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Employment Distribution, Income, And City Size: A Statistical Analysis

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Employment Distribution, Income, And City Size: A Statistical Analysis

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Content EMPLOYMENT DISTRIBUTION, INCOME, AND CITY SIZE: A STATISTICAL ANALYSIS t>y David Junewhan Park 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 (Economics) January 1963 UNIVERSITY O F SOU TH ERN CALIFORNIA GRADUATE SCHOOL UNIVERSITY PARK LOS ANGELES 7 . CALIFORNIA This dissertation, written by .......... under the direction of hiJS....Dissertation Com mittee, and approved by all its members, has been presented to and accepted by the Graduate School, in partial fulfillment of requirements for the degree of D O C T O R OF P H IL O S O P H Y Dean Date nmm.19.63i.............. DISSERTATION COMMITTEE TABLE OF CONTENTS CHAPTER PAGE I. INTRODUCTION ......................... 1 General Statement ................... 1 Statement of Purpose of the Study . . 2 Definitions of Terms Used .......... 3 Economic base theory .......... 3 Basic activity............. 4 Service activity .............. 4 Base-service ratio ............ 4 Community income multiplier ... 4 Statistical approach .......... 5 The Scope of the S t u d y........ 3 Limitation of Statistical Data . . 5 Difficulty Arising from the Definitional Differences .... 7 Basis of Selecting Areas for Exam ination ....................... 8 Organization of Remainder of the Thesis....................... 11 II. CURRENT STATUS OF THE ECONOMIC BASE THEORY......................... 14 Base-Service Concept .............. 14 iii CHAPTER PAGE Basic Activity.............. 15 Service Activity ................ 18 Identifying and Measuring the Base . 19 Identification .......... 19 Measurement.................. 20 Location quotient ............ 21 Index of surplus employment . . 21 Concept of Economic Base Ratio ... 23 Community Income Multiplier: A Keynesian Model .................. 24 Economic Base Theory and City Planning.................... 28 Master Plan.................. 28 Economic Base Theory as an Aid to Planning.................. 29 III. METHODOLOGY...................... 32 Assumptions.................... 32 Analysis of Employment in a Single Industry.................... 34 Analysis of Employment in the Pour Industries Combined .............. 36 Analysis of Income and City Size . . 36 IV. ANALYSIS OF MANUFACTURING EMPLOYMENT . 40 iv CHAPTER PAGE Summary and Analysis of the Statis tical Measurements.............. 40 National and City Patterns .... 42 Manufacturing Employment and City S i z e ........................... 45 High and Low Rates of Population Growth and the Rates of Growth in Manufacturing Employment .... 45 Low Percentages during the Earlier Period and the Rates of Growth . 48 Patterns of the Percentage Fluctuations .................. 50 Manufacturing Employment and the Economic Base..................... 52 Modification of the Index of Surplus Employment ............ 53 Test of the Index Technique .... 54 Determination of the Size of the B a s e ........................... 55 V. ANALYSIS OF RETAIL-TRADE EMPLOYMENT . . 56 Summary and Analysis of the Statis tical Measurements.............. 56 National and City Patterns .... 58 V CHAPTER PAGE Retail Employment, City Size, and Population Growth ............ 59 Patterns of the Percentage Fluctua tions ........................... 60 Base-Service Identification ........ 63 VI. ANALYSIS OF WHOLESALE-TRADE EMPLOYMENT 65 Summary and Analysis of the Statis tical Measurements ........ 65 National and City Patterns .... 65 Wholesale Employment, City Size, and Population Growth ............ 67 Patterns of the Percentage Fluctua tions ........................... 68 Base-Service Identification ........ 70 VII. ANALYSIS OF SERVICE-TRADE EMPLOYMENT . 72 Summary and Analysis of the Statis- \ tical Measurements.............. 73 National and City Patterns .... 73 Service Employment, City Size, the Rate of Population Growth .... .75 Patterns of the Percentage Fluctua tions ......................... 77 Base-Service Identification ........ 79 Vi CHAPTER PAGE VIII. ANALYSIS OF MANUFACTURING, RETAIL, WHOLESALE, AND SERVICE EMPLOYMENT COMBINED........................ 82 Relationship between Employment Growth and Population Growth ... 83 Importance of Manufacturing, Retail, Wholesale, and Service Employment as the Employment Generator .... 88 National and City Patterns .... 92 Employment and City S i z e ..... 92 Fast-Growing and Matured Cities . . 93 Base-Service Identification ........ 9k IX. INCOME AND CITY S I Z E ............. 96 Payrolls........................ 97 Analysis of the Statistical Measure ments ............................. 98 "K” Value and Population Growth . . . 101 Keynesian System and "K" Value . . 102 High Level of Income and Decline in Population................. 105 X. THE ECONOMIC BASE THEORY VS. STATIS TICAL APPROACH................. 106 Major Weaknesses of the Economic Base Theory....................... 106 vii CHAPTER PAGE Instability of the Base-Service Ratio ........................ 107 Assumption of Automatic Mechanism . 108 Constituents of the Basic and Service Activities ............ 109 Cost of Field Surveys............ Ill Empirical Evaluation of the Economic Base Theory...................... 112 Economic Base and City Growth: Employment as the Measure .... 112 Economic Base and City Growth: Payrolls as the Measure . . . . . 114 Appraisal of the Base-Service Concept........................ 115 Pure Statistical Approach .......... 117 Elements in the Pure Statistical Approach...................... 118 Correlation analysis .......... 118 Determination of trend........ 119 Population Projection ............ 121 Employment Distribution .......... 122 Urban Land Use Planning.......... 123 XI. SUMMARY AND CONCLUSIONS.............. 125 Summary............................ 125 viii CHAPTER PAGE Percentage of Employment, Its Growth Rate, and City Size .... 125 Rate of Population Growth and Rate of Growth In the Percentage of Ernployment...................... 125 Size of the Percentage and Employ ment Fluctuations .............. 126 Employment Growth and Population Growth........................... 126 Income Growth and City Growth . . . 127 Employment Distributions .......... 127 Conclusion.......................... 128 BIBLIOGRAPHY................................... 132 APPENDIXES..................................... 140 Appendix A: Manufacturing Employment and City S i z e .................... 145 Appendix B: Retail Employment and City S i z e ......................... 180 Appendix C: Wholesale Employment and City S i z e ......................... 190 Appendix D: Service Employment and City S i z e ........................ 216 CHAPTER Ix PAGE Appendix E: City Size and Employment in Manufacturing Industry, Retail, Wholesale, and Service Trades: Multiple Correlation Analysis . . . 234 Appendix F: Analysis of Employment in Manufacturing Industry, Retail, Wholesale, and Service Trades Combined, and City Size......... 244 Appendix G: Income and City Size . . 279 LIST OP TABLES TABLE PAGE I. Summary of the Results of the Statistical Analysis of Population and Manufacturing Employment......... 41 II. Summary of the Results of the Statistical Analysis of Retail Employment........................... 57 III. Summary of the Results of the Statistical Analysis of Wholesale Employment........................... 66 IV. Summary of the Results of the Statistical Analysis of Service Employment........................... 74 V. Summary of the Multiple Correlation Analysis for Employment Growth and City Growth......................... 84 VI. Summary of the Results of the Statistical Analysis of Employment in the Pour Industries Comhined . . . 90 VII. Payroll and Population Indexes, 1935- 1958 (1935 = 1 0 0 ) .................. 99 VIII. Base-service Identification for the Pour Industries During the Examination Period ..................... 113 xi TABLE PAGE IX. Base-service Identification by Using Payrolls of the Pour Industries as the Unit of Measure................ 116 LIST OP FIGURES FIGURE PAGE 1. Comparison of the Growth Rates of Manu facturing Employment for the Sixteen Cities and the Nation................... 43 2. Comparison of the Growth Rates of Manu facturing Employment for Group I Cities . 46 3. Comparison of the Growth Rates of Manufacturing Employment for Group II Cities................................. 46 4. Comparison of the Growth Rates of Manufacturing Employment for Group III Cities ,................................. 47 5. Comparison of the Growth Rates of Manufacturing Employment for the Group IV Cities............................... 47 6. Comparison of the Growth Rates of Manufacturing Employment for the Cities with High Rates of Population Growth (80# or more)........................... 49 7. Comparison of the Growth Rates of Manufacturing Employment for the Cities with Low Rates of Population Growth (12# or less)........................... 49 xiii FIGURE PAGE 8. Patterns of Growth In Manufacturing Employment for the Sixteen Cities and the Nation, 1929-1957 .................... 51 9. Patterns of Growth in Retail Employment for the Sixteen Cities and the Nation, 1929-1957 ................................. 61 10. Patterns of Growth in Wholesale Employment for the Sixteen Cities and the Nation, 1929-1957 ................................. 69 11. Patterns of Growth in Service Employment for the Sixteen Cities and the Nation, 1929-1957 ........................ 78 CHAPTER I INTRODUCTION I. GENERAL STATEMENT "Look now toward heaven, and tell the stars, if thou be able to number them, . . . , So shall thy seed be. . . . I am the lord that brought thee out of Ur of the Chaldees, to give thee this land to inherit it.1 1 * Thus, from early human history, we see a close relation ship between population and wealth. In proposing the attraction of a greater number of foreigners to Athens and granting privileges to merchants, Xenophon, as early as in 355 B.C., clearly related prosperity with 2 population and wealth. More recently, we see the same underlying idea from Malthus if we narrow the concept of wealth to the means of subsistence. Today a great majority of the population in the United States is living in urban areas. As the way of living and the structure of wealth have become more complex, scientific methods of explanation have been Genesis, XV, 5 and 7. 2Arthur E. Monroe (ed.), Early Economic Thought (Cambridge: Harvard University Press), 1951)* PP* 3?**38. sought to be incorporated in the economic policy to bring about prosperity and welfare of the population. All economic policies thus far advocated can be reduced ultimately to an attempt for maintaining a properly balanced relationship between population and income. During the 1930's the economic base theory was first enunciated and has been accorded widespread acceptance. The economic base theory is a system of logic that was Intended to explain urban growth. During the 1930's when it seemed that a proper balance was missing between population and income, the need for an explanation of urban growth was strongly felt. In this respect, the economic base theory was not unlike the General Theory of Keynes which linked an increment of new activity with the generation of expansion in the national product. The development of the economic base theory was thus a product of the times. II. STATEMENT OP PURPOSE OP THE STUDY Although the relationship between population and Income (or wealth In other forms) has been stated since early times, a more precise functional relation ship has not been examined through wide empirical studies. For more adequate policies or planning, the major premise should be tested empirically and the degree of functional relationship, if it exists, must be determined. The major objective of this study is to empiri cally test the economic base theory which was found on the belief that income growth and population growth are functionally related. An incidental result of this test is to provide an empirically sound method to assist the urban land planner to optimize his allocation of space in his plans. For example, if the urban land planner has a good knowledge as to the future growth in, say, manufacturing employment and land requirement per employee, he has the first-hand assistance in his land planning process. To accomplish the twofold objective stated above, the present study involves a study of the relationships between (l) employment and population growth, (2) income and population browth, and the characteristics of employment composition and their changing patterns, on the city level. III. DEFINITIONS OF TERMS USED Economic base theory. The economic base theory is a system of logic that was intended to explain regional growth. The main properties of the theory are the basic and service activities and the base-service ratio which explains the quantitative relationship between the basic activity and the service activity. Basic activity. The basic activity constitutes the economic base of a community. It was defined as the activity which can command income from beyond the borders of a community. Service activity. Economic activities of a community that are not basic activity are termed as service activity. Thus, production of goods and services locally consumed, plus activities engaged in importing goods and services from outside the community belong to service activity. Base-service ratio. The base-service ratio measures the quantitative relationship between the basic and service activities. The ratio may be expressed in terns of employment, income, output, or any other appropriate unit of measure. Thus, if, for instance, the service activity employs twice the number of persons employed in the basic activity, the base-service ratio would be 1:2. Community income multiplier. Community income multiplier is similar to the concept of the base-service ratio. It is a device to measure the ultimate magnitude of a community's income derived from the basic activity. Statistical approach. Statistical approach in this study means an empirical study conducted by making use of the usual statistical techniques. The main statistical techniques used in this study are correlation and regression analyses. IV. THE SCOPE OP THE STUDY An adequate amount of factual information is vital for empirical studies. The lack of factual data available for an adequate examination has severely limited the scope of this study. Limitation of Statistical Data Statistical information gathered by different organizations for different purposes from the same population usually result in discrepancies due to definitional differences and/or different methods of survey used. Therefore, this study made use of the U.S. Census data exclusively. Even so, there were numerous definitional changes encountered in time series data. For the examination of employment distribution, only four categories were used in this study, namely: manufacturing, retailing, wholesaling, and services employment. For this kind of study, it is desirable to Include a much wider range of employment categories. However, for other than these four categories, either (1) the number of censuses taken is so few or else, (2) no statistics for various cities selected for inclu sion in the study were available. The U.S. Census of Manufactures had started long before the turn of the century, but the Census of Business (which includes retail trade, wholesale trade, and service trade) did 3 not start until 1929. Therefore, the period of investigation in this study included the years between 1929 and 1958. Although the validity of this study is limited due to the lack of available statistics and inability to obtain information for other employment categories, an examination of the four categories cited is very important in understanding the economic characteristics of the major cities in the United States, for the employment in those four categories accounts for well ^statistics for service trade before 1933 are not available. The Selected Services of the Census of Business includes hotelservice, service in tourist courts and camps, personal service, miscellaneous business services, crematories, auto repair, auto service, garages, miscellaneous repair services, motion pictures, amusement and recreation services. 7 over 60 per cent of total urban employment for the nation in recent years and half of the cities under examination were close to the national average and the other half were higher than the national average. Thus, on the average, employment in manufacturing industry, retail trade, wholesale trade, and service trade combined, accounted for between 65 and 70 per cent of the total employment of the cities under investigation. A study of employment of the main urban industries that account for more than three-fifths of the urban employment, therefore, is believed to shed important light in understanding of urban employment, income, and population relationships. Difficulty Arising from the Definitional Differences Although the U.S. Census data are most reliable and widely used for various purposes, many researchers who use such data often face difficulty due to the definitional differences from one census to another. For Instance, the manufacturers’ sales branches were not included in the wholesale trade in earlier censuses. There is no valid way to reconcile such definitional differences. However, the discrepancies in the figures arising from such definitional differences were not too significant during the period of examination for the present study. Some censuses made distinction between full-time employment and part-time employment, but In others the employment figures were given under the heading "Paid Employees" or "Total Employment." Therefore, the entire employment, whether part-time or full-time, was used in this study. Still another problem that arises from defini tional differences was that employment in each industry was (l) the yearly average in sane censuses and (2) employment at the weekend nearest to November 15 of the census year in others. This study was compelled to ignore such all of the foregoing definitional differences although they no doubt influence in some degree the nature of the findings. Basis of Selecting Areas for Examination In this study sixteen cities were selected for examination. The basis on which the selection of the cities had been made was the size of population. Small cities usually have some peculiar characteristics as to the makeup of population and employment. For instance, a great majority of the population of a community may consist of retired pensioners, or the main Industry of a seaboard town may be fishery. For communities that have some unique characteristics, the study of employment typical of urban localities in general will be of little importance. Therefore, large cities were selected in this study in belief that their main employment generating (and therefore income generating) industries Involved in the four categories of industry mentioned above. Considering these problems, five cities having population in i960 between 450,000 and 600,000 were selected as the Group I cities. Three cities in the same range of population were selected for the Group II cities. The difference between the Group I and Group II was that cities belonging to the Group I have not so far undergone a population decline during the current century, whereas the cities in the Group II have 4 undergone a population decline during the 1950's. The reason for making such a distinction between the Group I and Group II cities lies in the interest of an examination whether there is a marked difference between cities that have enjoyed a continuous increase in population and those that have not. ^*Two more cities were available for the Group I but they had unusual population growth, and it was believed that five cities were enough for a comparison within this group. The three cities in the Group II were all that were available with the Group II characteristics. 10 For cities that have larger population had also been selected for an examination, and they were included in the Group III. This group of cities had a population size between 800,000 and 950,000. For the Group III size of population, a distinction between those cities that have continued population growth and those that have not could not be made because three cities included in the Group III were all of those that were available within this population size. It was awkward to leave out the major cities all of which had population of over one million as of I960. Therefore, all cities with population of over one million were Included in the Group IV without regarding the size, growth or decline, and the growth tempo, of the population. In the Group I, were Memphis, Tennessee (97 per 5 cent); Atlanta, Georgia (80 per cent); Columbus, Ohio (62 per cent); Seattle, Washington (52 per cent); and Denver, Colorado (37 per cent) Included. The Group II included Cincinnati, Ohio (11 per cent); Minneapolis, Minnesota (4 per cent); and Buffalo, New York (-7 per cent). Houston, Texas (221 per cent); Baltimore, -*The percentage figures Indicate the Increase or decrease in population during the period between 1930 and i960. 11 Maryland (17 per cent); and Cleveland, Ohio (-3 per cent) were included in the Group III. The Group IV consisted of Los Angeles, California (100 per cent); New York, New York (12 per cent); Detroit, Michigan (6 per cent); Chicago, Illinois (5 per cent); and Philadelphia, Pennsylvania ( 3 per cent). V. ORGANIZATION OP REMAINDER OF THE THESIS This study is directly related to the eoonomic base theory. In fact, it is an outcome of reaction to the theory. Therefore, it is necessary to state the fundamental concept of the economic base theory. This is done in Chapter II, which summarizes the economic base theory as thus far developed and its use In the planning process. The methodologies used In this study are briefly stated in Chapter III. It was felt that this statement of methodology is very important because the results of the statistical analysis depend much upon the specific methods used. If one rejects the methods used herein, the results of the analysis must also be rejected. Thus the importance of the methods cannot be overemphasized. Chapters IV, V, VT, and VII are concerned with the analysis of the relationship between city size in terms of population and manufacturing employment, retail employment, wholesale employment, and service employment, respectively. These four chapters are largely the conclusions of the statistical analyses made in Appendixes A, B, C, and D. The relationship between the city size and the total employment of the four industries combined was analyzed in Appendixes E and P and the results of the analysis were summarized and analyzed in Chapter VIII. Chapter IX studies the relationship between income and city size. The statis tical measurements were provided in Appendix G. Thus, Chapters IV through IX are the summaries and conclusions of the results of the statistical measurements made in Appendixes A through G. The relationship between the economic base theory at the current status and the statistical approach of this study necessitates a revision of both approaches and a comparison between them. This is done in Chapter X. Chapter XI, the concluding chapter, is simply a brief summary of the whole study because the main conclusions regarding employment in each category and the four combined, income, and city size were made in each corresponding chapter. Appendixes A through G are not merely supplements to the main body of the study. As mentioned above, each corresponding chapter is largely the summary of the statistical analysis made in the Appendix. The basic statistical information and analysis of each subject were provided in appendixes in order to make it readable without much interruption in each chapter. CHAPTER II CURRENT STATUS OP THE ECONOMIC BASE THEORY This chapter Is intended primarily to state the concept of the economic base theory developed so far. Any comments on the shortcomings or feasibility of it will be reserved until Chapter IX where the comparison between the economic base theory and the statistical approach proposed in this study is discussed. I. BASE-SERVICE CONCEPT Inasmuch as Homer Hoyt is the pioneer of the economic base concept for urban economic analysis, it seems proper to see his idea to obtain the fundamental concept of the economic base theory. He stated that "A particular city must be able to command a stream of income from beyond its borders if it is to be founded at 6 all." Prom Hoyt's words quoted above, we may deduce that the larger the volume of income a city can command, the better and the more prosperous the city will be. According to the economic base theory, the extent of the g Arthur Weiman and Homer Hoyt, Principles of Real Estate (New York: The Ronald Press Company, 1939)* p. 27. 15 ability of a community to command Income from beyond its borders determines the total employment and income of the community. Therefore, the growth in such an income-commanding ability is the cause of a community's growth (population growth). The source of commanding income from beyond the city borders is conveniently termed as "basic activity," "economic base," or "town-builder." All other activity that is not the basic activity is called "service activity" or "town-filler." Thus, a community's economic activity is consisted of basic activity and service activity. Basic Activity Generally speaking, a community must export goods and services in order to command income from beyond its borders. Therefore, the basic activity is also called "export activity." This export activity may involve in three general kinds; namely, (l) export of goods, (2) export of service, and (3) export of capital. Activities involved in exporting goods are undoubtedly the most important part of the economic base. The resident individuals or organizations may export goods to other communities, or non-residents may come in and make purchases of local goods within the l6 borders. In either case the net result is the same as far as export of goods is concerned. Activities involved in exportation of services constitute another part of the economic base. To some communities, this sort of activity may be more important than exportation of goods. For instance, if the main source of deriving income from outside is work in resort and amusement, the service to visitors, such as hotel service, restaurant service, etc., will constitute the main part of the community1s economic base. If a town exists primarily because of a large educational institution, such as a university, most of the students are expected to be those who come from other communities. Their stay in the town where the school is located is temporary; and they receive educational service within the town. From the point of view of the town, it exports service to non-residents. In the above two examples, the export of service is done in the form of "people to service" in the sense that the non-residents come into the town to receive service. Export of service may take another form, namely, "service to people." For instance, doctors may get house-calls from residents of adjacent communities. Their service to non-residents constitute exportation of service in the form of "service to people." A more 17 important kind of ejqaorting service for certain commun ities, small communities located near a large city in particular, is commuters. If a substantial number of the residents of a community hold their employment outside its borders and draw incomes, this kind of service exportation constitutes an important part of the community’s economic base. The third kind of activity in the economic base is those activities engaged in exportation of capital. Although this is the least important sort of basic activity for most communities, it may be one of the main source of commanding income from beyond its borders for some particular communities. For example, if a small community has many rich residents and their investment in other communities amount to a substantial magnitude, the income derived from such investment will be an important source of income from outside. For small communities which consist to a great extent of retired pensioners, the payment of such pensions to them will be an important part of the community's income from outside. Though many of such people may have moved into the community after or upon their retirement, it is appropriate to classify this as an exportation of capital because the end result is the same as that of.capital export in any form, i.e., it brings income into the 18 community. Thus, as read in Hoyt's statement, the importance of the economic base lies in the ability to draw income from beyond the borders of a community. Service Activity That part of a community's economic activity which is not involved in export activity is service activity. Certain amount of service activity exists to support the basic activity. For instance, people working in a manufacturing industry whose products are primarily exported must be consuming local goods and service, such as food, rental service, etc. Activities engaged in supplying such needs are local and no exportation is involved. The other part of service activity is those activities involved in importing goods, service and capital from outside the community for local needs. Thus, the two general types of service activity are (l) service activity involved in goods fabrication, service production, capital origination and distribution which are entirely local and no importation of any significant extent, and (2) service activity involved in importing goods, service and capital. 19 II. IDENTIFYING AND MEASURING THE BASE Identification It is an enormous task to examine every industry to determine the economic base for a community of any considerable size. Practically, any industry can and may be involved in basic activity in one form or another. Therefore, it has been the practice to survey only those industries which are understood to be constituting important parts of the economic base of a community. Hoyt, for instance, includes in the basic activity type (l) manufacturing, (2) trade and finance, (3) extractive industries, (4) governmental activity, (5) educational institutions, (6) resort and amusement centers, and (7) retirement. Not all of the above seven types will be important for every community. For Washington, D.C., for instance, only the governmental activity may constitute the main part of the basic activity. For most large cities in the United States, extractive industry would be negligible. Even for a single category, such as manu facturing, it may be virtually impossible to assess all information. Therefore, the selection of the different 7 Ibid., p. 34. 20 basic activity types and the sub-types within a selected basic activity type should be done at the discretion of the prudent planner's Judgment in the light of the specific situation of a particular community. Measurement Once the selection of the basic activity types has been made, the next problem is to measure the magnitude of each activity selected. There are a number of devices of such measure. Andrews cites six different units of measure thus far in the development of the urban economic base concept, namely (l) employment, (2) payrolls, (3) value added, (4) value of production, (5) physical production, and (6) community income and 8 expenditure. This is no place to review the merits and demerits of each of these six units of measure. Employ ment as a unit of measure has most conveniently and widely been used. With employment as a unit of measure, some simplified devices have been utilized. Here will be Introduced only two such techniques, namely the location quotient and the index of surplus labor. q Ralph W. Pfouts (ed.), The Techniques of Urban Economic Analysis (New Jersey: Chandler-Davis Publishing Company, 19t>o), p. 67. 21 Location quotient. The location quotient as a short-cut method of Identifying the economic base of community is expressed as local employment in a given Industry L.Q. = national employment in the same Industry total local employment total national employment If the location quotient is greater than 1, that industry is involved in the basic activity of that community.9 As readily seen in the above formula, it is valid only if the basic activity of a community is always relatively larger than the national average. If, for instance, a particular industry is involved in the basic activity of a community and yet it employs relatively less than the national average, the location quotient cannot identify this industry as the basic activity. Index of surplus employment. According to the location quotient method, an industry may or may not be 9it has been argued whether a quotient greater than one can identify the economic base. Therefore, Hildebrand and Mace, in their study of Los Angeles County used 1.5 instead of 1 as the basis. George H. Hildebrand and Arthur Mace, Jr., "The Employment Multiplier in an Expanding Industrial Market: Los Angeles County, 1940- 1947*" Review of Economics and Statistics, XXXII (August, 1950), pp. 241-249. 22 identified as a basic activity depending on whether 1 or any other number is taken as the basis (see footnote 9). To avoid this troublesome problem, am alternative technique, namely, the index of surplus employment has been devised. The basic assumption made for this technique is the same as that made for the location quotient technique. The formula of the index of surplus labor is n t S = n± - (------ x N.) Nt where S = Index of surplus employment, n.= local employment in the 1 industry of a community, Ni= national employment in the same industry, nt= total local employment of the community, N = total employment of the nation. w Thus, if the S shows a positive value it i3 supposed that the industry is basic; and if negative, it is identified as non-basic. It is not necessary that the above formula should U3e employment as the unit of measure. Income derived from an industry, for instance, can be used in place of employment of that industry, or any other unit of 23 measure may be substituted In the same manner. III. CONCEPT OP ECONOMIC BASE RATIO A definite functional relationship Is assumed to exist between the economic base and service activities. This relationship is called base-service ratio. By taking the basic activity component of a community as a constant, or one, the service activity component is made as an economic function of the base. Thus, the ratio of the base to service may look something like 1 : I1/ 2, 1 : 2, 1 : 2^ 2, or 1 : 3, etc. The specific ratio must depend upon the economic conditions of a community and it will also vary as the general economic conditions and other component parts change.3’ ^ The concept of the ratio of the basic activity to service activity is further extended and related to total population and employment of a community. Thus, a complete set of ratios of an hypothetical community would appear as; Base : Service =1:2 therefore, Base : Employment =1:3 1<3Por city planning purposes, however, a certain ratio computed from a survey of the base-service situation is frequently expected or assumed to be stable at least for a considerable period of time. 24 and, Employment : Population =1:2 therefore, Base : Population =1:6. Since a functional relationship Is believed to exist between the base and service, quantitative reactions in the service components are assumed to take place when the basic activity undergoes quantitative changes. An important assumption made here by supporters of the base-service ratio theory is that the corresponding quantitative changes in the service activity due to the quantitative changes in the basic activity come about sooner or later not through conscious activities but through rather automatic chain reactions. If the above set of ratios were assumed for a particular city, for instance, an addition of 1,000 workers in the basic activity will sooner or later increase automatically the employment in service activity by 2,000 and population by 3*000. The increase in population by 3*000 plus 1,000 workers in the basic activity and its corresponding increase in employment in the service activity by 2,000 will make the total addition to the city's population by 6,000. IV. COMMUNITY INCOME MULTIPLIER: A KEYNESIAN MODEL The importance of the basic activity lies in its 25 ability to command income from beyond the boundaries of a community. The income thus derived is expected to yield various repercussions and raise the total incomes and employment of its residents. The problem is to determine to what extent the income brought in from outside will increase the total income of the community. It is clear that the Keynesian model can fit here well. A simple Keynesian model can be set as: Yt = C + Yb C = f(Yt) Yt is the total community income, C the consumption expenditure by the residents,and Y^ the income derived from the basic activity. Since we are interested in knowing the ultimate magnitude of the community income, we will have to know what portion of income will be spent on the local products because a certain amount of the income will leak out of the community via payments of wages to non-resident employees, payment for raw materials imported from other communities, consumption expenditure by the residents on non-local products, etc. This is clearly the problem of determining the community income multiplier k. Thus, we have narrowed the problem to be finding the value of the multiplier k. The above siiqple model can be rewritten as: = xb + *s Ys = f(Yt) where Ys is income derived from service activity. Once the ratio of income from the basic activity to that of service activity is determined, it is assumed to hold for all levels of income. This assumes that the marginal propensity of the residents to consume local products is constant and also equal to its average propensity to consume. Thus, the base-service function reduces to a simple linear function Yg = A + bY^. The assumption of equality between the marginal propensity and the average propensity to consume local goods and service will make the value of the intercept A, zero. The coefficient b may be interpreted as the propensity of the residents to consume local goods and service. Through field surveys, total community income Y - j . and income originating in the service activity may be found. Then, the coefficient b can be computed from Ys = A + bYt. Since A =0, 27 Once the value of b Is given, the multiplier k is easily determined in usual way. Thus, 1 What it actually means above is this: If the basic activity draws certain amount of income from outside the community, only a portion of it will be spent on local goods and service and this portion only is subject to multiplier k. As an example, if the propensity of the residents of a particular community to consume local goods and service is .1 or 10, the income multiplier will be 1.11. If the basic activity draws an addition of $1,000 income, it is expected ultimately to increase the community income by $1,110 (including the original $1,000). For any community other than a town which is largely made up of not well-to-do retired pensioners, the net increment in income due to the basic activity may not be expected to be very high because of large leakage via payment of wages to non-resident employees, payment for raw materials imported from other communities, consumption e^qsenditure on non-local goods and service, etc. 28 V. ECONOMIC BASE THEORY AND CITY PLANNING The fundamental goal of city planning is the making of the city a better place to live, recreate, and work. In more precise terms, the objective of city planning is to arrange the physical plant and the layout of the city in which the population lives so that it will minister to and promote rather than impede the social and economic welfare of the community. Master Plain Economic base theory is primarily concerned with the drawing of a master plan for a community. Bettmam and others define the master plain as: A plan setting forth the general location and extent of the physical development of the city or other unit for a considerable period of time. It embodies the interrelationships between different functional classes of public improvements, streets, pairts, riverfront structures, aurid locations of residential, business, industrial, etc., aireas, based on studies of the needs through a considerable period of tlme.H The economic base theory gives some rough guidance but tells little about specific and detailed 1]-Alfred Bettman and others, City and Regional Planning Papers (Cambridge: Harvaird University Press, i94br )'r p. 42; 29 problems. Specific problems pertinent to a particular community must be solved in the light of specific situations and conditions of that community within the master plan. "The present status and anticipated trends of the urban economy . . . are the basis for forming and ultimately changing the details of the community master plan. ' ' 12 Economic Base Theory as an Aid to Planning It is then necessary to know exactly what the economic base theory does or in what way it becomes an aid to planning. It has been believed that the urban economic base has a direct long-run influence over the size quantitative and the social qualitative makeup of the community population. The resulting quantitative and qualitative changes in turn determine the detailed needs and demands for a special combination of land uses. As to these needs and demands, two attitudes have been taken by planners. One is a passive attitude, i.e., the planners take it as their responsibility to understand the urban economic problems and plain to meet the future needs and demands based on their prediction. 12Pfouts, 0£. cit., p. 155. 30 For instance, if population increase of 100,000 is expected in five years, they would estimate residential land requirements and its location, corresponding needs for new streets and roads, sewage extension, availability of electric power and water, etc., and plan to meet such needs. On the other hand, the planners who take a positive attitude will attempt, in addition to the above, to change the forces that will influence future demands. For an example, if a quantitative change is desired, such as an increase in employment and aggregate payrolls, the planners would plan so as to assist in increasing the basic activity. If we assume a functional relationship between the base and service in terms of employment being 1:2, a positive plan to increase the basic activity will bring about another increase in service activity which is twice that of basic activity. In many instances, productive and locational factors might be partly under the control of the locality. The planner in such a situation has a chance to influence market directly by specific planning programs, such as expanding or creating out-of-door parking, recreation, and general scale of personnel service. The locality can also assist local industry actively and attract new industry through promoting 31 locational advantage, proper zoning of adequate space for industrial and commercial areas, tax considerations, and the like. The locality can also encourage increased service activity independently if it wishes not to increase imports which are expected to accompany an increase in the basic activity. This is equivalent to increasing the multiplier k, as we have seen in the previous section. Decreasing imports makes the income leakage smaller. Emphasis on one or only a few particular industries that have comparative advantages in order to increase the basic activity may result in inefficiencies as a point of diminishing returns is reached. Planners who desire to increase the total volume of employment and payrolls as well as the economic stability of the community may aim at a more balanced emphasis on a wider range of the basic activity. CHAPTER III METHODOLOGY The statistical analysis of the same population often yields different results if different methods of analysis are used. Using the same statistical information used in this study, one may come to different conclusions if different methodologies are taken. Therefore, the nature of this study necessitates specifi cation of the methodologies used. In this chapter, the techniques chosen for the analysis are specified. I. ASSUMPTIONS The population census has been taken every decennial year; but the Censuses of Manufactures and Business have not been taken so regularly although the intervals between Censuses (manufacturing and business) were smaller than that of population censuses. As mentioned In Chapter I, the number of censuses taken was so few and irregular that it was necessary to assume that population and employment increased or decreased at constant rates between census years. The statistical analysis made under this assumption would yield no valid results needed for an explanation of intercensal phenom ena nor can trends be deduced over a period covering a 33 few observations only. However, the present analysis is believed to be satisfactory for detecting the rela tionship between employment and income and city size over a period of time of considerable length. Statistical information for manufacturing employment, retail employment, and wholesale employment was available for the year of 1929, but the earliest employment statistics for service trade was 1933 census data. In order to keep the length of the period of examination uniform for the four employment categories, the average of 1933 and 1935 census figures or the aver age of 1933, 1935, and 1937 census figures was used for 13 1929. There is no logical reason to believe that the level of service employment of 1929 was the same as such an average. However, there is strong reason to believe that the probable error involved in the analysis made under this assumption would be very small. As seen in Appendix D, the percentages of service employment among population in most cities were less than one per cent during the early part of 1930's and they have 13 For the cities where the percentage of service employment on the whole is not large, the average of 1933 and 1935 employment was used for 1929; and for the cities where the percentage of service employment is rather significant, the average of 1933, 1935, and 1937 was used for 1929. almost steadily Increased as time passed. The low per centages as time progressed are the most reasonable trend for service employment because of the types of employment Included In the service trade (see footnote 3). If this is agreeable, there is reason to suppose that the level of service employment in 1929 was not high. It Is not reasonable, however, to suppose that the level of service employment in 1929 was not higher than 1933 because the depression hit about hardest in 1933. Therefore, the average of 1933 and 1935 or 1933* 1935> and 1937 employment figures was used for 1929. At any rate, the difference between the estimate for 1929 and what should have been should be far less than one per cent for all cities. Therefore, the estimates made under the assumption should not damage the results of the analysis to any meaningful extent. II. ANALYSIS OP EMPLOYMENT IN A SINGLE INDUSTRY The analysis of employment in a single industry is made in Chapters IV through VII. The basic method ology to determine the relationship between employment and city size is the percentage analysis— the percentage of employment among population. Since it is expected -that the percentage of 35 employment among populations differs from one city to another even for cities of similar size, the Interest of the analysis rests on the comparison of the patterns of the percentage changes. The most convenient way for such a comparison would be to compare the rates of changes in the percentages. Thus, a time series analysis was made to determine the trend in the per- 14 centage changes and the trend function N_ was differ- v entiated with respect to time X (independent variable). Thus, d (A + bX) = b dX where A is the constant equivalent to the mean of the 15 percentages of employment during the period of exam ination and the parameter b shows the degree of the slope or the trend line or the rate of change in the 14 Although a curvilinear equation would fit the actual percentages more closely and give smaller standard error of extimates, the linear equation was used, for there is no logical Justification for fitting curvature. "^From the "normal equations" H X= EinA + bziX and e x n = A e X + bcX2, we get 2 zN=riA andEXN=bcXa , where N is the percentage of employment and n is the sample size. Because of transforming the scale of the independent variable, eX is always equal to zero. Thus, A=-^— = N. percentages.1^ 36 II. ANALYSIS OP EMPLOYMENT IN THE POUR INDUSTRIES COMBINED In Chapter VIII the analysis of the total employ ment (of the four industries) and city size was made. The purpose of the chapter was two-fold. One was to determine how closely employment and population move together. The method used was the multiple correlation (and regression) analysis. The other was to see the importance of the four industries as the employment generator. Here the method was the same as the one used for a single employment category. III. ANALYSIS OP INCOME AND CITY SIZE The relationship between income and city growth was analyzed in Chapter IX. The basic methodology used was simple correlation analysis. The specific method used in this analysis was concerned with the refinement of statistical variables. •^Two years were taken as IX, for the averaging effect in the absence of an adequate number of sample population would not give any more refined measurement even If one year was taken as IX. 19^3, the midyear, was taken as OX or the origin. Although Income of a community is one thing and the payrolls of the residents of that community is another, the total payrolls (of the four industries) were used for two reasons. In the first place, the U.S. census gives no information as to the income derived from each industry. In the second place, even if such information were available payrolls are preferred, because income derived from industries within a community may not become the community's income in its entirety. The proflt-sharers of large concerns sire generally scattered around the country. The majority of the employees, however, is expected to be the residents. Because of the fluctuations in the price level, the total payrolls were divided by consumer price index (1947-49 = 100) to get payrolls in constant dollars. Since service census was not available before 1933 and no Census for Manufactures was taken in 1933, the total payrolls for the year of 1935 were the earliest one that could be used for the suialysis. Both the Census of Manufactures and the Census of Business were taken in 1939* 1954, and 1958, and Manufactures in 1947 and Business in 1948. Although the Census of Manufactures and that of Business soon after World War II were taken In two different years, it was treated as if they were done in the same year (or between 1947 and 48). The payrolls of 1939, 1947-48, 1954, and 1958 were divided by the payrolls of 1935 to get the payroll index. The same thing was done for population for the corresponding years to get the population index. It would be meaningless to compare these two indexes directly, as the income index rises much faster than the population index in the United States where economic growth is comparatively high. In order to obtain the highest possible correlation coefficients between the increases in the payroll index and the population index, the increase in the payroll index over the base (1935) for each census year was divided by the corresponding population index and the average of the quotients (K in 17 Table VII) was obtained. The payroll index of 1939, 1947-48, 1954, and 1958 was divided by this average and thus was obtained the "modified payroll index" (see Tables CXII through CXXV). Therefore, the correlation analysis was made on the increases in the population index and the modified income index over the respective bases. In the case of employment analysis, it will be recalled, comparison was made between population-size 17 The average was not mean. It was somewhere between the mode and the mean of the mean, median, and mode. groups. In the income analysis this was not done. Instead, all cities were divided into two groups (l) those cities with steadily increasing in both the population index and the payroll index, and (2) those cities which declined in either or both respects during the examination period. Since cities were classified into two groups, the examination of all the sixteen cities was not necessary. Therefore, Buffalo, Cleveland, and Baltimore were omitted. The main reason for omitting Buffalo and Cleveland was that their population index fell below 100, that is, negative increase over the base. Baltimore was dropped because the census for wholesale trade for the year of 1954 was not available. CHAPTER IV ANALYSIS OP MANUFACTURING EMPLOYMENT Manufacturing industry offers the largest single employment opportunity for most large cities and for the nation. An examination of manufacturing employment in relation to population, therefore, is important in understanding the characteristics of employment. The purpose of this chapter is to examine the relationship between manufacturing employment and city size in terms of population and to compare the pattern of change in such relationships among the sixteen selected cities and the national average. II. SUMMARY AND ANALYSIS OF THE STATISTICAL MEASUREMENTS The original sources of information and statis tical analysis are given in the Appendix A. In Table I the results of the statistical analysis are summarized. In Figures 12-A through 28-A (see Appendix A), the general trend is that the distance between the population and manufacturing employment curves for each city and the nation is narrowing as time progresses during the 41 TABLE I SUMMARY OP THE RESULTS OP THE STATISTICAL ANALYSIS OP POPULATION AND MANUFACTURING EMPLOYMENT Percentage Mean of Rate of per- City Increase In percentage centage changes population (A) (b) Memphis 97 7.31 .310 Atlanta 80 9.20 Columbus 62 10.30 .486 Seattle 52 9.00 .740 Denver 37 6.04 .275 Cincinnati 11 15.43 .456 Minneapolis 4 9.27 .566 Buffalo -7 12.20 .430 Houston 221 6.20 .263 Baltimore 17 11.09 .273 Cleveland -3 18.65 .752 Los Angeles 100 7.99 .610 New York 12 9.59 .440 Detroit 6 15.03 .272 Chicago 5 14.15 .595 Philadelphia 3 13.26 .360 United States 40 14.30 .370 18 period of 1929-58. This trend is expressed in the positive values of the rate of changes in the percentage (b) for all cities and the nation in the Table I. Findings regarding the relationship between manufacturing employment and city size among the selected cities and the nation were based on the above summary table. National and City Patterns The rates of increase in the percentage of manufacturing employment (b) for the selected cities and the nation are graphically compared in Figure 1. It was found that two-thirds of the cities examined have performed higher than the national average as far as the rate of growth in manufacturing employment relative to population is concerned. Cities that had a rate of growth in manufacturing employment (b) smaller than that of the nation are Memphis, Denver, Houston, Baltimore, Philadelphia, and Detroit. Although a few cities have had very high rates of increase comparatively, the real difference for practical purposes seems to be very small. The •*-®This trend was observed only during the period mentioned above. If we take a different period of time, the result would be different. This matter will be discussed later in other chapter. FIGURE 1 COMPARISON OF THE GROWTH RATES OF MANUFACTURING EMPLOYMENT FOR THE SIXTEEN CITIES AND THE NATION difference between the highest and the lowest growth rates is .480. This figure is by no means a large one. For all practical purposes, the growth rates (in terms of b) differentials within the range of .5 should be regarded as fairly uniform. An example will make this point clearer. If we take two cities with 500,000 population and assume that the difference in the growth rates is .5 and that the patterns established in the past would continue in the future for some time, the expected difference in the percentage figures in ten years would be 2.5 per cent and the numerical difference 19 in the manufacturing employment would be 12,500. For cities of one half million population, 12,500 difference in manufacturing employment in ten years cannot be regarded as large. Thus, when we interpret the statistical measure ments in a practical manner, we may conclude that the major cities in the nation do not differ much from the national average and they have experienced a rather uniform growth in manufacturing employment during the period of 1929-57* 19 Since two years were taken as one X, ten years would give a value of 5 for X. Therefore, bX or *5(5) = 2.5, and 2.5# x 500,000 = 12,500. 45 Manufacturing Employment and City Size The average level of manufacturing employment relative to city size differs considerably from one city to another. As seen in the Table I, no uniformity was found among the sixteen selected cities or within each population group. The rates of growth (the last column of Table l) of each population group were graphically presented in Figures 2 through 5, ignoring the values of A. As observed in these Figures, there seems no greater uniformity within each group than among all cities except for the Group II cities. The range of difference in the growth rates within the Group II is .136, which is very small. On the other hand, the two extreme cities, Cleveland with .752 and Houston with .263, are found within the Group III. The differences between the highest and the lowest growth rates within Group I and Group IV are .465 and .338 respectively. Thus, it seems from the analysis that any closer similarity found within any particular population group is merely accidental. High and Low Rates of Population Growth and the Rates of Growth in Manufacturing Employment Cities that had very high rates of population growth (80 per cent or more) and very low rates of 46 FIGURE 2 COMPARISON OF THE GROWTH RATES OF MANUFACTURING EMPLOYMENT FOR GROUP I CITIES FIGURE 3 COMPARISON OF THE GROWTH RATES OF MANUFACTURING EMPLOYMENT FOR GROUP II CITIES 47 FIGURE 4 COMPARISON OF THE GROWTH RATES OF MANUFACTURING EMPLOYMENT FOR GROUP III CITIES FIGURE 5 COMPARISON OF THE GROWTH RATES OF MANUFACTURING EMPLOYMENT FOR THE GROUP 17 CITIES 48 growth (12 per cent or less) during the examination period are compared in Figures 6 and 7* respectively. Although a slightly greater uniformity is found among the cities that have had very low population growth than among cities that have had high population growth, such a slight difference in the degree of uniformity does not lead to any valid conclusion. The mean deviation of the rates of growth in the percentage of manufacturing employment for the rapidly growing cities was .136 and for the slowly growing (or declining) cities was .133. Low Percentages during the Earlier Period and the Rates of Growth It is often believed that the cities that had low percentage of manufacturing employment (or other employment) during the early times are bound to have higher rates of growth than others as they and the entire nation grow. This is logically sound because the high mobility in nearly all phases tends to bring about an equalizing effect among the different areas of the nation and the general growth of the total economy offers wider markets. However, the analysis made in this chapter does not support such a belief. Denver and Houston had rather low percentages of manufacturing employment (less than 6 per cent) and Cincinnati and 49 FIGURE 6 COMPARISON OF THE GROWTH RATES OF MANUFACTURING EMPLOYMENT FOR THE CITIES WITH HIGH RATES OF POPULATION GROWTH (80# or more) FIGURE 7 COMPARISON OF THE GROWTH RATES OF MANUFACTURING EMPLOYMENT FOR THE CITIES WITH LOW RATES OF POPULATION GROWTH (12# or less) Cleveland had high percentage (l4.3 per cent and 16.5 per cent, respectively) in 1929. Yet, Denver had the rate of growth as low as .275 and Houston .263 (the lowest among the sixteen cities), whereas Cincinnati (with .456) sind Cleveland (with .752, the highest) had much higher rates of growth. However, if we exclude the prewar statistics, the nation's major old cities have shown a mstrked decline in the rate of msmufacturing employment growth and even in population. Patterns of the Percentage Fluctuations All percentage movements (actual) and the theoretical movement or trend lines (A + bx) showing in the Figures 12-B through 28-B were presented on a single plstne in the Figure 8. The general pattern of the movements of all seventeen curves (sixteen cities and the U.S.) show a marked similarity. If we ignore the slight increase in 1937, a curvilinear function Nc = A + b-^X + bgX^ would Just fit for all curves except that of Seattle. The changes in the direction of the curves (ups and downs) have definitely caused by the depression of the 1930's and the war boom. An interesting thing to note from the Figure 8 is that the major old cities, Cleveland, Detroit, Cincinnati, Baltimore, Chicago, Philadelphia, and New Memphis Atlanta Columbus Seattle Denver Cinci* Minneap Buf f alo Houston Baltimore Cleveland L.A. New York .Detroit ’ Chicago •Phila. U.S 1960 1950 1940 1930 FIGURE 8 PATTERNS OP GROWTH IN MANUFACTURING EMPLOYMENT FOR P THE SIXTBBN CITIES AND THE NATION, 1929-1957 52 York, have a marked trend of decline in the rate of manufacturing growth since World War II, and this trend seems likely to continue in the future at least for quite a while. On the other hand, other cities, though they have shown a slight decline since early or middle of the 1950's, do not give an impression that the trend is of a decline in the near future. Prom the Figure 8, it is clearly observed that the manufacturing employment fluctuates more extensively and is subject to depression and boom to a much greater extent for the cities where manufacturing employment shows higher percentages. Cleveland, Cincinnati, Detroit, and Chicago have over 14 per cent and the mean deviation of estimates ranges between I.58 and 2.2. On the other hand, Houston and Denver have very low average percentages (6.20 and 6.04, respectively) and the mean deviation of estimates is .66 for Houston and .79 for Denver. Other cities lie in between these two groups. Thus, it may generally be concluded that the higher the percentage of manufacturing employment the greater the extent of fluctuations. II. MANUFACTURING EMPLOYMENT AND THE ECONOMIC BASE Many critiques have attacked the assumption of a 53 stable base-service ratio as one of the serious short comings of the economic base theory. When the economy of a community Is undergoing a secular change, It Is more reasonable to suppose that the ratio changes. However, this problem should not be a really serious blow to the theory. Such a shortcoming can be minimized by statistical manipulation. Modification of the Index of Surplus Employment Logically, the method of index of surplus employment as a base-identification technique sounds reasonable for typical large cities or metropolitan areas. Since the assumption of the stable nature of the base-service ratio is erroneous, the trend equation may be substituted to make the ratio rather dynamic. Thus, Sp = nc - Nc, or Sp = (a + bx) - (A + BX) nt should replace S = n. - ( x N,). Nt S = Index of surplus percentage of employment P nc = Trend equation of employment for a community N. = Trend equation of employment for the nation v a = n Intercept for a community A = N intercept for the nation b = Rate of changes for a community 54 B = Rate of changes for the nation X = Independent variable (time) Test of the Index Technique Although the index technique is modified above, the fundamental underlying idea is the same as before, except it attempts to avoid shortcomings that come from a long-run quantitative changes. If we apply this technique to the results obtained from the Section I, manufacturing industry of only four cities, Cincinnati, Cleveland, Detroit, and Chicago, may be identified as involved in the basic activity. Although two-thirds of the cities under examination have the growth rates higher than that of the national average, the average percentage of manu facturing employment is so low that the high rates of growth are unable to bring the Sp to a positive value during the period of the examination. Although the validity of the base-identlfication technique used here is not unquestionable, the results do not seem to be too unreasonable. A large portion of the manufacturing activity is generally located not within the city borders but near the cities and within the metropolitan areas. Since the area delimitation in this study was on the city basis, the manufacturing activity in most of the sixteen cities may not constitute 55 the economic base. Determination of the Size of the Base Once an Industry is Identified as being involved in the basic activity, the portion of the industry that constitutes the economic base must be determined if part of the entire output of that industry is locally consumed. This is a simple task. Since the Sp (surplus of the percentage) is in the form of a percentage, it merely needs to be reduced to the number of persons employed in that industry. For an example, if the Sp (or n. - N_) is 3 for a city with a population of C v 500.000, the number of employees involved in the basic activity would be 15,000, for 500,000 x 3# = 15#000. If the total manufacturing employment in that city is 45.000, the base-service ratio of the manufacturing industry should be 1:2. CHAPTER V ANALYSIS OP RETAIL-TRADE EMPLOYMENT The importance of retail trade as an employment generator is only next to manufacturing industry for the nation and for most cities in the United States. The average percentage of retail employment among population differs from one city to another, but the national average was as high as 6.76 per cent during the period of 1929-57. This figure is higher than the percentage of manufacturing employment for some cities (Denver and Houston). Retail employment together with manufacturing employment account for over half of the urban employment in the United States. In this chapter the patterns of the relationship between retail employment and city size for the sixteen selected cities and the nation were examined. I. SUMMARY AND ANALYSIS OP THE STATISTICAL MEASUREMENTS The statistical measurements of the relationship between retail employment and city size were provided in Appendix B. The results of the statistical measure ments for the sixteen cities and the nation were summarized in Table II. 57 TABLE II SUMMARY OP THE RESUUTS OP THE STATISTICAL ANALYSIS OP RETAIL EMPLOYMENT Rate of Mean of percentage percentage changes City (A) (b) Memphis 6.26 .140 Atlanta 8.77 .334 Columbus 6.90 .185 Seattle 6.80 .118 Denver 6.92 .127 Cincinnati 6.74 .156 Minneapolis 7.47 .225 Buffalo 5.87 .243 Houston 6.17 .085 Baltimore 6.10 .234 Cleveland 6.26 .199 Los Angeles 6.20 New York 4.90 .088 Detroit 5.25 .151 Chicago 5.80 .141 Philadelphia 5.30 .106 United States 6.76 .179 58 National and City Patterns Unlike manufacturing employment, a close uni formity was found in the means of the percentages of retail employment (A) among the sixteen cities and the nation. It seems that this is an inherent nature of retail employment, for retail trade is largely local and depends more closely upon the size of the population. Out of the sixteen cities, only six have enjoyed the growth rate higher than the national growth rate. The rates of growth of retail employment in relation to population for Atlanta, Columbus, Minneapolis, Buffalo, Baltimore, and Cleveland, were .334, .185, .225, .243, and .199, respectively. The difference between the highest and the lowest rates is .298 (Atlanta with .334 and Los Angeles with .036). Although this difference is numerically smaller than that of manufacturing (.480), it is much larger in relative sense. The national mean of the percentage of manufacturing employment was 14.3 and of the retail employment was only 6.76. If the range of the differ ence by .5 for the manufacturing employment would be permissible for the uniformity requirement as we supposed in Chapter IV, the range for retail employment should be within .25. This does by no means imply that the growth rates of retail employment are extensively 59 diversified among the sixteen selected cities. It only means that the uniformity among the major cities of the nation is slightly less pronounced in case of retail employment than manufacturing employment. As in the case of manufacturing employment, the range of differ ence in the growth rates of retail employment found among the sixteen cities might be considered as a small one for most practical purposes. Retail Employment, City Size, and Population Growth If any closer uniformity and similarity in population size are related, they should be observed more markedly within the Group I and Group II cities, for they have more in common in each group. However, the greatest uniformity was found within the Group IV cities. The mean deviation of the rates of growth (the mean of the differences between the rates of growth and the mean of the rates of growth) for the Group IV was found to be .034, whereas the mean deviation for the Group II was .063. For the Group II and Group III cities, the mean deviation was .035 and .058, respectively, and it was .057 for all the sixteen cities. For only the Group II and Group IV cities, the mean deviation was smaller than that of the sixteen cities together. Thus, it seems that a closer uniformity within the two groups of cities was not a necessity but 60 merely accidental. It seems, however, that there is a certain rela tionship between the rates of population growth and the growth In the percentage of retail employment. It was found that the lower the rate of population growth, the greater uniformity In the rate of retail employment growth (b). The slow-growing or matured cities showed .044 of the mean deviation which was below the average (•057), and the fast-growing cities (rather young cities) had the mean deviation of .093 which was above the average and about twice that of the matured cities. This relationship between maturity and uniformity will be observed for other industries in later chapters. Patterns of the Percentage Fluctuations In Figure 9 all percentage movements shown in Appendix B are presented on a single plane to compare the patterns of development. Like the percentage of manufacturing employment (see Figure 8), the patterns of movements in the percentages of retail employment are very alike among the sixteen cities and the nation. All seventeen curves show moderate upward movement during the period of 1929-57. The positive values of b in Table II specify the degree of such upward movements. Unlike manufacturing employment, retail employment Memphis Atlanta Columbus Seattle Denver Cincinnati Minneap Buf f alo Houston 'Baltimore Clev L.A New York Detroit Chicago Phila U.S 1960 1950 1940 1930 FIGURE 9 PATTERNS OP GROWTH IN RETAIL EMPLOYMENT FOR THE SIXTEEN CITIES AND THE NATION, 1929-1957 62 is very stable in relation to population. As observed in Figure 9, the curves are very smooth during the 1927-1957 period except in the year of 1933. Yet the drop in that year was not so severe as manufacturing employment. This proves that retail employment is inherently stable. As seen in Figure 9 (also see Appendix B), the actual figures deviate not very extensively from the trend lines. As in the case of manufacturing employment, in general, the larger the mean of the percentages of retail employment the greater is the extent of fluc tuations around the trend lines. Atlanta and Minneapolis have the mean of percentages of 8.77 and 7.47, respec tively, and the retail employment in these two cities fluctuates more widely than other cities (the extent of fluctuations for Atlanta is of course much larger). On the other hand, Buffalo (with a mean of 4.87), New York (with 4.90), Detroit (with 5*25), Chicago (with 5*80), and Philadelphia (with 5*30) show the least fluctuations around the regression lines. All others line in between in the mean of percentages as well as in the extent of retail employment fluctuations. Thus, from Figure 2 it may be concluded that the major cities in the nation have a close similarity in the pattern of retail employment growth in relation to 63 population. II. BASE-SERVTCE IDENTIFICATION If applied the modified index of surplus labor as a base-service identification technique, retail trade of Atlanta, Columbus, and Denver is easily identified as the base activity, for they have both the mean (A) and the rate of growth (b) higher than the national averages. Seattle and Denver have A higher than that of the national average, but they have smaller b. For Seattle and Denver, retail trade was the basic activity until 20 around 1943-45. On the other hand, Buffalo, Baltimore, and Cleveland have smaller A but larger b than the national averages. Retail trade of these cities therefore is ejected to be the basic activity pi around 1965-70. This prediction is of course based on the assumption that the coefficients A and b would remain stable until that time. This assumption may not be too unrealistic because the predicted year is only one decade ahead. 20The values of 6.8 + .ll8x and 6.92 + .127X will become smaller than the value of 6.76 + .179 (national) between 1/2X and IX. IX = 2 years and 1943 = OX. 21The values of 5.87 + .243X (Buffalo). 6.10 + 234x (Baltimore), and 6.26 + .199X (Cleveland) will become smaller than the value of 6.76 + .179 between 12X and 15X. Thus, if the index of surplus employment is an accurate measuring technique, none of the cities with population of over one million is identified as those whose retail trade is the basic activity. This result, however, does not seem to be too unrealistic because retail trade by nature is local to a large extent. Retail trade may be an important base only for some particular communities where a large number of non residents (relatively to the number of residents) make purchases within those communities. CHAPTER VI ANALYSIS OP WHOLESALE-TRADE EMPLOYMENT Although wholesale trade in general is of much less importance as an employment generating industry than manufacturing industry or retail trade in the United States, the absolute number of persons employed in wholesale trade is quite significant for most major cities in the nation. This chapter studies the rela tionship between wholesale employment and city size for the sixteen selected cities and the nation. I. SUMMARY AND ANALYSIS OP THE STATISTICAL MEASUREMENTS Table III is the summary of the statistical analysis made in Appendix C. National and City Patterns The mean of the percentages of wholesale employment for the nation is 2.3. As seen in Table III, only two cities (Columbus and Detroit) are below the national average. This is in accordance with the fact that wholesale trade is am industry of large cities. In 1958 the total wholesale employment of the sixteen cities accounted for 32 per cent of the wholesale employment of the nation, while the population of the 66 TABLE III SUMMARY OP THE RESULTS OP THE STATISTICAL ANALYSIS OP WHOLESALE EMPLOYMENT Rate of City Mean of percentage (A) percentage changes (*) Memphis 3.6 .050 Atlanta 5.5 .350 Columbus 2.2 .069 Seattle 3.9 .105 Denver 3.7 .121 Cincinnati .095 Minneapolis 4.8 .096 Buffalo 2.5 .118 Houston 3.2 .134 Baltimore 2.4 .077 Cleveland 3.3 .180 Los Angeles 3.1 .066 New York 3.4 .065 Detroit 2.0 .108 Chicago 3.3 .026 Philadelphia 2.7 .102 United States 2.3 .076 67 sixteen cities combined was 21 per cent of the national urban population (i960). As to the rate of growth of wholesale employment in relation to population, five cities, Memphis, Columbus, Los Angeles, New York, and Detroit, are below the national average. Atlanta achieved the highest growth rate with .350 and Detroit the lowest with .026, and the range of difference is .324 which is very significant in relative terms. However, the rest of the cities are not spread uniformly between these two extremes. Most cities do not deviate very much from .100 and thus Atlanta and Detroit seem to be somewhat exceptional. Excluding these two cities, a close uniformity is found as to the growth rate among the major cities in the nation. Wholesale Employment, City Size, and Population Growth A close examination of Table III reveals a closer similarity within the Group III, Group II, and Group IV cities. The mean deviation of the rates of growth (b) was .084 for the Group I, .010 for the Group II, .036 for the Group III, .025 for the Group IV, and .044 for all sixteen cities. Like retail trade, the rates of growth in the percentage of wholesale employment for the Group I cities show the greatest diversity, and the mean deviation is almost twice that of the sixteen 68 cities combined. As to the rate of growth in population and the rate of the percentage growth in wholesale employment, the mean deviation for the four cities (Los Angeles, Atlanta, Memphis, and Houston) which have had population increases by 80 per cent or more is .133* and the mean deviation for the six cities which had very low growth rates in population (Cleveland, Chicago, New York, Buffalo, Detroit, and Philadelphia, all 12 per cent or less) is .041. Thus, there is a wide difference between the fast- and slow-growing cities and the more uniform growth rates are found among the slow-growing cities, Thus it seems that once cities have reached their maturity, they behave in much similar pattern. Patterns of the Percentage Fluctuations Like manufacturing and retail employment, the patterns of the percentage changes for the sixteen cities are very similar. Such patterns were graphically compared in Figure 10. The range of fluctuations in the percentages of wholesale employment is much narrower than manufacturing or retail employment. All cities other than Atlanta show very stable percentages except during the bottom of the depression in the 1930's. This rather smooth movement of the percentages was due to the fact that the war did not inflate wholesale trade. Mmneap. Buffalo Houston Detroit ®altimore Cleveland !*• A* New York Chicago Phiia. FIGURE 10 PATTERNS OF GROWTH IN WHOLESALE EMPLOYMENT FOR THE SIXTEEN CITIES AND THE NATION, 1929-1957 i960 70 The war effect was chiefly found in manufacturing employment. Like manufacturing and retail employment, it was generally observed that the larger the percentages of wholesale employment, the wider the extent of fluc tuations around the trend line. The only exception in Figure 3 was Minneapolis. The average percentage of wholesale employment (a) for Minneapolis is fairly high (highest only next to Atlanta), yet the actual per centages deviate very little from the trend line. The larger the percentage of employment of any industry, the greater the possibility of that industry to become the economic base. Therefore, we may conclude that industries involved in the basic activity are more vulnerable to fluctuations and unstable than those engaged in the service activity. II. BASE-SERVTCE IDENTIFICATION As shown in Table III, only Columbus and Detroit have the average percentage of wholesale employment (A) lower than the national average. As to the rate of growth (b), Memphis, Columbus, Los Angeles, New York, and Detroit are below the national average. According to the modified index-of-surplus labor method, the wholesale trade of Columbus and Detroit is not involved 71 in the basic activity. For other cities that have the value of b lower than the national average, the wholesale trade would remain as involved in the basic activity at least until 1975 to 1980 (if the trend continues until that time), for the slight difference in b cannot bring the nc below Nc until that time. Thus, wholesale trade of all cities except Columbus and Detroit is identified as the basic activity for the time being. This conclusion does not seem to be unrealistic. As mentioned earlier in this chapter, wholesale trade was found to be an industry of large cities. CHAPTER VII ANALYSIS OP SERVICE-TRADE EMPLOYMENT During the early part of the 1929-1957 period, service trade was negligible as an employment-generating industry. If statistics for the years before the examination period were available, the service trade would show a much less importance. As the economy of the nation grew, however, service trade as an employment generator has gained the importance and kept pace with the growth in the national economy. During the 1929-1957 period, fourteen cities out of the sixteen have enjoyed about 200 per cent increase (some much higher) in the percentage of service employ ment. Only Houston and New York have achieved about half of what the fourteen cities have done (100 per cent Increase for New York and a little more than 100 per cent increase for Houston). No other industry has achieved such a remarkable increase during the period 22 examined. Thus the Importance of an examination of such a growing urban industry cannot be ignored. 22 The rates of growth (b) for each industry cannot be directly compared with that of another Industry. The rate of Increase b is determined by the changes in the percentages as well as the magnitudes of per centages. 73 I. SUMMARY AND ANALYSIS OP THE STATISTICAL MEASUREMENTS The statistical analysis of the relationship between service employment and city size was made in Appendix D. Table IV is the summary of the statistical analysis done in Appendix D. National and City Patterns The growth rate in the percentage of service employment for all cities except Houston is higher than the national average. This means that the service trade has been gaining its importance as an employment generator faster for the nation's major cities than for the nation as a whole. However, the importance of the service trade varies considerably among the sixteen cities, and in only five cities (Atlanta, Seattle, Houston, Los Angeles, and New York) the average per centage of service employment is above that of the national average. In 1957 the percentage of service employment for only two cities (Columbus and Philadelphia) was below the national average (see Appendix D). This is an indication that service trade, like wholesale trade, is largely of urban (particularly city) character. The lowest rate of growth (b) is .109 (Houston) 74 TABLE IV SUMMARY OP THE RESUI/TS OP THE STATISTICAL ANALYSIS OP SERVICE EMPLOYMENT City Mean of percentage 00 Rate of percentage changes 00 Memphis 1.55 .147 Atlanta 2.63 .247 Columbus 1.46 .150 Seattle 2.02 .118 Denver 1.78 .154 Cincinnati 1.88 .188 Minneapolis 1.75 .192 Buffalo 1.27 .139 Houston 2.06 .109 Baltimore 1.50 .143 Cleveland 1.73 .182 Los Angeles 2.18 .187 New York 2.19 .164 Detroit 1.55 .166 Chicago 1.87 .196 Philadelphia 1.34 .121 United States 1.97 .116 and the highest is .196 (Chicago) and thus the difference being .087. The extent of this difference is somewhat significant in relative sense, for such a difference in the growth rate in ten years would produce the actual j difference in service employment by about 2,200 (or 1 I j .44 per cent) for cities with 500,000 population. This | figure is about a quarter of the average total service i I employment and it has a relative significance. Thus, the greater diversity in the growth rates is observed in service employment than manufacturing, retail, or wholesale employment. Service Employment, City Size, the Rate of Population Growth As mentioned earlier, the importance of service trade as an employment generator (the size of A) varies among all cities and within each population group and no particular uniformity was found. However, the uniformity in the rate of growth was found within each population group except the Group I. The mean deviation was .033 for the Group I, .014 for the Group II, .026 for the Group III, .020 for the Group IV, and .028 for all sixteen cities. A greater uniformity was found within Group II and Group IV cities. This greater uniformity or diversity seems to be more closely related to the rate of population growth. Among the cities of high rates of population growth (Los Angeles, Houston, Memphis, and Atlanta, with 80 per cent or over), the mean deviation of the rates of growth in the percentage of service employment was .045. This is larger than the mean deviation for all the sixteen cities together (.028). On the other hand, the old and fully-matured cities (Cleveland, Buffalo, New York, Detroit, Chicago, and Philadelphia) with very low rates of population growth had the mean deviation of .013 which is smaller than one-half of the mean deviation of all the sixteen cities and much smaller than one-third of that of the fast-growing cities. Thus, a lesser uniformity is found among the fast- growing cities and this explains why the degree of uniformity is lowest within the Group I cities, for the Group I cities on the whole had high rate of population growth. The relationship between the rate of population growth and the uniformity in the growth performance was observed not only in service employment but all the four employment categories. In all cases, as we have seen in the previous three chapters, the same phenomenon was markedly visible (although with much lesser degree in case of manufacturing employment). 77 Patterns of the Percentage Fluctuations Although In general the growth patterns in the percentages of service enjployment for the sixteen cities I and the nation are very similar, the similarity is | slightly less than those of manufacturing, retail, and i | wholesale employment. In Figure 3 the patterns of the percentages for the sixteen cities and the nation are l graphically compared. The range of fluctuations of the percentages along the trend lines for the service employment is about the same as that of wholesale employment. This may be because the average magnitude of the percentages of service employment is almost as large as that of wholesale employment. For some cities it is even larger than wholesale employment. Like manufacturing, retail, and wholesale employment, it is observed in Figure 11 that the cities of whose percentages of service employment fluctuate more widely from the trend are those cities that have larger magnitudes in the percentages of service employment. This, from the examination of the four industries, it was found that the size of percentages and the range of their fluctuation are closely related. This conclusion is different from the argument that growth and stability are essentially 78 Columbus ‘Seattle 'Denver Cinci. Minneap Buf f alo Houston Balt. New York Detroit Chicago Phila U.S 1930 1940 1950 I960 FIGURE 11 PATTERNS OP GROWTH IN SERVICE EMPLOYMENT POR TUB SIXTEEN CITIES AND THE NATION, 1929-1957 79 23 incompatible. As mentioned earlier in this chapter, service employment achieved the fastest growth in percentage-wise, yet the range of fluctuation in service employment was found very narrow. II. BASE-SERVICE IDENTIFICATION As mentioned already, service trade is a very fast-growing industry although its employment is far below that of manufacturing industry or retail trade. Like wholesale trade, service trade is also of an urban nature. Therefore, it is appropriate here to attempt the base-service identification. The average of the percentage of service employment for Atlanta, Seattle, Houston, Los Angeles, and New York is above that of the nation. Since all cities except Houston have had higher growth rate than the national average, the service trade of these five cities must have been involved in the basic activity. Houston has the size of A higher than the national average but it has lower growth rate (b = .109), than the national average (.116). Therefore, the service 23 Joseph Schumpeter's analysis of capitalism may be expressing this belief most strongly. Capitalism, Socialism, and Democracy (New York: Harper and Brothers Publisher, 1950), 'CiSpEers V-VIII. 80 trade of Houston should theoretically become the service activity, sifter around i960. The actual percentage for Houston in 1957 was higher than that of national average (see Tables LXEX and LXXVII in Appendix D). The service trade of seven more cities should have theoretically been involved in the basic activity before i960. The theoretical date for service trade to become involved in the basic activity for Memphis was 1955; Denver, 1953; Cincinnati, 1949; Minneapolis, 1950; 24 Cleveland, 1955; Detroit, 1959; and Chicago, 1947. Actually, the service trade of Memphis has become involved in the basic activity since 1955 (same as the theoretical data), Denver since 1953 (same as the theoretical date), Cincinnati since 1951* Minneapolis since 1953* Cleveland since 1953* Detroit since 1959, and Chicago since 1951 (for the actual date in Appendix D). The two remaining cities (Columbus and Philadelphia) have rather low average percentages and the growth rates. Yet, their growth rates are greater than the national average and, therefore, the service trade of the two cities is bound to become involved in 24 For computational procedure, see footnote 19, Chapter IV. 81 the basic activity some time, provided that the trend continues. Thus, theoretically, the service trade of Columbus will become Involved In the basic activity after 1963 2 1 1 1 ( 1 Philadelphia after 1975* As seen above, the theoretical date and the actual date to become involved in the basic activity for the service trade for most cities do not deviate much from each other. This Is due to the narrow range of fluctuations in service employment. The fact that the service trade of the fourteen cities out of the sixteen is identified as involving in the basic activity before i960 suggests that service trade is largely of city character. CHAPTER VIII ANALYSIS OP MANUFACTURING, RETAIL, WHOLESALE, AND SERVICE EMPLOYMENT COMBINED The preceding four chapters were concerned with the analysis of the relationship between city size and employment in a single industry. The present chapter is concerned with the over-all relationship between city growth and employment growth (the four categories of employment). This chapter is largely divided into three parts. Prom the beginning, it was assumed or believed that there exists a functional relationship between the growth in employment and population growth. Therefore, in the first part an examination was made to determine the degree of the relationship between the city size and employment of the four industries (that account for well over three-fifths of urban employment in recent years). In the second part, the examination was concerned with the importance of the four industries as the major employment generator in the major cities In the United States. In the last part an examination was made to see whether the four Industries together constitute a 83 part of the economic base In each city. I. RELATIONSHIP BETWEEN EMPLOYMENT GROWTH AND POPULATION GROWTH The degree of the functional relationship between employment growth In the four industries and the popu lation of the sixteen selected cities was examined by means of multiple correlation analysis. Table V is the summary of the correlation analysis made in Appendix 25 E. As seen in Table V, except for Seattle the correlation coefficients for all cities are larger than .9. Although only Seattle in the Group I has a somewhat smaller correlation coefficient, it does not seem that the correlation coefficient and a certain population size are meaningfully related. Furthermore, Table V reveals no specific relationship between the correlation coefficients and the rates of growth in population. Because the comparison of the correlation coefficients for the different population groups and cities with high and low rates in population growth is found to indicate no meaningful relationship, the 2^por the coefficients of the regression functions and a little more detailed statistical measurements, see Appendix E. TABLE V SUMMARY OP THE MULTIPLE CORRELATION ANALYSIS FOR EMPLOYMENT GROWTH AND CITY GROWTH City Coefficient of determination Multiple correlation coefficient Proportion of variance_____ Manu- factur- Whole- ing Retail sale Service Memphis Atlanta Columbus Seattle Denver Cincinnati Minneapolis Buffalo Houston Baltimore Cleveland Los Angeles New York Detroit Chicago Philadelphia .9888 .987? .9764 .6310 .9922 .9676 .9620 .9809 .9903 .8888 .9904 .9622 .8577 .9862 .9545 .9573 .9944 •9939 .9881 .7943 .9961 .9836 .9808 .9904 .9951 .9428 .9952 .9809 .9261 .9931 .9770 .9784 .92098 .91995 .95792 .54172 .92168 .82218 .32006 .47176 .89966 .71365 .35331 .86523 .69553 .64888 .69760 .50508 .00000 .00066 .05469 .08434 .37461 .37553 .03314 .12890 .08435 .01309 .00240 .15889 .04327 .00002 .02651 .02574 .00997 .07621 .01581 .02593 .10424 .11185 .05665 .00121 .11770 .07569 .04621 .04771 .09266 .06699 .00179 .OOO54 .00849 .01238 .00002 .03511 .16309 .02174 .00084 .04502 .43507 .00812 .11359 .13069 .12093 .38518 United States .9624 .9810 .85595 .05578 .03673 .01385 00 4 = - 85 correlation coefficients can reveal nothing further. Thirteen cities out of the sixteen show the coefficients of determination higher than .9 (between .9545 and .9922). This figure is far larger than the results expected from researches on social phenomena in general. Thus, over 90 per cent of the variation in employment can be explained by the variation in population for the thirteen cities. Out of the remaining three cities (Seattle, Baltimore, and New York), Baltimore and New York still show fairly high coefficients of determination (.8888 for Baltimore and .8577 for New York). For these two cities, between 86 per cent and 89 per cent of the variation in employment (in the four industries) is explained by the variation in population. These two cities in fact are very close to the thirteen cities observed above. The coefficient of determination for Seattle is the lowest (.6310), and only two-thirds of the growth in employment is explained by the growth in population. Thus, for thirteen out of sixteen cities under examination and the nation as a whole, over 90 per cent of the growth in employment in the four industries can be explained (or predicted) by the growth in population (or the growth in population by the growth in employment in the four industries). The proportion of variance in Table V indicates the importance of each employment category in explaining the variation in population. For the all sixteen cities and the nation, the variation in manufacturing employment explains 35 per cent to 96 per cent of the variation in population. In general, it was observed that the variation in manufacturing employment in the cities with very high population growth explains the variation in population to a much greater extent. Houston, Los Angeles, Memphis, and Atlanta had popu lation growth of 80 per cent or more, and the proportion of variance of manufacturing employment is .89966, .86523, .92098, and .91995, respectively. On the other hand, Buffalo, Cleveland, Philadelphia, Detroit, Chicago, and New York are the cities that had low rates of population growth (12 per cent or less, and Buffalo's with -7 per cent and Cleveland with -3 per cent), and the proportion of variance of manufacturing employment for these cities is between .35331 and .69553. The less significant relationship of the variation in population by the variation in manufacturing employment for the slow-growing (or declining) cities can easily be explained. The six cities that had very low population growth during the 1929-1957 period underwent population decline during the 1950's. The 87 population decline for the nation's major cities is largely explained by the fact that many manufacturing establishments have moved out of the cities and their employees followed. However, because of rather cheap public transportation facilities, greater use of automobiles, and housing shortages and financial inability to establish new residences in the new indus trial districts, many employees still maintain their residence in the cities and commute to their work 2 6 place. In this situation, the decline in manufac turing employment in those cities must be greater than that of population decline. This fact can positively be supported by statistical information. During the period 1954-58* the decrease in population in Buffalo was by 3.37 per cent, Cleveland by 8.53 per cent, Philadelphia by 1.35 per cent, Detroit by 4.03 per cent, Chicago by .78 per cent, and New York by .56 per cent; whereas the decrease in manufacturing employment during the same period in Buffalo was by 18.18 percent, Cleveland by 14.72 per cent, Philadelphia by 7.34 per cent, Detroit by 31.06 per cent, Chicago by 13*19 per cent, and New York by 5.48 per cent. Thus, in general, 2%his point was also revealed by Vernon's study of New York Metropolitan Region. See Raymond Vernon, Metropolis 1985 (Cambridge: Harvard University Press, T95U7ppTi35^I65 * 88 the greater the discrepancy between the percentage decrease In population and the percentage decrease in manufacturing employment, the smaller is the proportion of variance of manufacturing employment. On the whole, the proportion of variance of retail employment is small. However, for two cities (Minneapolis and Buffalo) it is very significant. The proportion of variance of wholesale and service employment is still smaller in general. For Cleveland and Philadelphia, however, the variance in service employment explains the variance in population to a very significant extent. II. IMPORTANCE OF MANUFACTURING, RETAIL, WHOLESALE, AND SERVICE EMPLOYMENT AS THE EMPLOYMENT GENERATOR An examination of the U.S. Census data revealed that the ratio of urban employment to urban population in the United States since 1930 fluctuated in a very 27 close neighborhood of 2:5* This very stable rela tionship between employment and population was supported 27 The ratio of total employment to all persons residing in the United States (excluding those in the armed services) was also found very stable with 2:5 ratio during the same period. 28 by other empirical study. Although there would be some variation among different cities as to this ratio, the likely deviation is not believed to be very signifi cant because the sixteen selected in this study are the nation's major cities and large cities resemble one another in many respects. The average per cent of population employed in the four industries for the United States was 25.38. This average in fact does not mean much unless the growth rate is taken into account, for the percentage was rising during most of the 1929-1957 period. The average percentages and the growth rates for the sixteen cities and the nation were given in Table VI. This table is the summary of the statistical measurements provided in Appendix F. All the sixteen cities and the nation have positive values for b. This means that the percentage of employment for the four industries has been rising. 28 The study made by Long shows that ratio of labor force to the total population of the United States between 1890 and 1950 was very stable in the neighborhood of 1:2. The discrepancy between Long's figure and the figure in this study is due to the fact that in Long's analysis were the unemployed and those in the armed services included. Moreover, the labor force in his analysis included all in labor market who were ten years of age or over. See Clarence D. Long, The Labor Force Under Changing Income and Employment (Princeton: Princeton university Press, 1958)* P* 24l. 90 TABLE VI SUMMARY OP THE RESULTS OP THE STATISTICAL ANALYSIS OP EMPLOYMENT IN THE POUR INDUSTRIES COMBINED City Mean of percent age (A) Percent age in 1933 Percent age in 1957 Rate of percent age 0h1 f)3 Memphis 18.72 12.30 21.51 .647 Atlanta 26.10 14.55 32.51 1.437 Columbus 20.88 14.08 24.86 .890 Seattle 21.72 12.83 29.36 1.081 Denver 18.44 12.26 21.99 .677 Cincinnati 27.75 20.21 30.83 .895 Minneapolis 23.29 15.70 29.29 1.079 Buffalo 21.84 15.35 26.43 .930 Houston 17.63 11.48 20.29 .591 Baltimore 21.05 15.22 24.87 .727 Cleveland 29.94 20.52 34.83 1.313 Los Angeles 19.47 12.02 25.80 .899 New York 20.08 13.75 24.53 .757 Detroit 23.83 17.57 24.58 .697 Chicago 25.12 16.35 28.89 .958 Philadelphia 22.60 16.82 25.67 .689 United States 25.33 16.91 27.40 .735 Since it was found that the total urban employment maintained about 40 per cent of the urban population (2:5 ratio) and it was fairly stable, the growth in employment in the four industries must be accompanied by decline of employment in other industries. The percentages of the employment in 1933 and 1957 were also given in Table VI. This was to give a more positive impression on the increase of the employment in the four industries, for the rate of growth (b) is more or less abstract and does not impress the magnitude of the growth at the first glance. During the period between 1933 and 1957, the per cent urban population employed in the four industries for the nation as a whole increased by 62 per cent. Three cities achieved over 100 per cent increase— Atlanta (123 per cent), Seattle (129 per cent), and Los Angeles (115 per cent). Only one city had less than 50 per cent increase (Detroit, 40 per cent) and the rest achieved increases ranging between 53 per cent and 87 29 per cent. These remarkable increases during the last quarter of century are very impressive and significant ^Memphis, 75 per cent; Columbus, 77 per cent; Denver, 79 per cent; Cincinnati, 53 per cent, Minneapolis, 87 per cent; Buffalo, 72 per cent; Houston, 77 per cent; Baltimere, 63 per cent; Cleveland, 70 per cent; New York, 78 per cent; Chicago, 77 per cent; and Philadelphia, 53 per cent. 92 in understanding the changing employment characteristics of large cities. Nation al and City Patterns Out of sixteen cities, only three (Atlanta, Cincinnati, and Cleveland) have an average percentage of employment (in the four industries combined) higher than the national average, and five cities (Memphis, Denver, Houston, Detroit, and Philadelphia) have performed poorer than the nation in growth. The difference between the highest (Atlanta)and the lowest (Houston) growth rates is .846. The impact of this difference in the growth rate is somewhat significant. For an example, this growth rate differential would produce a difference of 42,300 in employment between 1943 (the origin) and 1963 for cities with 500,000 population, which is larger than the total manufacturing employment of Memphis or Denver in 1958. Employment and City Size The average size of employment of the four industries shows a slight uniformity within each population group. For the average percentage of employment (A), the mean deviation among the sixteen cities was 2.73. Three population groups have the mean deviation smaller than 2.73— 2.19 for Group I, 2.30 for 93 Group II, and 1.96 for Group IV. The mean deviation for the Group III (4.71) is larger than that for all the sixteen cities together. The large extent of diversity is related to the growth in population. Although the cities within this group have similar population size, cities other than Houston are declining in population. For the rate of growth in the percentage of employment, the mean deviation for all the sixteen cities was .182, and two groups (Group II with .074 and Group IV with .103) have it smaller and two groups (Group I with .25 and Group III with .291) larger than .182. Thus, as far as the rate of growth is concerned, one can hardly claim any correlation between the uni formity and size of population. Fast-Growing and Matured Cities Six cities have achieved a population growth of more than 50 per cent during the examination period— Houston (221 per cent), Los Angeles (100 per cent), Memphis (97 per cent), Atlanta (80 per cent), Columbus (62 per cent), Seattle (52 per cent). Six cities have achieved it by 12 per cent or less— Buffalo (-7 per cent), Cleveland (-3 per cent), Philadelphia (3 per cent), Chicago (5 per cent), Detroit (6 per cent), and New York (12 per cent). As far as the average size of the employment of the four Industries Is concerned, the matured cities show a greater diversity than the fast- growing cities. On the other hand, as was the case for employment in each industry, a greater uniformity in the rate of growth was found among the matured cities. The mean deviation of the rates of growth for the matured cities was .176 and for the fast-growing cities was .223. III. BASE-SERVTCE IDENTIFICATION Since employment in the four industries constitutes the major part of urban employment, an examination of the employment in those industries is important to review the economic base theory. Atlanta, Cincinnati, and Cleveland have both the average percentage of employment (A) and the rate of browth (b) larger than the national averages. There fore, the industries in these three cities may be said to be involved in the basic activity during the entire period of examination and it will continue so in the future (if the trend continues). Memphis, Denver, Houston, Baltimore, Detroit, and Philadelphia have the values of both A and b lower than the national averages. Therefore, the four industries combined in these six cities must be identified as the service activity. Seattle, Minneapolis, Buffalo, and Chicago have A smaller than the national average but they have larger b. Therefore, the four industries combined in these four cities are expected to become involved in the basic activity sometime after 1943 (the origin). Thus, it was calculated that the theoretical date for the four industries combined to become involved in the basic activity for Seattle was 1964; Minneapolis, 1954; Buffalo, 1978; and Chicago, 1946. Columbus, Los Angeles, and New York have rates of growth only slightly larger than the national average. Therefore, the four industries combined cannot constitute a part of the basic activity for these three cities before 1980. CHAPTER IX INCOME AND CITY SIZE Analysis in Chapters IV through VIII was concerned; with the relationship between employment and city size. The analysis has shown the existence of a close func tional relationship between the growth in employment and growth in city population. As mentioned in Chapter I, a close relationship between income (a form of wealth) and population has been recognized explicitly or implicitly from early times. Since the major portion of income today derives from wages and salaries, and since employment is the main source of income, the income and employment of a 30 community must maintain a functional relationship. Thus, if a high correlation is found between employment and population and between income and employment, the natural and logical expectation is that there exists a close functional relationship between the growth in income and population. This functional relationship is the essence of the economic base theory. ^^BortS1 study discloses a high correlation between the growth of per capita income and growth of non-agricultural employment. See "An Approach to Measuring Regional Growth Differentials, Papers of Proceedings of the Regional Science Association, Vol. TV, 195B,i>p. 507^22U 7 ------------------------------ 97 An attempt to project the growth in population through projected income is also a logical development under the 31 assumption or belief of such a functional relationship. Although the high correlation between employment and population growth, already proved logically as well as empirically, leads to a conclusion that income and population are highly correlated, this study requires a direct measurement of such relationship. This chapter therefore is concerned with the statistical analysis of the relationship between income growth and city size. I. PAYROLLS Although most studies measuring the relationship between income and population growth use total income (or per capita Income), the present study used total payrolls of the four industries, which is only a part of total income derived from those industries. As mentioned in Chapter III, the U.S. census publications did not include the total income derived from each industry. Furthermore, there were other reasons for using payrolls rather than income. Since income consists Gerald A. P. Carrothers, "Population Projection by Means of Income Potential Models," Ibid., pp. 121-152. Carrothers set up an income potential model to project population. 98 of payrolls and others, and Income derived from other than employment usually leaks out of the community in which the income-generating industries are located to a great extent, payrolls are believed to represent the more definite source of a community's income. Other sources of income are precarious when the mobility of income receivers is great and reliable source of information is scarce. II. ANALYSIS OP THE STATISTICAL MEASUREMENTS Table VII shows the payroll and population indexes (1935 figures were taken as the base). The first seven cities have not e^qaerienced any decline either in income index or population index, and the next six cities have had a decline either in the payroll index or population index or both. All cities were arranged in the order of the size of population growth. In a country like the United States where the economic growth is considerably large and the living standards rise constantly, the direct measurement of the two indexes would yield a low correlation. There fore, it was computed that the increases in payroll index are on the average so many times the average increases in the population index. Thus, the increase in the payroll index for each period was divided by the TABLE VII PAYROLL AND POPULATION INDEXES, 1935-1958 (1935 = 100) Year 1939 191* 7. 1 * 8 1951* 1958 City Pay. Pop. Pay. Pop. Pay. Pop. Pay. Pop. O ind. ind. k ind. ind. k ind. ind. k ind. ind. k K r r Houston 173 HI ( 6.6) 1 *0 1 160 ( 5.0) 623 216 ( *.5) 776 257 ( *.3) 5 .9 9 .99 Los Angeles 152 108 ( 6.5) 316 135 ( 6.2) 520 158 ( 7.2) 638 173 ( 7.3) 7 .99 .99 Memphis 133 106 ( 5.5) 309 135 ( 6. 0) 1*20 159 ( 5A) 1*57 175 ( 6. 1) 6 .99 .99 Atlanta 151 id* ( 1 2. 8) 315 113 ( 1 6. 5) 1*32 136 ( 9.2) 502 157 ( 7.1) 10 .89 .91* Columbus 13** 102 (17.0) 271 120 ( 8. 6) 431 * 138 ( 8. 8) 1* 68 150 ( 7.6) 9 .97 .98 Seattle 151 101 ( 5 1. 0) 307 121 ( 9.9) 1*35 137 ( 9.1) 570 ll*7 ( 1 0. 0) 10 .99 •99 Denver 1^5 105 ( 9.0) 318 129 ( 7.5) 396 11*7 ( 6. 3) 1*57 157 ( 6. 3) 7 .98 .99 New York 130 103 ( 1 0. 0) 235 108 ( 1 6. 8) 253 109 ( 1 7. 0) 267 108 ( 2 0. 0) 17 .93 .96 Cincinnati 132 101 ( 3 2. 0) 2U 8 108 (18.5) 302 111 ( 1 8. 1 *) 289 110 ( 1 7. 2) 38 .99 .99 Detroit 129 101 (29.0) 253 u p ( 1 3. 0) 281* 111 (16.7) 236 107 (19.5) 17 .8 8 .91* Chicago 136 101 ( 3 6. 0) 280 105 ( 3 6. 0) 315 106 ( 3 6. 0) 308 105 (to.o) 36 •98 •99 Minneapolis 13! * 102 ( 1 7. 0) 260 108 ( 2 0. 0) 330 108 (36.7) 336 103 ( 1 1 2. 0) 35 .23 . 1 * 8 Philadelphia 122 101 ( 2 2. 0) 232 105 ( 2 6. 0) 262 105 ( 3 2. 0) 269 105 ( 1* 2. 0) 30 . 1 * 6 .6 7 NOTE: The value for k was obtained by dividing the increase in the payroll index (over the base) by the increase in population index (over the base). The value for K was obtained by taking the average of k's. The average is not mean. Refer to Chapter III. r 2 is the coefficient of determination, r is the product-moment correlation coefficient. ^ vo 100 corresponding increase in population index and the 32 quotients were averaged to obtain the values of "K" in Table VII. The increases in the modified payroll index (increases in the payroll index divided by "K" value) and the increases in the population were given in Tables CXII through CXXV in Appendix 0. The linear correlation analysis was made for these variables. The table also shows the product-moment correlation coefficient and coefficient of determination between the increases in the payroll index (modified) and the 33 population index. For cities that have enjoyed steady increase in the payroll and population indexes, the lowest correlation 34 coefficient was .94 and mostly .99 or over. For these cities the coefficient of determination is .89 or larger. Thus the variation in the payroll index explains about 32 The average quotient does not mean the mean of the quotients. The average was computed differently from the usual ways. See Chapter III. ^The computational procedure, the regression coefficients, the coefficients of determination, and the graphic comparison of the two variables were given in Appendix G. -’In rounding-off process, the figures in thousandth and thereafter were discarded for the coeffi cients which showed higher than .99* Otherwise, the correlation coefficient, if rounded off, would be equal to 1. 101 90 per cent or more of the variation In the population index and therefore we may conclude that these two maintain a close functional relationship. As seen in earlier chapter, New York, Cincinnati, Detroit, Chicago, Minneapolis, and Philadelphia have had declining populations during the last decade. The correlation coefficient between the increases in the payroll index and the population index for these cities are somewhat lower and more diversified than for those cities that have not had population decline. Among this second group of cities (declining in population) Minneapolis has the poorest correlation coefficient (.48) and Philadelphia also shows a poor correlation (.67). All the rest of the cities in this group have very high correlation coefficients. In all the cities in both groups except Minneapolis and Philadelphia, almost 90 per cent or more of the variation in the payroll index is explained by the variation in the population index. This result therefore supports the basic assumption on which any income potential model is established to project future population growth. III. "K" VALUE AND POPULATION GROWTH As explained earlier, the value for "K" was 102 obtained by averaging the k's for each city. Therefore, the "K" value is the average of the ratios of the payroll indexes to the population indexes. Since employment in the four industries account for the major part of urban employment and the major part of modern income derives from employment in the United States, it would be fair to consider that the "K" measures the relative abundance of income in each city. As seen in Table VII, the matured cities (slow- growing or declining in population) have far larger "K" values than the fast-growing cities. This fact does not conform with what the economic base theory contends. According to the "K" values, the relative size of income does not seem to determine the community's growth. Thus it becomes necessary to turn to other theory to ejqplain the relationship between the community's income and growth. Keynesian System and 1 1 K" Value The Keynesian-type community income model was 35 discussed in Chapter II. The "K" value can be related in some way to the Keynesian system. According to 35 An attempt to set the Keynesian model for regional economics has been made by a few economists. See Pfouts, op. cit., pp. 291-301, 3^1-358. Keynesian economics, income, subject to income multiplier, determines demand and the demand (in con junction with interest rate) in turn determines invest ment, and investment determines the level of employment. The size of the income multiplier depends on the pro pensity to consume. The average propensity to consume is generally higher in a poor community than in a richer community. If a large amount of the rich com munity's income is saved, a large portion of it will seek investment opportunity in other communities where demand is large, for the propensity to consume in the wealthy community is low and therefore demand is insuffi cient to absorb the rich saving. On the other hand, the high propensity to consume in a poorer community offers outside savings the incentive to invest within the poorer community. The inflow of funds will increase employment and income. The initial income thus created multiplies due to the multiplier effect. The exact size of the multiplier will depend upon the community's propensity to spend their income minus the propensity to consume non-local goods sind service. This propensity to consume non-local goods and service depends much upon the ability of the community's service activity in supplying the community's needs. If the community can prevent a large portion of 104 Income from flowing out of its borders by satisfying the community's demand through expanded service activity (not import), then the inflow of fund will increase income further and employment will also increase. Thus, when employment increases population is expected to increase, for employment and population were found to have a close positive functional rela- tionshipi. This series of reasoning within the Keynesian system is in accordance with the "K" values and the rates of population growth. As seen in Table VII, the first seven cities have very high rates of population growth and low values for "K." On the other hand, the matured cities have low rates of population growth (all declining in the 1950's) and very high values for "K."36 Though the population growth cannot be explained by the economic factors alone, it seems that the explanation through consumption function and multiplier analysis is more satisfactory than the base-service method. Such a Keynesian-type explanation is in accord 3<Ve cannot expect a mathematical precision with regard to the relation between "K" values and the rates of population growth. Since no exact mathematical formula was used in computing "K" values, a difference of two or three for the group of fast-growing cities and several for the matured cities has no real signifi cance. with the "K" value analysis. 105 High Level of Income and Decline in Population As shown in Table VII, the high "Km value cites are those that enjoyed a low rate of population growth; all of them have undergone population decline during the 1950»s. In accordance with the "K" value analysis, the most reasonable explanation for such a population decline for a mature city seems to be the high level of income and relationship between the land area and the population of the cities. There is a certain rela tionship between the land area and population size. For pleasant living, certain land area must be secured per person. Thus there is a saturation point for the population growth for the limited area. It Is most natural that people who can afford to do so would seek a better place to live if the per capita land area becomes smaller than the optimum size. Under this situation, the rate of exodus of the people for the wealthy communities should be higher than for the poor communities. CHAPTER X THE ECONOMIC BASE THEORY VS. STATISTICAL APPROACH The validity of the economic base theory can firmly be established only after Its logic has been tested empirically by an appropriate statistical method. The purpose of this chapter is therefore to evaluate the economic base theory and its usefulness in aiding city planning. Additionally, this chapter is concerned with a suggestion as to how the statistical approach can be used better for the same end purpose. I. MAJOR WEAKNESSES OP THE ECONOMIC BASE THEORY The economic base theory thus far developed was described concisely In Chapter II. As mentioned there, the theory is not yet completely out of its infant stage of development and therefore a great deal of criticism is naturally expected. As long as the funda mental concept of the economic base theory Is based on sound logic, it has its future for refinement and further development. Among the numerous criticisms made so far, however, some have touched the core of the economic base theory and given a critical blow to It. 107 In this section only a few major defects of the theory are reviewed to determine its over-all ability to become a guidepost in the city planning process. Instability of the Base-Service Ratio Although some studies conclude that the base- service ratio is fairly stable over a considerable 37 08 period of time, other studies show instability. When a community is undergoing secular change in its economic structure, it is most likely that the base- service ratio also undergoes change. The. proportion of the basic activities is expected to increase with increasing division of labor between communities and decrease with increasing the size of community. Thus, it is proper to treat the base-service ratio as unstable. The instability of the ratio, however, should not be the main weakness of the economic base theory. For, as discussed in Chapter IV, the trend equation can substitute the base-service ratio to avoid the problems arising from the changing ratio. If 37 The Economic Status of the New York Metro politan Region by Dr. York City show the stable base- service ratio. 3®See "The Economic Base Multiplier" by Edgar Z. Palmer and others, University of Nebraska Business Research Bulletin, Nb. 63, 195^7 108 adequate statistical information is available and a proper period is chosen to determine the coefficients of a trend function, the trend equation can safely replace the base-service ratio for long-run analysis. Assumption of Automatic Mechanism As discussed in Chapter II, the economic base theory assumes that service activity will follow auto matically (without deliberate effort on the part of the planning authority) the direction of the quantitative change in the basic activity in due time through economic force, so that the base-service ratio originally computed or assumed is restored. For an example, if the base-service ratio is believed to be 1:2 and an increase of 1,000 workers in the basic activity, an increase of 2,000 workers is expected to follow sooner or later in the service activity and the total increase in employment due to the increase in the basic activity would be 3,000 by maintaining the 1:2 ratio. Logically, this assumption is not unsound, for the increased 1,000 workers in the base must consume goods and services. Since imports are included in the service component, the community must either produce more of goods and service or import them to supply the 1,000 workers. However, if the above example is applied to a particular community where the newly increased employment 109 accounts for the significant portion of the community's total base and the average consumption function of the 1,000 workers differs greatly from that of the original ! residents of that community, the increase in the service activity would not be the same as expected from the base-service ratio. A somewhat complicated situation arises in base- service identification when the major manufacturing firms are located within a community but near its borders and most of their workers maintain residence outside the borders. This kind of situation is not unlikely. If the products of those firms are mostly exported, the question arises as to whether the firms constitute the economic base of that community, or if they do, to what portion of the manufacturing activity should be counted as the basic activity. For, the labor of the non-resident workers clearly is the importation of service to that community and constitutes the service activity. On the other hand, the manu facturing firms pay a considerable amount of taxes to the community with the money earned from beyond the borders of that community. Constituents of the Basic and Service Activities The crude over-all base-service ratio is grossly misleading if the economic and employment structure is 110 complex. For Instance, if 100 laborers in the basic activity and 100 doctors and lawyers whose service is exported are counted as 200 persons in the base, the net result is erroneous because the abilities of the two groups in commanding income from beyond their community borders are greatly different. As we saw the definition of the base-service activities in Chapter II, the service component includes imports. If, for instance, the base-service ratio of a community is 1:2 and the base increased employment by 1,000, no significant increase in the local employment is expected if the community is unable to supply with locally produced goods and service and import them to meet the Increased needs. In this case, the increase in the base does not give practical employment benefit and therefore income to the community. Thus, it is desired to distinguish the constit uents of both the base and service under many different classifications. Particularly, import activity needs to be separated from the main body of service activity. If the base-service ratio can shed practical light in the planning process, the base-service ratio in each sector of the economy should be determined. Otherwise, the changes within the base component without changing the over-all base-service ratio are likely to be ignored Ill and lead to a serious mistake in the planning process. Cost of Field Surveys In the base-service identification in the previous chapters, the index of surplus employment was used. Like the location-quotient method, the index-of- surplus technique is a method of proportional appor tionment. It supposes that the consumption patterns of a community and the nation as a whole are alike. As we know, there are poor as well as rich communities. The former tends to consume more luxuries than the latter. This fact gives quite a different impact to the community’s service activities. Avoiding such shortcomings of the short-cut method of base-service identification means the actual market survey. This is a costly task for any community of a considerable size. In addition, it is not so easy to collect accurate information from the private business sectors due to the unwillingness to expose certain facts on the part of the private business concerns and/or their inability to determine the exact portion of their output that cross the community borders and often the origin of their input. Therefore, the surveyors are compelled to make estimates from the information they could get. Thus the methods in such estimation give positive impact on the results. 112 II. EMPIRICAL EVALUATION OP THE ECONOMIC BASE THEORY In the previous section a few of the major shortcomings of the economic base theory were discussed. Those shortcomings, however, sire not the deadly blow to the economic base theory. They can be minimized by further refinement of the theory. The real deadly blow 39 comes from the empirical studies and tests. In this section the economic base theory is tested in the light of the analysis made in the previous six chapters. Economic Base and City Growth: Employment As the Measure The base-service identification made in Chapters IV through VIII were summarized In Table VIII. Industries in many cities could be Identified as the base sometime in the future as long as the rate of growth (b) was larger than that of the national average. However, It is absurd to suppose that the trend should continue in the remote future. Therefore, the base- service identification was concerned only with the period of examination (1929-1957). Thus B In the table means that the corresponding industry was involved in 39 Pfouts empirically tested the economic base theory and refuted its validity. See Pfouts, o£. cit., pp. 291-304. TABLE VIII BASE-SERVICE IDENTIFICATION FOR THE FOUR INDUSTRIES DURING THE EXAMINATION PERIOD City Population growth per cent) I n d u s t r y Manufacturing detail Wholesale Service Combined Houston 221 S S B B S Los Angeles 100 S S B B S Memphis 97 S S B B S Atlanta 80 B B S S B Columbus 62 B B S S S Seattle 52 S S B B S Denver 37 S S B B S Baltimore 17 S S B S S New York 12 S S B B S Cincinnati 11 B S B B B Detroit 6 B S S B S Chicago 5 B S B B B Minneapolis 4 S B B B B Philadelphia 3 S S B S S Cleveland -3 B S B B B Buffalo -7 B S B S S NOTE: B means the industry is involved in the basic activity and S means the industry is identified as the service activity. 113 114 the basic activity during the entire period of the examination or it became the base during the period. The same holds true for S. ! As observed in Table VTII, the combination of the four industries of Atlanta, Cincinnati, Chicago, Minneapolis, and Cleveland was identified as involving i in the basic activity. This is very unsatisfactory results as far as the economic base theory is concerned. According to that theory, the base and the population growth of Atlanta alone could be explained, for Atlanta had a very high population growth. Cincinnati and Chicago belong to the group of low population growth. The worst thing is that the population growth of Cleveland was negative, yet the four industries combined of that city are identified as the base. Thus, from the empirical test made in this study is compelled to conclude that there is no functional relationship between the economic base of a community and its population growth. Economic Base and City Growth; Payrolls As the Measure An analysis of the relationship between income (payrolls) and city size was made in Chapter IX. The nature or meaning of the "K" value was discussed there. Using the "X" value the base-service identification will be made here. Table IX gives the population growth for the seven cities that had high growth rate and six cities that had low growth rate and the national average and the "K" value for each city and the nation. If the "K" value is larger than the national average, the four industries combined are identified as the base. As shown in the table, only Houston has the "K" value below the national average. Houston had the highest rate of growth in population (221 per cent) among all the cities examined in this study, yet the four industries combined of Houston must be identified as the service activity. Appraisal of the Base-Service Concept Neither the analysis of the relationship between employment and city size nor the relationship between income and city size thus far made in this study support the fundamental concept of the economic base theory. The shortcomings of the theory discussed in the previous section can be minimized and the measuring technique as well as base-service classification method can be improved if the fundamental concept of the theory is sound. However, if the theory is found to render no valid practical service in the city planning process, any refinement or improvement on the minor parts of the theory is futile. The valid practical service can only be measured through empirical studies. Not only the 116 TABLE IX BASE-SERVICE IDENTIFICATION BY USING PAYROLLS OF THE FOUR INDUSTRIES AS THE UNIT OF MEASURE City Population growth (per cent) "K" value Base or £ Houston 221 5 S Los Angeles 100 7 B Memphis 97 6 B Atlanta 80 10 B Columbus 62 9 B Seattle 52 10 B Denver 37 7 B New York 12 17 B Cincinnati 11 18 B Detroit 6 17 B Chicago 5 36 B Minneapolis 4 35 B Philadelphia 3 30 B United States 40 6 NOTE: B means the four Industries combined of the cities involved in the basic activity and S means they are identified as the service activity. empirical test made in this study but also a number of such studies reject the practical use of the theory for urban economic analysis and there is a growing sign that the planning authorities abandon the base-service technique in their planning process. III. PURE STATISTICAL APPROACH The base-service analysis is expected to contribute to planning transportation and communication facilities, housing and zoning regulations, peak-load parking requirements, land usage, and community money flows. For planning these, an understanding of the community's economic characteristics, the patterns of changes, and the projection of population and employment is required. We have reviewed the major shortcomings of the economic base theory and evaluated it, and concluded that the theory failed to render valid practical service which it intended to. Even if the theory could be improved and proved to render the desired service, it would be a costly task to compile all the needed 40 The base-service technique was rejected in the Portland1s Economic Projects, a recent major urban economic base study, prepared by the City Planning Commission, Portland, Oregon, December, 1957. information to which the theory could be applied. If an alternative method that costs less and renders the desired service, the planning authorities should use it by all means. The proposed method in this study is the pure statistical approach. Elements in the Pure Statistical Approach The elements in the statistical approach proposed in this study concerned with correlation and regression analysis. Correlation analysis. It was useful to examine the functional relationship between employment growth and city growth. The existence of a close functional relationship between them enables us to estimate one from the other. The multiple correlation analysis was also helpful in determining the employment category whose variation that explains more closely the variation in population, or vice versa. In a certain way, Income and population are 41 functionally related. The functional relationship between income and population of course cannot be used for any purpose In the same way as the functional ^See the way "K" value was determined and the correlation analysis between payroll and population Indexes was made In Chapter IX and Appendix 0. 119 , relationship between employment and population, for the high correlation between Income and population was found ! only through a statistical manipulation. However, a logical projection model can be established by taking account of the "K" value. ! Determination of trend. The most important element in the statistical approach for urban economics is the determination of the trend in the relationship between growth and employment and growth in population. In the determination of such a trend, an important thing the planning authority should consider is the selection of the period for examination. The statistically estimated trend depends not only upon the compiled factual information but also upon the perod chosen for the examination. For instance, the rate of growth of the percentage of employment among population (b) for the four industries in all the sixteen cities during the period of 1929-1957 was positive (see Chapters IV through VIII). However, when the period was chosen between 1890 and 1958 for manufacturing industry (statistics available only for manufacturing employment for the years before 1929)> the growth rate (b) for New York, Philadelphia, Houston, Cincinnati, and 120 42 Minneapolis was found to be negative. As the period of examination, the period that includes 1930's and 1940's is about the worst, for the low employment figures during the depression and the ultra-high figures during the war give nothing but a high positive growth rate. The worst period was chosen in this study because of the scarcity of census information. However, any period is satisfactory as far as the comparison among the cities is concerned. Because of the importance in the selection of the period for examination, planning authority should be extremely careful and use good sense of judgment. In addition, it is the duty of the local authority to compile the factual information regarding its own com munity with regularity and small intervals between censuses. If statistics can be compiled every other year or every three years, for instance, the planning authority has a greater chance to select proper period of examination. Also important thing in trend analysis is the selection of a proper trend equation. In this study the The value of b was -.088 for New York, -.184 for Philadelphia, -.073 for Houston, -.11 for Cincinnati, and -.01 for Minneapolis, during the period between 1890 and 1958. 121 linear equation was used, for there was no particular reason to believe that other functions can determine the trend better. Once the selection of the period for the deter mination of the trend is believed to be satisfactory, the linear function will give the best result for the long-run purpose. Population Projection In any economic planning, the importance of population projection is utmost. Economic factors alone cannot explain the population growth, but many factors together attribute to it. Fortunately, the pattern of the population growth is not subject to violent changes. It changes rather slowly during a fairly long period of time. In modern societies, failure in business (depression) and unemployment do not give direct impact on the growth in population during any considerable period of time. Since the population census is taken every ten years, the likely error in the estimate of population between the censuses cannot be large. Furthermore, the modern population projection technique has been so improved that an estimate of over a decade may still be a fairly close approximation. 122 Employment Distribution As the examination between the growth In popu lation and the growth In employment In Chapter VIII revealed, a very close functional relationship exists between them. Therefore, unless there occur violent changes (social, economic, physiological, or legal), It would be safe to assume that about 40 per cent of the population Is gainfully employed. Then, the next task for the planning authorities is to estimate the employ ment distribution. Change in technology, taste, and income affects the pattern of employment distribution. However, the change in the pattern of employment is rather of long- run character, and therefore a fairly close estimate can be made. In Chapters IV through VIII, the trend of the percentage of employment in each of the four industries nnd the four industries combined was statisti cally estimated. By understanding the share of the employment and the trend among the four industries that account for 65 per cent to 70 per cent of urban employ ment, transportation and communication facilities, housing and zoning regulations, road, streets, and parking requirements, water and power requirements, effective land uses, and many others can effectively be planned. 123 ! If a community desires to attract more manufac turing establishments, a number of means may be taken. It does not matter and there Is no need to know what portion of the output of the attracted establishments are exported, that is, no need to determine the base- service ratio. As long as the new establishments can increase the community's employment, they will attract income into the community. The increase in income will not necessarily accelerate population growth as evidenced by the analysis made in Chapter IX. If that community also desires higher propensity to consume local goods, the planning authority can again take a number of measures. Urban Land Use Planning Through a careful analysis of the trend and other causal factors, population and employment projections can now be made fairly accurately. Once the magnitude of future growth in population and employment in different categories Is determined, the planning authority can make an estimate of land area which will be required to meet the growth. The additional land area needed by a certain future date for residential and industrial uses can be estimated by studying the trend of changing tastes, 124 technological development, and governmental regula- 43 tions. The planning authority can influence much on the selection of specific land area for specific uses. ^The study of Los Angeles County during the latter part of the 1930's shows that the number of persons accommodated on each acre was 24.6 (excluding farm homes). Master Ply of Land Use; County of Los Angeles. The Planning CommTssion, County of Los Angeles, 1941. p. 27. In the New York Metropolitan Region, it was estimated that more than an acre of land is used for every ten manufacturing workers (in the new plants). See Vernon, og. cit., p. 117. CHAPTER XI SUMMARY AND CONCLUSIONS Since Chapters IV through IX were conclusions of the statistical analyses-made Appendixes, this final chapter is largely the summary of the conclusions. I. SUMMARY Percentage of Employment, Its Growth Rate, and City Size On the whole, no correlation was found between the magnitude of the percentage of employment (whether 44 single or the four industries combined) among popu lation and the city size. As to the rate of growth, the same conclusions holds true. Thus the division of the sixteen cities into four population groups was meaningless. Rate of Population Growth and Rate of Growth in the Percentage of Employment The analysis has shown that a close uniformity in the rate of growth of the percentage of employment The slight similarity in the average percentages of employment in the four industries combined was found within the Groups I, II, and IV (See Chapter VIII). However, the degree of the uniformity is so slight that it virtually has no meaning. 126 I existed among the matured (slow-growing or declining) cities. On the other hand, a great diversity In the rate of growth was found among the fast-growing cities. Size of the Percentage and Employment Fluctuations j The analysis revealed that the larger the per centage of employment (whether single or the four Induatrles combined) the greater was the extent of employment fluctuation. Therefore, If employment stability is an Important objective of the economic policy, it is desired to have a greater diversity in the distribution of employment. Since it was found that the total employment maintained about 40 per cent of the population and this proportion has been very stable, a greater spread of the employment among different activities means the low percentage per activity and therefore less vulnerable to fluctuations. Employment Growth and Population Growth It wasfbund that there was a very high correlation between employment growth and population growth. All the cities examined except Seattle showed the coefficients of correlation higher than .9. For Seattle, about two-thirds of the variation in the employment of the four industries combined could be explained by the variation in population (r = .63 and r = *79)* Thus, for the most cities under examination, j employment growth and population growth maintained a close functional relationship. j i Income Growth and City Growth Though the analysis of the relationship between ' the growth in income and the growth in population has shown a very high correlation, it is erroneous to conclude that a high level of income is attributable to the high rate of population growth. The high corre lation was partly due to the fact that the payroll index was divided by the "K" value before the corre lation analysis was made. Employment Distribution The four industries combined accounted for about 65 per cent to 70 per cent of the city employment during the 1950's. The importance of these four industries as the major employment generator has been growing during the period under examination. The pattern of the distribution of employment among these four industries shows that manufacturing employment is far the largest percentage of the total, and next is retail employment. Although the percentage of service employment for some cities during the 1950's was larger than that of wholesale employment, it remained below I 128 I I wholesale employment during the greater part of the 1929-58 period. ! As far as the growing pattern Is concerned, the ; service employment has demonstrated the most promising j future. The future of manufacturing employment will i be dependent much upon the tempo of automation In the major sectors In the economy. It Is believed that retail and wholesale employment will grow rather In close pace I I with the growth In population, although the percentages j j of these two employment categories have grown moderately ) i during the period under examination. II. CONCLUSION The economic base theory is closely tied with the concept of growth. This should not lead to any confusion that growth per se is to be optimized. This study has been concerned with whether a functional 1 relationship may safely be postulated between growth in one sector of the economy and in its total magnitude 1 in terms of particular variables, i.e., population, employment, and income. On the other hand, the prime objective of the city planning should rest on making the city a better place to live, to work, and recreate. Growth and these objectives are not necessarily achieved simultaneously. Growth beyond the optimum point makes the place unpleas suit to live and Inconvenient to work. Some Investigators have concerned themselves with this question which is a nebulous one scarcely susceptible 45 to any precise handling quantitatively. This is the reason that there are many optima, many of which we are 46 unprepared to assign economic values. Whatever the objective of the planning of a community may be, a good understanding of the major industries of the community is the important factor. A good understanding of the major industries means the understanding of the pattern of change in each industry as well as in the total magnitude. The economic base theory was intended to help understanding relationship ^Though the optimum size of a city depends on a general viewpoint from which criteria of good, better, and best can be derived, and the concept is largely con ceptual, yet it must certainly exist somewhere, depending upon the values the people unconsciously assign. See Otis Dudley Duncan, Optimum Size of Cities," Reader in Urban Sociology, edited by Paul K. Hatt and Albert J. Reiss, Jr. (Slencoe, Illinois: The Free Press, 1951), pp. 632-645. ^Florence assigned four main economic tests to determine the optimum size of cities: (l) efficiency in increasing current production, (2) efficiency in pattern of income, (3) efficiency in increasing future income, and (4) efficiency in offering a variety of Jobs and services. See P. Sargant Florence, "Economic Efficiency in the Metropolis," The Metropolis in Modern Life, edited by Robert Moore Fisher (New York: Doubleday and Company, Inc., 1955), PP* 85-121. among the major sectors of the economy as time series data permit and the effects of the changes In them. Yet, the analysis made In this study has shown that the economic base theory failed to render the service Intended. On the other hand, the empirically derived approach In this study Is believed to serve the desired purpose. It was proposed because economic base theory failed to achieve Its objective. Further more, the statistical approach will render the more effective service for the purpose. Less costs are involved in the actual market surveys and it avoids the vulnerability which is inevitable in base-service classification and identification. As was found, employment in manufacturing indus try, retail, wholesale, and service trades combined accounted for the fair greater part of the total employ ment in most large cities. Understanding of the growth pattern of the four industries combined gives the first approximation of the changing pattern of the economic structure of a community. Once these over-all characteristics are found, the share of each industry and its changing pattern should be determined. If the public authority compiles a census of the economic activities of its community with regularity and 131 frequency, the statistical analysis of a proper period will enable the determination of the growth pattern of the over-all economy and of each of the major sectors within it. Once the dynamic characteristics of the over-all economy and each of the major sectors within it are determined, the planning authority can set up specific objectives in the planning process and take proper measures accordingly. As mentioned in Chapter I, the statistical analysis in this study made use of the U.S. Census data exclusively. Because of the comparatively few observa tions in the available data and frequent changes in the definition of the employment category, the analysis of the trend in employment growth may deviate considerably from the actual growth. These limitations notwithstand ing, the analysis is believed to render useful results as far as the comparison among the different cities are concerned. The prime objective and service of this study lay in the empirical testing of economic base theory and, second, in suggesting an alternative technique for the urban economic analysis. BIBLIOGRAPHY 133 BIBLIOGRAPHY A. BOOKS Abercrombie, Patrick. Town and Country Planning. New York: Oxford University 'Press, 1944. Bassett, Edward M. The Master Plan. New York: Russel Sage Foundation,“T53HI Bennett, Carl A., and Norman L. Franklin. Statistical Analysis in Chemistry and the Chemical industry, New York: JohrTWllVy and Sons,~Tnc. T954. ------ Bettman, Alfred, and others. City and Regional Planning Pagers. Cambridge: Harvard University Press, 194fc>. Croxton, Frederick E., and Dudley J. Cowden. Applied General Statistics. New York: Prentice-Hali, Inc., T 555~ . ---------------- Davies, George R., and Walter F. Crowder. Methods of Statistical Analysis. New York: John Wiley andHSons. The:-; 1933.— — Dixon, Wilfred J., and Frank J. Massey, Jr. Introduction to Statistical Analysis. New York: McGraw-Hill Book eo.TTnc.7 195i: Fi3her, R. A. Statistical Methods for Research Workers. New York: Hafnur Publishing Co., 1954. Fisher, Robert M. (ed.). The Metropolis in Modem Life. New York: Doubleday and Co., Inc., 1955• Glikson, Arthur. Regional Planning and Development. New York: McGraw-mi Boole Co"., Tnc.,' 19517---- Hatt, Paul K., and Albert J. Reiss, Jr. (eds.). Reader in Urban Sociology. Glencoe, Illinois: The Free Press, T55T7-------- Hiberseimer, Ludwig. The New Regional Patterns. Chicago: P. Theobold, 1949. Hubbard, Theodor K., and Henry V. Hubbard. Our Cities Today and Tomorrow. Cambridge: Harvard University Press, 1923^ 134 Kumow, Ernest, and others. Statistics for Business Decision. Homewood, Illinois: Richard D. Irwin, Inc., 1959. ; Mills, Frederick C. Statistical Methods. New York: Henry Holt and Co., 1930. Monroe, Arthur E. (ed.). Early Economic Thought. Cambridge: Harvard University Press, T55IT i | Mumford, Lewis. The Culture of Cities. New York: ; Harcourt, Brace and Co., T938. I i Pfouts, Ralph W. (ed.). The Techniques of Urban Economic i Analysis. New Jersey: Chandler-Davis Publishing do., | i960. Ratcliff, Richard U. Urban Land Economics. New York: McGraw Hill Book Co., YncTTlVW' Raymond, Vernon. Metropolis 1985. Cambridge, Mass.: Harvard University Press, 1900. Smith, James, and Acheson J. Duncan. Elementary Statistics and Applications. New York: McGraw-Hill Book Co. , i m --------- Walker, Helen M., and Joseph Lev. Statistical Inference. New York: Henry Holt and Co., 1953. Weimer, Arthur, and Homer Hoyt. Principles of Real Estate. New York: The Ronald Press Co.,"T939• B. PUBLICATIONS OF THE GOVERNMENT United States Bureau of the Census. Eleventh Census of the United States: 1890. Population, Pts. 1 and 2. Washington: Government Printing Office, 1895. . Twelfth Census of the United States: 1900. Population, Vols. Iand II. Washington: Government Printing Office, 1902. ______. Thirteenth Census of the United States: 1910. Population, Vols. Il and~TlI. Washington: Grovemment Printing office, 1913. 135 United States Bureau of the Census. Thirteenth Census of the United States: 1910* Manufacturers. Vol. IX. Washington: Government Printing office, 1912. . Fourteenth Census of the United States: 1920. Topula'tTonT Vols .~T,~ II .^TTEl."n^sHTngt'dn x ~ Govemment Printing Office, 1922. _______. Fifteenth Census of the United States: 1929. Population, Vol. Ill, Pts. 1 and 2. Washington: Government Printing Office, 1932. _______. Fifteenth Census of the United States: 1929. Distribution, Vol. Ii Retail Distribution, Pts. 1, 2, and 3. Washington: