ore. - Wash. Central City Providence -Pawtucket - Warwick, R. I. - Mass, Central City 4,258 4,258 4,262 95 99 192 1, i4o 1,138 1,727 35 37 128 2,054 2,054 2,042 30 34 34 2,918 2,918 3,662 58 67 71 402 402 2,653 54 55 71 1,118 1,118 1,975 199 199 199 3,663 3,663 3,650 64 64 67 494 494 680 18 18 18 (Continued) 68 2,130 131 3,36 4 242 2,979 454 8,703 590 8,979 589 3,802 130 5,682 241 7,289 458 8,529 140 5,561 193 6,224 254 6,956 1,147 7,220 1,373 7,739 346 6,689 494 2,482 613 2,861 459 3,157 137 4,803 192 5,829 225 5,546 1,370 14,162 1,492 13,892 1,208 11,464 TABLE A-8.“-(continued) Land Area Population Density- Standard Metropolitan (Square Miles) (Persons per Square Mile) Statistical Areas 1940 1950 1960 1940 1950 i960 San Bernardino - Riverside Ontario, Cal, 20,131 27,310 27,295 8 17 30 Central Cities 57 59 82 1,386 1,864 2,720 San Bernardino 18 20 25 2,372 3,234 3,648 Riverside 39 39 39 887 1,196 2,162 Ontario • • • • •1 18 • • • • • • 2,634 Tampa - St. Petersburg, Pla. 1,304 1,304 1,303 209 314 593 Central Cities 71 71 119 2,380 3,113 3,832 Tampa 19 19 69 5,705 6,562 3,985 St. Petersburg 52 52 53 1,165 1,853 3,434 Columbus, Ohio 538 538 1,494 722 936 505 Central City 39 39 89 7,846 9,541 5,296 Rochester, N. Y, 673 673 2,316 631 725 316 Central City 35 36 36 9,339 9,236 8,753 Dayton, Ohio 881 881 1,708 376 519 426 Central City 24 25 34 8,891 9,755 7,693 Louisville, Ky. - Ind. 908 908 908 497 635 799 Central City 38 40 57 8,417 9,251 6,841 (Continued) • p - V j T TABLE A-8(continued) Land Area Population Density Standard Metropolitan (Square Miles) (Persons per Square Mile) Statistical Areas 1940 1950 i960 1940 1950 i960 San Antonio, Texas 1 ,247 1,247 1,960 271 401 365 Central City 36 70 160 7,115 5,877 3,662 Anaheim - Santa Ana - Garden Grove, Cal, * « • « « 1 782 « • « l i t 900 Central Cities 10 11 . 62 3,040 4,216 4,645 Anaheim • • • • • • 25 « • • • * • 4,118 Santa Ana 10 11 21 3,o4o 4,216 4,801 Garden Grove • • • • • • 16 • t • • • • 5,232 Memphis, Tenn. - Ark. 751 751 1,363 477 642 495 Central City 46 104 128 6,425 3,800 3,881 Phoenix, Ariz. 9,231 9,226 9,238 20 36 72 Central City 10 17 187 6,701 6,247 2,343 Source: U. S. Bureau of the Census, County and City Data Book. (Washington, D. C.: U. S. Government Printing Office, 1949, 1956, and 1967)* ■ £ - ON TABLE A-9.— Employment by Industry Group, Los Angeles County, 1949 to 1966 (Sheet 1 of 2) (Thousands of Employees) Trans portation Non- Contract Manufac and Public Whole Retail Year agricultural Mining Construction turing Utilities sale Trade 1949 1,346.8 13.4 84.7 376.3 108.1 88.9 247.0 1950 1,415.2 12.8 97.6 414.5 108.5 91 .2 252.3 1951 1,554.5 14,2 103.2 497.9 117.6 100.0 260.1 1952 1,674.3 13.9 102.0 577.3 120,2 103.6 271.6 1953 1,771.5 13.1 113.1 626.1 125.4 109.4 282.6 1954 1,788.0 13.0 110.5 626.6 124.8 111.2 284.9 1955 1,907.2 12.8 117.2 678.6 130.1 118.6 299.3 1956 2,029.9 13.1 122.7 732.1 138.7 127.3 312.1 1957 2,099.1 12.7 113.8 760.1 143.8 134.2 316.6 1958 2,037.7 11.8 107.8 698.7 134.9 132.7 307.0 1959 2,149.7 11.0 113.2 743.9 134.8 140.3 320.6 1960 2,189.3 10.4 109.6 738.7 136.7 146.8 328.6 1961 2,203.5 10.2 106.6 722.6 133.3 148.9 330.3 1962 2,294.8 10.4 113.2 755-9 135.8 151.7 343.0 1963 2,355.5 2,409.1 10.0 119.5 754.3 138.2 156.6 357.3 1964 10.0 122.8 745.7 142.4 160.6 372.8 1965 2,472.9 9.9 112.4 761.0 147.6 164.6 383.5 1966 2,614.8 10.0 108,8 826.2 155.2 170.9 396.9 u • p- TABLE A-9.--(sheet 2 of 2) Year Financ e, Insurance, and Real Estate Services and Miscel- laneous Govern ment Federal Govern ment State Govern ment County Govern ment City Govern ment 19^9 65.9 198.8 163.7 43.0 55.7 23.5 41 .5 1950 71.5 199.7 167.1 4l . 1 59.0 24.9 42.1 1951 73.9 212.7 174.9 47.1 60.1 25.3 42.4 1952 76.0 226.5 183. 2 50.5 62.3 27.6 42.8 1953 81 .5 230.7 189.6 48.8 66.6 28.8 45.4 1954 85.4 236.4 195.2 47.2 71.0 29.7 47.3 1955 93.7 253.6 203.3 47.4 77.1 30.5 48.3 1956 100.2 267.3 216.4 48.7 85.2 32.9 49.6 1957 102.5 285.8 229.6 50.8 92.9 34.6 51.3 1958 103.7 295.0 246.1 52.0 104.1 36.9 53.1 1959 109.7 318.4 257.8 53.2 113.2 37.7 53.7 1960 116.8 331.3 270.4 55.5 120.8 39.5 54.6 1961 120.5 348.2 282.9 55.8 130.6 40.5 56.0 1962 125.9 364.1 294.8 55.7 139.9 42.2 57.0 1963 133.4 382.0 304.2 55.9 146.9 43.3 58.1 1964 140.3 400.9 313.6 55.8 153.0 46.1 58.7 1965 144.3 419.6 330.6 57.5 164.1 48.3 60.1 1966 145.4 447.4 354.0 64.2 178.1 50.5 61.2 Source: U. S. Department of Labor, Bureau of Labor Statistics, Employment and Earnings Statistics for States and Areas, 1939-66 (Washington, D.C. : U. S. Government Printing Office, July, 19^7)• to ■ P - oo 349 TABLE A-10.— Total Personal Income, Los Angeles County, 1940 and 1947 to 1968, Current and Constant Dollars (Total Personal Income in Thousands of Dollars) Year Current Dollars 1957-59 Dollars 19^0 $ 2,430,609 $**«*. 1 947 6,881,687 8,983,926 1948 7,264,796 8,848,716 19^9 7,329,980 8,9^9,915 1950 8,058,611 9,779,868 1951 9,284,448 10,385,289 1952 10,438,596 11,346,300 1953 11,245,996 12,118,530 1954 11,654,122 12,571,868 1955 13,041,688 14,068,703 1956 14,246,321 15,139,555 1957 15,386,772 15,830,012 1958 15,9^2,995 15,847,908 1939 17,334,098 16,960,957 1960 18,071,543 17,359,792 1961 19,037,793 18,062,422 1962 20,3^1,568 19,082,146 1963 21,580,665 19,945,162 1964 22,978,970 20,852,060 1965 24,228,017 21,536,015 1966 26,098,515 22,753,718 1967 28,099,316 23,893,976 1968 28,897,150 23,647,422 Sources: Security Pacific National Bank, Economic Research Department, "Personal Income in the 14 Southern most Counties of California" (September,19, 1969). Consumer Price Index for Los Angeles used to calculate total personal income in constant dollars: U. S. Department of Labor, Bureau of Labor Statistics, "Consumer Price Index, Los Angeles - Long Beach, California" (May, 1968). 350 TABLE A-11.— Personal Income Per Capita, Los Angeles County, 1940 and 19^-7 "to 1968, Current and Constant Dollars Year Current Dollars 1957-59 Dollars 1 940 $ 873 $« • • 19^7 1 ,862 2 ,431 1948 1 ,860 2,266 1949 1 ,805 2,204 1950 1 ,941 2,356 1951 2, 170 2,427 1952 2,331 2,53^ 1953 2,427 2,615 1954 2 , 4o4 2,593 1955 2,592 2,796 1 956 2,726 2,897 1957 2,823 2,904 1958 2,816 2,799 1 959 2,953 2,889 1960 2,991 2,873 1961 3,065 2,908 1962 3,193 2,995 1963 3,306 3,055 1964 3,^29 3,112 1965 3,535 3, 142 1966 3,741 3,262 1967 3,989 3,392 1968 4,068 3,329 Sources: Tables 2 and A-10. Consumer price Index for Los Angeles used to calculate personal income per capita in constant dollars: U. S. Department of Labor, Bureau of Labor Statistics, "Consumer Price Index, Los Angeles - Long Beach, California” (May, 1968). 351 TABLE A-12.— Assessed Valuation and Estimated Market Value of Tangible Property Subject to Local Taxation, Los Angeles County, Selected Years from 1935 to 1967, Current and Constant Dollars (Values in Thousands of Dollars) Year Current Dollars 1957-59 Dollars3- 1935 Assessed Valuation $ 2,346,331 $••••• 19^0 2,485,966 1945 2,978,393 • • • • » 1950 5,348,389 6,611,1 1 1 1955 7,624,209 8,119,498 1956 8,405,735 8,838,838 1957 9,846,084 10,098,548 1958 10,500,536 10,427,543 1959 10,899,880 10,707,151 1960 11,688,344 1 1 ,282,185 1961 12,374,474 11 ,796,448 1962 13,021,946 12,319,722 1963 13,407,831 12,414,658 1964 13,499,903 12,272,639 1965 14,312,915 12,632,758 19 66 15,706,995 13,470,836 1967 16,834,940 14,064,277 1960 Estimated Market Value $49,737,634 $48,009,299 1961 53,109,330 50,628,532 1962 53,368,631 50,490,663 1963 54,503,378 50,466,091 1964 56,249,596 51,366,707 1965 63,052,489 55,650,917 1966 71,721,438 61,510,667 1967 71,638,043 59,847,989 aConsumer Price Index for housing in Los Angeles County -was used to calculate values in constant dollars: U. S. Department of Labor, Bureau of Labor Statistics, "Consumer Price Index, Los Angeles - Long Beach, California" (May, 1968). Source: California, Economic Development Agency, dalifornia Statistical Abstract (1961 to 1968 issues). 352 TABLE A—13•— Assessment Ratio, Los Angeles County, Fiscal Years 1959-60 to 1967-68 Fiscal Year Ending June 30 Assessment Ratioa 1960 23.5 1961 23.3 1962 24. 4 1963 24.6 1964 24.0 1965 22.7 1966 21 .9 1967 23.5 1968 24.7 cL Ratio of assessed value to market value. Source: California, Economic Development Agency, California Statistical Abs&rac t {/I 96 1 to 1 968 ) . 353 TABLE A-1 4.— Gross Value of Stolen Property, Value of Recovered. Property, and Net Value of Stolen Property, United States, 1957 to 1968, Current Dollars (Thousands of Dollars) Gross Value Value of Net Value of Stolen Recovered of Stolen Year Property Property Property 1957 $261,500 $151,800 $109,700 1958 265,700 143,300 122,400 1959 269,000 142,100 126,900 1960 281,300 147,300 134,000 1961 309,500 159,900 149,600 1962 352,800 181,000 171,800 1963 475,100 256,800 218,300 1964 592,500 307,100 285,400 1965 629,700 324,500 305,200 1966 582,300 319,200 263,100 1967 693,800 356,400 337,^00 1968 818,700 408,300 410,400 Source: U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States (Wa shingt on, D. C.: U. S. Government Printing Office, 1957 to 1968 issues). 35^ TABLE A-15.— Average Loss Per Offense and. Total Loss for Crimes Against Property, Cities with. Populations of 25,000 or more, 1957 to 1968, Current Dollars Year Burglary Robbery Larceny- Thef t Auto Theft Average Loss Per Offense 1957 *171 $202 $ 68 $ 859 1958 186 226 73 835 1959 186 233 76 829 1960 183 256 74 830 1961 1 87 266 74 828 1962 192 223 76 8 66 1963 21 1 276 82 927 1964 224 280 84 1 ,048 1965 242 25^ 84 1 ,030 1966 248 256 90 1 ,029 1967 273 261 95 1,017 1968 298 269 100 991 Total National Loss (Billi ons of Dollars) 1957 $ 55,600 $ 9,600 $ 55,700 $151,000 1958 61,4oo 10,900 58,600 13^,800 1959 62,000 10,900 60,300 135,800 1960 66,600 11,400 64,000 139,300 19^1 74,800 12,400 70,700 151,600 1962 84,400 11,400 80,800 176,200 1963 109,200 20,100 103,400 242,400 1964 130,300 22,800 116,900 • • « • 1965 153,600 21,800 120,400 • * # • 1966 162,100 23,000 130,100 • • • • 1967 204,200 29,800 149,000 • * • » 1968 302,500 48,600 197,^00 « • • • Source: U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States (Washington, D. C.: U 0 S. Government Printing Office, 1957 to 1968 issues). TABLE A-16,--Crime Rates by Type of Crime, United States, California, and Los Angeles - Long Beach SMSA, 1958 to 1968 Year Burglary Robbery Larceny Auto Theft Homicide Forcible Rape Aggravated Assault Total 1960 500.5 59.9 United States 282.3 181.6 5.0 9.4 84.9 1,123.4 1961 510.6 58.1 288.9 182.3 4.7 9.2 84.4 1,138.2 1962 526.4 59.^ 308.4 196.0 ^.5 9.3 87.3 1,191.2 1963 566.9 61.5 344.0 214.9 ^•5 9.2 91.0 1,292.0 1964 623.8 67.9 382.6 245.3 4.8 •11.0 104.5 1,439.9 1965 651.0 71.3 408.8 254.4 5.1 11.9 109.5 1,511.9 1966 708.3 8O.3 456.8 284.4 5.6 12.9 118,4 1,666.6 1967 811.5 102.1 529.2 331.0 6.1 13.7 128.0 1,921.7 1968 915.1 131.0 636.O 389.1 6.8 15.5 141.3 2,234.8 1958 785.5 88.5 California 462.4 323.2 3.7 20.7 112.6 1,796.6 1959 718.8 73.8 427.2 286.7 3.3 18.6 107.4 1,635.8 1960 913.3 98.0 494.5 328.1 3.9 18.3 120.2 1,976.5 1961 894.2 90.5 482.6 319.5 3.7 18.5 119.5 1,928.5 1962 93^.1 91.9 516.6 325.7 3.9 17.4 121 . 1 2,010.7 1963 998.9 93.6 562.6 362.2 3.8 17.5 125.7 2,164.2 1964 1,088.7 103.2 650.9 419.1 4.1 20.0 137.6 2,423.5 1965 1,209.6 113.3 712.0 439.6 4.7 21 .2 142.9 2,6^3.5 1966 1,277.4 118,0 782.5 460.7 4.6 23.4 159.1 2,825.7 1967 1,446.0 149.0 901 .2 508.1 5 A 25.0 172.7 3,207.5 1968 1,644.5 192.5 1,075.0 621.4 6.0 29.9 194.6 3,763.8 (Continued) u> Ut Ur Year 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 TABLE A-16.--(continued) A -------- ■ - — - ------------ ---------------- Auto Forcible Aggravated Burglary Robbery Larceny Theft Homicide Rape Assault Total Los Angeles - Long Beach SMSA 1,068.3 122.9 678.9 416.7 4.0 31 .9 185.0 2,507.6 971.0 103.1 582.5 371.9 3.6 28.9 176.0 2,237.0 1,200.9 143.9 657.3 444.3 4.4 29.0 199.1 2,678.9 1,195.4 135.9 643.8 447.4 4.2 29.3 201 .3 2,657.2 1 ,208.6 136.4 665.1 443.3 4.5 26.0 197.6 2,681.5 1,305.4 153.0 733.3 493.5 4.7 26.7 218.9 2,935.4 1,400.8 171 .2 838.7 587.7 4.8 29.1 230.7 3,263.0 1,564.4 189.1 917.0 627.4 6.1 32.9 229.7 3,566.6 1,653.8 189.5 1,003.9 646,4 5.8 34.9 245.9 3,780.2 1,774.2 234.3 1,109.8 687.1 7.0 35.4 269.6 4,117.4 1,932.5 272.7 1,280.4 846.7 8.6 45.0 319.5 4,705.4 Source: U. S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports for the United States, 1968 (Washington, IL C. : ui s " ! Government Printing Office). \n o\ 357 TABLE A-17.— Self-Assessed. Retail Trade Transactions Subject to Sales and Use Taxation, Los Angeles County and Los Angeles, 1950 and 1954 to 1967, Current and Constant Dollars (Thousands of Dollars) Los Angeles Year County Los Angeles Current Dollars 1950 $ 3 ,7 0 7 ,8 5 4 $ ..................... 1954 4,599,642 ......... 1955 5,347,387 ......... 1956 5,546,051 ......... 1957 5,776,728 ......... 1958 5,538,701 2,450,393 1959 6 ,285,829 ......... 1960 6,309,163 2,793,337 1961 6 ,4 1 9 ,9 3 4 2,824,101 1962 7,022,739 3,056,431 1963 7 ,453,808 3,198,174 1964 8,021,898 3,388,603 1965 8 ,1 3 3 ,3 0 0 3,461,473 1966 8,728,412 3,623,675 1967 8 ,878,912 ......... (Continued) 358 TABLE A- 1 7 . — ( c out inue d) Year Los Angeles County Los Angeles 1950 19'57-59 Dollars3 - $4,499,823 $ • • • • • 1 954 4,961,858 * • • « « 1955 5,768,487 • • # • • 1956 5,893,784 * » • • » 1957 5,9^3,136 • • • • • 1958 5,505,667 2,435,778 1959 6,150,518 • • • • • 1960 6,060,675 2,683,321 1961 6,091,019 2,679,413 1962 6,587,935 2,867,196 1963 6,888,917 2,955,799 1964 7,279,399 3,074,957 1965 7 ,229,600 3 ,076,865 1 966 7,609,775 3,159,263 1967 7,550,095 • • • • • Consumer Price Index for Los Angeles is used to calculate retail trade transactions in 1957-59 dollars. Sources: California, Economic Development Agency, California Statistical Abstract (1961 to 1968). U. S. Department of Labor, Bureau of Labor Statistics, "Consumer Price Index, Los Angeles - Long Beach, California" (May, 1968). TABLE A-18.--Total and Per Capita Government Expenditures by Level of Government, Selected Years from 1950 to 1966, Current Dollars Year (Milli Totala ons of Dollars) Per Capita Federal State Local State and Local Total Federal State and Local Total 1950 $ 42,429 $10,864 $17,041 $27,905 $ 70,334 $250 $150 $400 1951 46,552 • « • * « 1 • • • • • • • • • • • • 1952 68,984 10,790 20,073 30,863 99,847 • • • • • • 1953 77,117 11,466 21,471 32,937 110,054 • • • • • • 195^ 74,725 13,008 23,599 36,607 111,332 • • • • • • 1955 70,342 14,371 26,004 40,375 110,717 388 204 592 1956 72,644 15,148 28,004 43,152 115,796 • • • • • • 1957 77,910 16,921 30,632 47,553 125,463 • • • • • • 1958 t • • « « » 1 « • » • • 134,931 • • • • 668 1959 • • • • • t • • t • • • 145,748 • • • • 704 I960 90,289 22,152 38,847 60,999 151,288 426 288 714 1961 » • • • • • • « • • • • 164,875 • « • • 760 1962 • • • « • • • • • 70,547 176,240 • • • • 803 1963 110,298 27,698 47,002 74,698 184,996 488 339 827 (Continued) Vo Li VO TABLE A-18.--(continued) Year Totala (Millions of Dollars) Per Capita Federal State Local State and Local Total Federal State and Local Total 1964 $115,852 $29,616 $50,964 $80,579 $196,431 $506 $362 $868 1965 118,996 31,334 55,221 86,554 205,550 511 385 896 1966 129,907 34,195 60,711 94,906 224,813 544 423 967 aDuplicate transactions among levels of government are excluded. Sources: U. S. Department of Commerce, Bureau of the Census, Historical Statistics of the United States. Colonial Times to 1957 (Washington, 5 " i C. : XL S^ Government Printing Office, i960), Series Y401, Y471, Y547, Y603, and Y632. U, S, Department of Commerce, Bureau of the Census, Statistical Abstract of the United States (Washington, D. C.: U. S, Government Printing Office, 1964, 1965, and 1968 issues), 1964: Table 555, 1965: Table 569, 1968: Tables 487 and 579. ON o TABLE A-19•--Total and Per Capita Government Expenditures by Level of Government, Selected Years from 1950 to 1966, Constant Dollars (1957-59 Dollars) Year (Milli Total3 , ons of Dollars) Per Capita Federal State Local State and Local Total Federal State and Local Total 1950 $ 50,660 $12,972 $20,347 $33,979 $.83,979 $298 $179 $478 1951 51,487 • 1 • • • • • • • • • • • 1952 74,572 11,664 21,699 33,363 107,835 • • 1953 82,669 12,292 23,017 35,308 117,978 • • 1954 79,881 13,906 25,227 39,133 119,014 • » 1955 75,336 15,391 27,850 43,242 118,578 416 218 634 1956 76,712 15,996 29,572 45,569 112,281 • » 1957 79,546 17,276 31,275 48,552 128,098 • • 1958 • • • • • • * • • • • • 134,121 664 1959 • • • • • * • • • • • • 11 *3,562 693 1960 87,671 21 ,510 37,720 59,230 146,901 414 280 693 1961 • « • • » « • • * • • • 158,280 730 1962 • • * • • « • * « 66,949 167,252 7 62 1963 103,349 25,953 44,041 69,992 173,341 457 318 775 (Continued) CD On TABLE A-19*--Total and Per Capita Government Expenditures by Level of Government Selected Years from 1950 to 1966, Constant Dollars (1957-59 Dollars) Year Totala (Millions of Dollars) Per Capita Federal State Local State and Local Total Federal State and Local Total 1964 $107,163 $27,395 $47,142 $74,536 $181,699 $468 $335 $803 1965 108,286 28,514 50,251 78,764 187,050 465 350 815 1966 114,838 30,228 53,669 83,897 198,735 481 374 816 aDuplicate transactions among levels of government are excluded. Sources: Table A-18. Indices of purchasing power of the dollar for consumer prices in the United States from U. S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States, 1968 (Washington, D. C.: U.S.Government Printing Office, 1968), Table 499. ON r o 363 TABLE A-20.--Total and Per Capita Expenditures, State of California, 1950 to 1968, Current and Constant Dollars Fiscal Year Total Ending (Thousands of Per June 30 Dollars) Capita Current Dollars 1950 $1,054,838 $101 1951 1,006,339 94 1952 1,068,072 95 1953 1,176,719 101 1954 1,381,400 113 1955 1,422,452 1 12 1956 1,532,811 11 6 1957 1,732,467 125 1958 1,891,436 131 1959 1,931,614 129 i960 2,085,584 134 1961 2,525,394 156 1962 2,406,218 144 1963 2,702,818 156 1964 2,977,742 166 1965 3,337,474 181 1966 3,636,358 194 1967 4,144,607 217 1968 4 ,670,365 241 ( Continued) 364 TABLE A-20.— (continued) Fiscal Year Ending June 30 Total (Thousands of Dollars) Per Capita 19 57-^9 Dollars 1950 $1,259,477 $ 1 20 1951 1,113,011 103 1952 1,154,586 1 03 1953 1,261,443 108 195^ 1,476,717 121 1955 1,523,446 1 20 1956 1,618,648 122 1957 1,768,849 1 28 1958 1,880,087 130 1959 1,902,640 127 1960 2,025,102 130 1961 2,424,378 1 50 1962 2,283,501 1 36 1963 2,532,540 146 1964 2,754,411 154 1965 3,037,101 1 65 1 966 3,214,540 171 1967 3,564,362 186 1968 3,876,403 200 Sources: California. California Statistical Abstract. 1968 (1968). Table 0-8. Indices of purchasing power of the dollar for consumer prices in the United States from U. S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States, 1968 (Washingt on, D. C. : U. S. Government Printing Office, 1968), Table 499 and U. S. Depart ment of Labor, Bureau of Labor Statistics, Monthly Labor Review. Vol. 92, no. 12 (December, 19^9)• 365 TABLE A-21.--Population Density of Cities with Popula tions of Over 500,OOO Persons in i960, 1940, 1950, and 1960 (Persons per Square Mile) City 1940 1950 1960 New York, N. Y. 24,933 25,046 24,697 Chicago, 111. 16,434 17,450 15,836 Los Angeles, Calif. 3,355 4,370 5,451 Philadelphia, Pa. 15,181 16,286 15,743 Detroit, Mich. 11 ,769 13,249 11,964 Baltimore, Md. 10,915 12,067 11,886 Houston, Tex. 5,288 3,726 2,860 Cleveland, 0. 12,011 12,197 10,789 Washington, D. C. 10,798 13,065 12,442 St. Louis, Mo. 13,377 14,046 12,296 Milwaukee, Wis. 13,525 12,748 8, 137 San Francisco, Calif. 14,238 17,385 15,553 Boston, Mass. 16,725 16,767 14,586 Dallas, Tex. 7,266 3,879 2,428 New Orleans, La. 2,482 2,861 3, 157 Pittsburg, Pa. 12,898 12,487 11,171 San Antonio, Tex. 7,115 5,877 3, 662 San Diego, Calif. 2, 130 3,364 2,979 Seattle, Wash. 5,372 6, 6o4 6,295 Buffalo, N. Y. 14,619 14,724 13,522 Cincinnati, 0. 6,298 6,711 6,501 Source: U. S. Department of Commerce, Bureau of the Census, County and City Data Book (Washington, D. C.: U. S. Government Printing Office, 1949, 1956, and 1962 issues). 366 TABLE A-22.— Area of Cities with. Over 500,000 Persons in 1960, 1940, 1950, and I960 (Square Miles) City 1940 1950 1960 New York, N. Y. 299.0 315.1 315.1 Chicago, 111. 206.7 207.5 224.2 Los Angeles, Calif. 448.3 450.9 454.8 Philadelphia. Pa, 127.2 127.2 127.2 Detroit, Mich. 137.9 139.6 139.6 Baltimore, Md. 78.7 78.7 79.0 Houston, Tex. 72.8 160.0 328. 1 Cleveland, O. 73. 1 75.0 81.2 Washington, D. C. 61.4 61.4 61 .4 St. Louis, Mo. 61.0 61 .0 61.0 Milwaukee, Wis. 43.4 50.0 91.1 San Francisco, Calif. 44.6 44.6 44.6 Boston, Mass. 46.1 47.8 47.8 Dallas, Tex. 4o. 6 1. 12.0 279.9 New Orleans, La. 199.4 199.4 198.8 Pittsburg, Pa. 52.1 54.2 54. 1 San Antonio, Tex. 35.7 69.5 160.5 San Diego, Calif. 95.3 99.4 192.4 Seattle, Wash. 68.5 70.8 88.5 Buffalo, N. Y. 39.4 39.4 39.4 Cincinnati, 0. 72.4 75. 1 77.3 Source: U. S. Department of Commerce, Bureau of the Census, County and City Data Book (Washington, D. C.: U. S. Government Printing Office, 19^-9» 1956, and 1962 issues). 367 TABLE A-23*— Population of Cities with. Populations of Over 500,000 Persons in i960, 19^0 , 1950, and 1960 (Thousands of Persons) City 1940 1950 1 960 New York, N. Y. 7,^55 7,892 7,782 Chicago, 111. 3,397 3,621 3,550 Los Angeles, Calif. 1 ,504 1 ,970 2,479 Philadelphia, Pa. 1 ,931 2,072 2,003 Detroit, Mich. 1 ,623 1 ,850 1 ,670 Baltimore, Md. 859 950 939 Houston, Tex. 385 596 938 Cleveland, 0. 878 915 876 Washington, D. C. 663 802 764 St. Louis, Mo. 816 857 750 Milwaukee, Wis. 587 637 741 San Francisco, Calif. 635 775 740 Boston, Mass. 771 801 697 Dallas, Tex. 295 434 680 New Orleans, La. 495 570 628 Pittsburg, Pa. 672 677 6o4 San Antonio, Tex. 254 408 588 San Diego, Calif. 203 335 573 Seattle, Wash. 368 468 557 Buffalo, N. Y. 576 580 533 Cincinnati, 0. 456 504 503 Source: U. S. Department of Commerce, Bureau of the Census, County and City Data Book (Washington, D. C.: U# S. Government Printing Office, 19^9,*1956, and 1962 issues). BIBLIOGRAPHY 368 BIBLIOGRAPHY BOOKS Aerojet-General Corporation. California Waste Management Study. Report No. 3056 (Final). Azusa, Calif.: Aerojet-General Corporation, August, 1965. 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Bloomington, Ind.: Prinpipia Press, 19^1* JOURNAL ARTICLES Ackley, Gardner. "Spatial Competition in a Discontinuous Market." Quarterly Journal of Economics. LVI ( 1962) 212-230. 380 Airov, Joseph. "The Construction of Interregional Business Cycle Models." Journal of Regional Science. V (Summer, 1963)9 1-20. Alexander, John W. "The Basic-Nonbasic Concept of Economic Functions." Land Economics, XXXII, 1 (February, 1956), 69-84. Allen, G. R. "The 'Courbe des Populations': A Further Analysis." Bulletin of the Oxford University Institute of Statistic" XVI (May and June, 195^)• Alonso, William. "The Historical and Structural Theories of Urban Form: Their Implications for Urban Renewal." Land Economics. XL, 2 (May, 1964), 227-231. Anderson, Theodore R., and Egeland, Janice A. "Spatial Aspects of Social Area Analysis," American Sociological Review, XXVI, 3 (June, 1961), 392-398. Andrews, Richard B. "Mechanics of the Urban Economic Base: Historical Development of the Base Concept." 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Mechanics of the Urban Economic Base: Causes and Effects of Change in the Base Ratios and the Ratio Elements (l)." Land Economics. XXXI, 2 (May, 1955), 144-155- "Mechanics of the Urban Economic Base: Causes and Effects of the Changes in the Base Ratios and the Base Ratio Elements (ll)." Land Economics, XXXI, 3 (August, 1955), 245-256. . "Mechanics of the Urban Economic Base: Causes and Effects of the Change in the Base Ratios and the Base Ratio Elements (ill)." Land Economics. XXXI, 4 (November, 1955), 361-371. . "Mechanics of the Urban Economic Base: The Base Connept and the Planning Process, ! ' Land Economics, XXXII, 1 (February, 1956), 69-84. Auerbach, F. "Das Gesetz der Bevolkerungskonzentration." Petermanns Mitteilungen, LIX (February, 1913). Bailey, Martin J. "Effects of Race and Other Demographic Factors on the Values of Single-Family Houses." Land Ec onomic s, XLII (May, 1966), 215-220. Bator, Francis M. "General Equilibrium, Welfare, and Allocation." American Economic Review, XLVII, 1 (March, 1957), 22-59. Bauer, Catherine. "The Pattern of Urban and Economic Development: Social Implications." The Annal of The American Academy of Political and Social Science. CCCV (May, 1956), 6O-6 9. Beckmann, Martin J. "A Continuous Model of Transporta* tion." Econometrica. XX (October, 1952), 643-660. 382 _________. "City Hierarchies and the Distribution of City Size." Economic Development and Cultural Change, VI (April", 1958), 243-248. _________. "The Partial Equilibrium of a Continuous Spatial Market." Weltwirtschaftliches Archiv. Bd. LXXI, Heft I, (1953), 73-89. _________, and Marschak, Thomas. "An Activity Analysis Approach to Location Theory. 1 1 Kvklos. VIII (1955), 125-1^3. Also in Proceedings of the Second Symposium in Linear Programming. Washington, D. C.: National Bureau of Standards and Directorate of Management Analysis, 1955* Bergmann, Barbara R. "The Urban Economy and the 'Urban Crisis'." American Economic Review. LIX, 4, Pt. I (September, 1969 ) , 639-645• Bergson, Abram. "A Reformulation of Certain Aspects of Welfare Economics." Quarterly Journal of Economics, LII (1938), 310-334. Berry, Brian J. L. "City Size Distributions and Economic Development." Economic Development and Cultural Change. IX, 4, Pt. I (July, 1961 ), 573-587. _________, and Garrison, William L. "Alternate Explana tions of Urban Rank-Size Relationships." Annals of the Association of American Geographers. XLVIII (March, 1958), 83-91. _________; Simmons, James W.; and Tennant, Robert J. "Urban Population Densities, Structure and Change." The Geographical Review. LIII (1963)* 389-405. Blau, Julian H. "The Existence of Social Welfare Functions." Econometrica, XXV, 2 (April, 1957), 302-313. Blumenfeld, Hans. "On the Concentric-Circle Theory of Urban Growth. 1 1 Land Economics, XXV (May, 1949), 207-212. . "The Economic Base of the Metropolis." Journal of the American Institute of Planners. XXI, 4 (Fall, 1955), 114-132. 383 Boulding, Kenneth.. "General Systems Theory^-The Skeleton of a Science." Management Science. II, 3 (April, 1956), 197-208. Boventer, Edwin von. Spatial Organization Theory as a Basis for Regional Planning." Journal of the American Institute of Planners. XXX.2 (May, 1964), 90-100. Brigham, Eugene F. "The Determinants of Residential Land Values." Land Ec on omi c s. XLI, 4 (November, 1965), 325-334. Buchanan, James M. "A Behavioral Theory of Pollution." Western Economic Journal. VI, 5 (December, 1968), 347-358. _________ , and Stubblebine, William Craig. "Externality. 1 1 Economica. XXIX (November, 1962), 371-384. Champernowne, D. G. "A Model of Income Distribution." Ec onomic J ournal. LXIII (June, 1953), 318-351* Childe, V. G. "The Urban Revolution." Town Planning Review. XXI (1950), 3-17. Chisholm, Michael D. I. "Agricultural Production, Location, and Rent." Oxford Economic Papers. XIII, 3 (October, 1961), 342-359. Clark, Colin. "The Economic Functions of a City in Relation to Its Size." Econometrica. XIII (1945), 97-113. _________ . "Urban Population Densities." Journal of the Royal Statistical Society, CXIV, Pt. IV (1951 ), 490-496. Coase, Ronald. "The Problem of Social Costs." Journal of Law and Economics. Ill (October, 1961), 1-44. Davis, Kingsley. "Recent Population Trends in the New World: An Over-all View." The Annals of the American Academy of Political and Social Science, CCCXVI (March, 1958), 1-10. 384 Dennison, S. R. "The Theory of Industrial Location." Manchester School of Economics and Social Studies. VIII ( 1937 ) , 23-47. Duncan, Beverly, and Duncan, Otis Dudley. "The Measure ment of Intra-city Locational and Residential Patterns." Journal of Regional Science, II, 2 (1960), 37-54• Durand, John D. "A Long-Range View of World Population Growth." The Annals of the American Academy of Political and Social Science^ CCCLXIX (January, 1967), 1-8. El-Badry, M. A. "Population Projections for the World, Developed and Developing Regions: 1965-2000." The Annals of the American Academy of Political and Social Science. CCCLXIX (January. 1967), 9-15- Englander, Oskar. "Kritisches und Positives zu einer allgemeinen reinen Lehre vom Standort." Zeitschrift fur Volkswirtschaft und Sozialpolitik. Neue Polge, V, 7-9 (1926) . “ Enke, Stephen. "Equilibrium Among Spatially Separated Markets: Solution by Electric Analogue." Ec onometrica, XIX (January, 1951)> 40-47. Fetter, Frank A. "The Economic Law of Market Areas." Quarterly Journal of Economics. XXXVIII (May, 1924), 520-529. Firey, Walter. "Residential Sectors Re-Examined." Appraisal Journal. XVIII (1950), 451-453. Fisher, Allan G. B. "Capital and the Growth of Know ledge." Economic Journal. XLIII (1933)j 379-389* ____ ____ . "Production, Primary, Secondary, and Tertiary." Economic Record, XV (June, 1939)» 24-38. Fleming, Marcus. "External Economies and the Doctrine of Balanced Growth." The Economic Journal. LXV (June, 1955), 241-256. 385 Fox Karl A. "A Spatial Equilibrium Model of the Livestock-Feed Economy in the United States." Econometrica. XXX (October, 1953) » 5^7-566. Friedmann, John R. P. "Locational Aspects of Economic Development." Land Economics, XXXII,3 (August, 1956), 213-227. Furlan, L. Vladimir. "Die Standortsprobleme in der Volks- und Weltwirtschaftslehre." Weltwirtschaft- liches Archiv. ±1 .(1913), 1-3^. Goodman, Leo A., and Markowitz, Harry. "Social Welfare Functions Based on Individual Rankings." American Journal of Sociology. LVIII (November, 1952), 257-262. Greenhut, Melvin L. "Integrating the Leading Theories of Plant Location." Southern Economic Journal. XVIII (April, 1952), 526-538. _________ . "The Size and Shape of the Market Area of a Firm." Southern Economic Journal. XIX (July, 1952), 37-50. Grotewold, Andreas. "von Thunen in Retrospect." Economic Geography. XXXV (October, 1959 )> 3^6-355* Haig, Robert M. "Toward an Understanding of the Metropolis; the Assignment of Activities to Areas in Urban Regions." Quarterly Journal of Economics. XL (May, 1926), 402-434. Hansen, Willard B. "An Approach to the Analysis of Metropolitan Residential Extension." Journal of Regional Science. Ill, 1 (1961), 37-55- Harris, Chauncy D. "A Functional Classification of Cities in the United States." Geographical Review. XXXIII (1943), 86-99* _________ . "The Market as a Factor in the Localization of Industry in the United States." Annals of the Association of American Geographers. XL1V. 5 (December, - 1 95*0 » 315-348 . 386 ____, and Ullman, Edward L. MTtxe Nature of Cities.” The Annals of the American Academy of Political and Social Science. CCXLII (November, 1945), 7“17. Henderson, Julia J. "Urbanization and the World Community." The Annals of the American Academy of Political and Social Science" CCCXIV (November, 1*957X 147-155. Herbert, John D., and Stevens, Benjamin H. "A Model for the Distribution of Residential Activity in Urban Areas." Journal of Regional Science. II, 2 (Fall, 1960), 21-36. Hicks, John R. "Foundations of Welfare Economics." Economic Journal, XLIX (1939), 696-712. Hildebrand, George H., and Mace, Arthur, Jr. "The Employment Multiplier in an Expanding Industrial Market: Los Angeles County, 1940-47." Review of Economics and Statistics, XXXII, 3 (August, 1950), 241-249. Hildreth, Clifford. "Alternative Conditions for Social Orderings." Econometrica, XXI (January, 1953), 81-91 . Hoover, Edgar M. "The Concept of a System of Cities: A Comment on Rutledge Vining1s Paper." Economic Development and Cultural Change, III (January, 1955), 196-198. _________. "Generative and Parasitic Cities." Economic Development and Cultural Change, III, 3 (April, 1955), 278-294. _________. "The Role of Cities in the Economic Growth of Underdeveloped Countries." Journal of Political Economy, LXI, 3 (June, 1953), 195”208, Hotelling, Harold. "Differential Equations Subject to Error and Population Estimates." Journal of the American Statistical Association, XXII (1927 ) , 283-314. _________. "Stability in Competition." Economic Journal. XXXIX (March, 1929), 41-57. 387 Hoyt, Homer. "Economic Background of Cities." Journal of Land and Public Utility Economics. XLII, 2 (May, 19^1), 188-195. ________ . "Homer Hoyt on the Concept of the Economic Base." Land Economics. XXX (May, 195^0 » 182-186. _________ . "Recent Distortions of the Classical Models of Urban Structure." Land Economics. LX, 2 (May, 196*0, 199-212. _________• "Residential Sectors Revisited." Appraisal Journal. XVIIX (1950), 445-450. Hyson, C. D., and Hyson, W. P. "The Economic Law of Market Areas." Quarterly Journal of Economics. LXIV (May, 1950), 319-327. Isard, Walter. "Distance Inputs and the Space Economy, Part I. The Conceptual Framework." Quarterly Journal of Economics. LXV (May, 1951)» 188-198. _________ . "Some Locational Factors in the Iron and Steel Industry Since the Early Nineteenth Century." Journal of Political Economy. LVI (1948), 213-217* _________ . "The General Theory of Location and Space Economy." Quarterly Journal of Economics. LXIII (November, 1949 ) > 476-506. ■ Kaldor, Nicholas. "Welfare Propositions in Economics." Economic Journal. XLIX (1939), 5*1-9-552. Kuhn, Harold W. , and Kuenne, Robert E. "An Efficient Algorithm for the Numerical Solution of the Generalized Weber Problem in Spatial Economics." Journal of Regional Science. IV, 2 (1962), 21-33. Koopmans, Tjalling C. "Optimum Utilization of the Transportation System." Econometrica, XVII (July, 19^9)» Supplement, 136-146. _________ , and Beckmann, Martin J. "Assignment Problems and the Location of Economic Activities." Econometrica. LXXV, 1 (January, 1957)» 53-76. 388 Lampard, Eric E. "The History of Cities in the Economi cally Advanced Areas." Economic Development and Cultural Change, III (January, 1955) f 81-102. Launhardt, Wilhelm. "Die Bestimmung des zweckmassigsten Standortes Einer Gewerblichen Anlage." Zeitschrift des Vereins Deutscher Ingenieure. XXVI, 3 (1882). Leigh, Arthur H. "von Thunen1s Theory of* Distribution and the Advent of* Marginal Analysis." Journal of Political Economy. LIV (December, 1946), 481-502. Losch, August. "The Nature of Economic Regions." Southern Economic Journal. V, .1 (July, 1938), 71-78. Lowry, Ira S., "Filtering and Housing Standards." Land Economics. XXXVI, 4 (November, i960), 362-370. Mandelbrot, Benoit. "Paretian Distributions and Income Maximization." Quarterly Journal of Economics. LXXVI (February, 1962), 57-85. _________ . "The Pareto-Levy Law and the Distribution of* Income." International Economic Review. I, 2 (May, i960), 79-106. Maruyama, Magoroh. "The Second Cybernetics: Deviation Amplifying Mutual Causal Processes." American Scientist. LI (1963)* 164-169. Reprinted in General Systems. VIII (1963), 233-241. Metzler, Lloyd A. "A Multiple-Region Theory of Income and. Trade." Econometrica. XVIII, 4 (October, 1930), 329-354. Mills, Edwin S.,,and Lav, Michael R. "A Model of Market Areas with Free Entry." Journal of Political Economy. LXXII, 3 (June, 1964), 278-288. Moses, Leon N. "A General Equilibrium Model of Pro duction, Interregional Trade, and Location of Industry." Review of Economics and Statistics. XLII, 4 (November, i960), 373-399. _________ . "Location and the Theory of Production." Quarterly Journal of Economics. LXXII (May, 1958), 259-272. 389 Muth, Richard F. "Economic Change and Rural-Urban Land Conversions." Econometrica. XXIX (January, 1961), 1-23. North, Douglass C. "Location Theory and Regional Economic Growth." Journal of Political Economy. LXIII, 3 (June, 1955), 243-258. Petersen, William. "Internal Migration and Economic Development in Northern America." The Annals of the American Academy of Political and Social Science" CCCXVI (March, 1958), 52-59• Pfouts, Ralph W., and Curtis, Erie T. "Limitations of the Economic Base Analysis." Social Forces. XXXVI, 4 (May, 1958), 303-310. Predohl, Andreas. "Das Standortsproblem in der Wirtschaftstheorie." Weltwirtschaftliches Archiv. x x i ( 1925) , 294- 331. _________ . "The Theory of Location in Its Relation to General Economics." Journal of Political Economy. XXXVI (June, 1928), 371-390. Quinn, James A. "The Burgess Zonal Hypothesis and Its Critics." American Sociological Review. V (1940), 210-218. Rhodes, E. C. "Population Mathematics III." Journal of the Royal Statistical Society. CIII (1940), 362ff. Ridker, Ronald G., and Henning, John A. "The Deter minants of Residential Property Values with Special Reference to Air Pollution." The Review of Economics and Statistics. XLIV, 2 (May, 1967), 246-257. Ritschl, Hans. "Reine und historische Dynamik des Standortes der Erzeugungszweige." Schmollers Jahrbuch. LI (1927), 813-870. 390 Rodwin, Lloyd. "Rejoinder to Dr. Firey and Dr. Hoyt." The Appraisal Journal, XVIII (1950), 454-457 • _________ . "The Theory of Residential Growth and Structure." Appraisal Journal. XVIII (1950)» 295-317. Rosenstein-Rodan, Paul N. "Problems of Industrialization of Eastern and Southeastern Europe." The Economic Journal, LIII (June-September, 1943), 202-211. Rydell, C. Peter. "A Note on a Location Principle: Between the Median and the Mode." Journal of Regional Science. VII, 2 (1967)} 185-192. Samuelson, Paul Anthony. "Spatial Price Equilibrium and Linear Programming." American Economic Review, XLII (June, 1952), 293-303. Schnore, Leo F. "The Statistical Measurement of Urbani zation and Economic Development." Land Economics, XXXVII, 3 (August, 1961), 229-2^5. _________ , and Petersen, Gene B. "Urban and Metropolitan Development in the United States and Canada." The Annals of the American Academy of Political and Social Science. CCCXVII (March, 1958), 60-68. Schultz, Henry. "The Standard Error of a Forecast from a Curve." Journal of the American Statistical Association, XXV (June, 1930), 139-185. Scitovsky, Tibor. "A Note on Welfare Propositions in Economics." Review of Economic Studies. IX (1941), 77-88. _________ . "External Diseconomies in the Modern Economy." The Western Economic Journal. IV, 3 (Summer, 1966), 197-202. _ _ _ _ _ _______. "Two Concepts of External Economics." Journal of Political Economy. LXII, 2 (April, 1954), 143-151. Simon, Herbert A., and Bonini, Charles P. "The Size Distribution of Business Firms." American Economic Review. LXYIII (September, 1958), <307-615. 391 Singer, H. ¥. "The 1Courbe des Populations', A Parallel to Pareto's Law." Economic Journal, XLYX (June, 1936), 254-263. Smithies, Arthur. "Optimum Location in Spatial Compe tition." Journal of Political Economy. XLIX (l9^l)» 423-439* Sombart, Werner. "Der Begriff der Stadt und das Wesen der Stadtebildung." Archiv fur Sozialwissenschaft und Sozialpolitik, XXV (1907). Spengler, Joseph J. "Richard Cantillon: First of the Moderns." The Journal of Political Economy. LXII (August, October, 195*0, 281-295, 406- 429. Also reprinted in Spengler, Joseph J., and Allen, William R. Essays in Economic Thought; Aristotle to Marshall. Chicago: Rand McNally & Company, i960. Stevens, Benjamin H. "Linear Programming and Location Rent." Journal of Regional Science. Ill, 2 (1961), 15-26. Stewart, John Q. "Empirical Mathematical Rules Con cerning the Distribution and Equilibrium of Population." The Geographical Review. XXXVII (1947)* 461-485. _________, and Warntz, William. "Physics of Population Distribution." Journal of Regional Science. I, 1 (1958), 99-123. Stigler, George J. "The Division of Labor is Limited by the Extent of the Market." Journal of Political Economy. LIX, 3 (June, 1951)* 185-193* Stolper, Wolfgang F. Book review of August Losch's The Economics of Location. American Economic Review. XXXIII (September, 1943), 626-636. Taeuber, Irene B. "Demographic Transitions and Population Problems in the United States." The Annals of the ' American Academy of Political and Social Science. CCCLXIX (January, 19^7), 131-140. Tiebout, Charles M. "Community Income Multipliers: A Population Growth Model." Journal of Regional Science, II, 1 (i960), 75-84. 392 _________ . "Exports and. Regional Economic Growth. 1 1 Journal of* Political Economy. LXIV (April, 1956), 160-164. _________ . "The Urban Economic Base Reconsidered." Land Economics, XXXII, 1 (February, 1956), 95-99* Tinbergen, Jan. "The Spatial Dispersion of Production: A Hypothesis." Schweizerische Zeitschrift fur Volkswirtschaft und Statistik. XCVXI (1961), 412-419)» Tintner, Gerhard. "A Note on Welfare Economics." Econometrica, XIV, 1 (January, 1946), 69-78. Tisdale, Hope. "The Process of Urbanization." Social Forces. XX (1942), 311-316. Ullman, Edward. "A Theory of Location for Cities." American Journal of Sociology. XLVI, 6 (May, 194l), 853-864. Vining, Rutledge. "A Description of Certain Spatial Aspects of an Economic System." Economic Development and Cultural Change , III (January"] 1 955 ) > 1 47- 1 95 • _________ . "Location of Industry and Regional Patterns of Business-Cycle Behavior." Econometrica. XIV, 1 (January, 1946), 37-68. Weigmann, Hans. "Ideen zu einer Theorie der Raumwirtschaft." Weltwirtschaftliches Archiv, XXXIV (1931), 1-4o. Weiss, Herbert K. "The Distribution of Urban Population and an Application to a Servicing Problems." Operations Research. IX, 6 (November-December, 1961), 860-874” Winsborough, Hal H. "City Growth and City Structure." Journal of Regional Science. IV, 2 (1963), 35-^9* Worchester, Dean A., Jr. "Pecuniary and Technological Externality, Factor Rents, and Social Costs." American Economic Review. LIX, 5 (December, 1969), 873-885. Young, Allyn. "Increasing Returns and Economic Progress." The Economic Journal, XXXVIII (December, 1928), 527-542. PAPERS AND PROCEEDINGS Alonso, William. "A Reformulation of Classical Location Theory, and Its Relation to Rent Theory. 1 1 The Regional Science Association Papers. XIX (1967), 23-44. _________ . "A Theory of the Urban Land Market." The Regional Science Association Papers and Proceedings'! VI ( 1 960 ) , 1 49- 1 57 • Anderson, Theodore R. "Social and Economic Factors Affecting the Location of Residential Neighbor hoods ." The Regional Science Association Papers and Proceedings. IX (1962). 16 1-170. Beckmann, Martin J. "Some Reflections on Losch's Theory of Location." The Regional Science Association Papers and Proceedings. I (1955 ) » N1-N9. Berman, Edward B. "Spatial and Dynamic Growth Model." The Regional Science Association Papers and Proceedings, V ( 1959)> 143-150• Berry, Brian J. L. "Cities as Systems Within Systems of Cities." The Regional Science Association Papers. XIII (1964), 147-163. _________ ; Barnum, H. Gardiner; and Tennant, Robert J. "Retail Location and Consumer Behavior." The Regional Science Association Papers and Proceedings, ix (1962), 65-106. Boventer, Edwin von. "Land Values and Spatial Structure: Agricultural, Urban and Tourist Location Theories." The Regional Science Association Papers. XVIII, (1967), 231-242. 39^ _________ . "Towards a United Theory of* Spatial Economic Structure." The Regional Science Association Papers. X (1962), 163-187. Chinitz, Benjamin. "Contrasts in Agglomeration: New York and Pittsburg." American Economic Review. Papers and Proceedings" LI, 2 (May, 1961 ) , 279-289• Guthrie, J. A. "Economies of* Scale and Regional Development." The Regional Science Association Papers and Proceedings] I (1955)» J1-J1O. Henderson, James M. "The Utilization of* Agricultural Land: A Regional Approach." The Regional Science Association Papers and Proceedings.Ill (1957)> 99-114. Hoselitz, Bert P. "The City, The Factory, and Economic Growth." The American Economic Review. Papers and Proceedings of* the American Economic Association. XLV (May, 1955), 166-184. Isard, Walter. "Game Theory, Location Theory, and Industrial Agglomeration." The Regional Science Association Papers. XVIII (1967)» 1-11• _________ . "Location Games: With Applications to Classic Location Problems." The Regional Science Association Papers. XIX (1967)» 45-80. _________ , and Smith, Tony E, "Coalition Location Games: Paper 3." The Regional Science Association Papers and Proceedings. XX ( 1968 ) . 95-107. Kain, John P. "The Journey-to-Work as a Determinant of Residential Location." The Regional Science Association Papers and Proceedings. I X (1962), 137-160. Moses, Leon N. , and Williamson, Harold F. , Jr. "The Location of Economic Activity in Cities." American Economic Review. Papers and Proceedings of the American Economic Association. LXII, 2 (May, 1967), 211-222. 395 Muth, Richard F. "The Spatial Structure of the Housing Market." The Regional Science Association Papers and Proceedings. VII (1961), 207-220. _________. "The Variation of Population Density and Its Components in South Chicago.1 1 The Regional Science Association Papers. XV (1965)5 173-183* Newling, Bruce E. "A Partial Theory of* Urban Growth: Mathematical Structure and Planning Implications. 1 1 Mexico City, Mexico: Latin American Regional Conference of the International Geographical Union, August 55 1966. Olsson, Gunnar. "Central Place Systems, Spatial Inter action, and Stochastic Processes." The Regional Science Association Papers. XVIII (1967 ) 5 13-^5• Orr, E. ¥. "Synthesis of Theories of Location, of Transport Rates, and of Spatial Price Equilibrium." Papers and Proceedings of the Regional Science Association. Ill (1957). 61-73. Rapkin, Chester. "Some Effects of Economic Growth on the Character of Cities." American Economic Review. Papers and Proceedings of the American Economic Association. XLVI (May" 1956), 293-301. Sakashita, Noburo. "Production Function, Demand Function and Location Theory of the Firm." The Regional Science Association Papers and Proceedings. XX (1968), 109-122. Thomas, Morgan. "Regional Economic Growth and Industrial Development." The Regional Science Association Papers and Proceedings. x (1963), 61-75. Tiebout, Charles M. "Intra-Urban Location Problems." American Economic Review. Papers and Proceedings of the American Economic Association. L I , 2 (May, 1961), 271-278. Tinbergen, Jan. "The Hierarchy Model of the Size Distribution of Centres." The Regional Science Association Papers and Proceedings. X X (1968), 65-68. 396 Ullman, Edward L. "Presidential Address: The Nature of Cities Reconsidered." The Regional Science Association Papers and Proceedings. XX (1962 ) , 7-23• _________ . "Regional Development and the Geography of Concentration." The Regional Science Association Papers and Proceedings. IV (1958), 179-198. Vining, Rutledge. "The Region as an Economic Entity and Certain Variations to be Observed in the Study of Systems of Regions." American Economic Review. Papers and Proceedings of the American Economic Association. XXXIX, 3 (May, 19^9)> 89-104• Ward, Benjamin. "City Structure and Interdependence." The Regional Science Association Papers and Proceedings" X (1963)» 207-221 * Wingo, Lowdon, Jr. "An Economic Model of the Utilization of Urban Land for Residential Purposes." The Regional Science Association Papers and Proceedings, v i i (1961), 191- 205. ARTICLES IN COLLECTIONS Alonso, William. "Location Theory." Regional Development and Planning. Edited by John Friedmann and William Alonso. Cambridge, Mass.: The M. I. T. Press, 1964. Beckmann, Martin J. "Transportation Economy and Urban Concentration." Paths to Economic Growth. Edited by A. Datta, New Delhi, India: Allied Publishers, 1962. Bill, W. "Social Areas: Typology of Urban Neighbor hoods." Community Structure and Analysis. Edited by Marvin B, Sussman. Riverside, N. J.S Cromwell Collier Press, 1959? Burgess, Ernest W. "The Growth of the City: An Introduction to a Research Project." The City. Edited by Robert E. Park, Ernest W. Burgess, and Roderick D. McKenzie. Chicago: University of Chicago Press, 1925* 397 _________ . ’ 'Urban Areas. " Chicago: An Experiment in Social Science Research. Chicago: University of Chicago Press, 1929* Dantzig, George B. "Application of the Simplex Method to a Transportation Problem. 1 1 Activity Analysis of Production and Allocation. Edited by Tjailing C. Koopmans, New York: John Wiley & Sons, Inc., 1951* Davie, M. R. "The Pattern of Urban Growth." Studies in the Science of Society. Edited by G. P. Murdock. New Haven, Conn.: Yale University Press, 1937* Davis, Kingsley. "The Urbanization of the Human Population." Cities. New York: A. A. Knopf, 1965. Ferguson, Charles E. "Statics, Dynamics, and Economic Base." The Techniques of Urban Analysis. Edited by Ralph W. Pfouts. West Trenton, N. J.: Chandler-Davis Publishing Company, 1960. Grigsby, William G. "The Filtering Process." Urban Housing. Edited by William L. C. Wheaton, Grace Milgram, and Margie Ellin Meyerson. New York: The Free Press, 1966). Hauser, Phillip M. "Urbanization: An Overview." The Study of Urbanization. Edited by Phillip M. Hauser and Leo F. Schnore. New York: John Wiley & Sons, Inc., 1965* Hirsch, Werner Z. "The Supply of Urban Public Services." Issues in Urban Economics. Edited by Harvey S. Perloff and Lowdon Wingo, Jr. Baltimore: The Johns Hopkins Press for Resources for the Future, Inc., 1968. Hoover, Edgar M. "The Evolving Form and Organization of the Metropolis." Issues in Urban Economics. Edited by Harvey S. Perloff and Lowdon Wingo, Jr. Baltimore: The Johns Hopkins. Press for Resources for the Future, Inc., 1968. . and Fisher, Joseph L. "Research in Regional Economic Growth." Problems in the Study of Economic Growth. Universities-National Bureau Committee for Economic Research, New York: National Bureau of Economic Research, 19^9* 398 Lampard, Eric E. "Historical Aspects of4 Urbanization." The Study of Urbanization. Edited by Phillip M. Hauser and Leo P. Schnore. New York; John Wiley & Sons, Inc., 1965. _________ . "The Evolving System of Cities in the United States; Urbanization and Economic Development." Issues in Urban Economics. Edited by Harvey S. Perloff and Lowdon Wingo, Jr. Baltimore: The Johns Hopkins Press for Resources for the Future, Inc., 1968. Ludlow, William H. "Urban Densities and Their Costs: An Exploration into the Economics of Population Densities and Urban Patterns." Urban Redevelopment; Problems and Practice. Edited by Coleman Woodbury. Chicago: University of Chicago Press, 1953* Mishan, Ezra J. "A Survey of Welfare Economics, 1939-59*1 1 Surveys of Economic Theory. Vol. I. London: Macmillan and Company, Limited, 19^5. Muth, Richard P. "The Distribution of Population in Urban Areas." Determinants of Investment. Edited by Robert Ferber. New York: National Bureau of Economic Research, 19^7» _________ . "Urban Residential Land and Housing Markets." Issues in Urban Economics. Edited by Harvey S. Perloff and Lowdon Wingo, Jr. Baltimore: The Johns Hopkins Press for Resources for the Future, Inc., 1968. Ohlin, Bertil G. "Some Aspects of the Theory of Rent: von Thunen vs. Ricardo." Carver Festschrift: Economics. Sociology, and the Modern World. Edited by N. Hines. Cambridge, Mass.j 1935- Perloff, Harvey S., and Wingo, Lowdon, Jr. "Natural Resource Endowment and Regional Economic Growth." Natural Resources and Economic Growth. Edited by Joseph J. Spengler. Washington, D. C.: Resources for the Future, Inc., 19^1» Simon, Herbert A. "On a Class of Skew Distribution Functions." Models of Man. By Herbert A. Simon. New York: John Wiley & Sons, Inc., 1957* 399 Spengler, Joseph J. "Population Theory." A Survey of Contemporary Economics. IX. Edited by Bernard F. Haley. Homewood, 111.: Richard D. Irwin, Inc., 1952. Thompson, Wilbur R. "Internal and External Factors in the Development of Urban Economies." Issues in Urban Economics. Edited by Harvey S. Perloff and Lowdon Wingo, Jr. Baltimore: The Johns Hopkins Press for Resources for the Future, Inc., 1968. _________ . "Urban Economic Growth and Development in a National System of Cities." The Study of Urbanization. Edited by Phillip M. Hauser and Leo F. Schnore. New York: John Wiley & Sons., Inc., 1965. Tiebout, Charles M. "Community Income Multiplier: A Case Study." Detroit: Joint Conference of the Econometric Society and the American Statistical Association, September, 1956. Reprinted in The Techniques of Urban Economic Analysis. Edited by Ralph W. Pfouts. West Trenton, N. J.: Chandler- Davis Publishing Company, i960. Vernon, Raymond, and Hoover, Edgar M. "Economic Aspects of Urban Research." The Study of Urbanization. Edited by Phillip M. Hauser and Leo F. Schnore. New York: John Wiley & Sons, Inc., 1965* Weigmann, Hans. "Standortstheorie und Raumwirtschaft." Johann Heinrich von Thiinen zum 150 Geburtstag. Edited by W. Seedorf and H. Jurgen. Rostock: Carl Hinstorffs, 1933» Wilson, James Q. "Crime in the Streets." Metropolis in Crisis. Edited by Jeffrey K. Hadden, Louis H. Masotti, and Calvin J. Larson. Itasca, 111.: F. E. Peacock Publishers, Inc., 1967. PUBLIC DOCUMENTS California. Economic Development Agency. California Statistical Abstract. 1961 to 1968 issues. 4oo California. Office ef the State Controller. Annual Report of Financial Transactions Concerning Cities in California. 1946-47 to 1966-67 issues. Los Angeles, California. "Population Estimate by Communities," Bulletin 1959-1• January 1, 1959* Los Angeles, California. City Planning Commission, Research Section. Population Estimate and Housing Inventory. April 1 issue, i960 and 1968. Los Angeles, California. Department of City Planning. Background Information for the Los Angeles Comprehensive Plan. Vol. II, Analysis of the Land Use Characteristics. Research Monograph RM-SD-40041-01. March 1, 1968. Los Angeles, California. Police Department. Statistical Digest. 1957 through 19^7 issues. Los Angeles, California. Police Department. Traffic Statistics. 1925-1968. Los Angeles County, California. Air Pollution Control District. Profile of Air Pollution in Los Angeles County. 1969. Los Angeles County, California. Regional Planning Commission. "A Summary Table--Population Growth, Los Angeles County, Los Angeles City, California, and the United States, 1940 to 1968." September, 1968. Los Angeles County, California. Regional Planning Commission. "Population of Los Angeles County, 1965-1985*1 1 August, 1966. Los Angeles County, California. Regional Planning Commission. Quarterly Bulletin. Population and Dwelling Units. Bulletin No. 105? July 1, 1969* Los Angeles County, California. Regional Planning Commission. 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Asset Metadata

Creator Bechdolt, Burley Vincent, Jr. (author)

Core Title Some External Diseconomies Of Urban Growth And Crowding: Los Angeles

Degree Doctor of Philosophy

Degree Program Economics

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Economics, General,OAI-PMH Harvest

Language English

Contributor Digitized by ProQuest (provenance)

Advisor Niedercorn, John H. (committee chair), Robinson, Ira M. (committee member), Tintner, Gerhard (committee member)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c18-409119

Unique identifier UC11361390

Identifier 7019107.pdf (filename),usctheses-c18-409119 (legacy record id)

Legacy Identifier 7019107.pdf

Dmrecord 409119

Document Type Dissertation

Rights Bechdolt, Burley Vincent, Jr.

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA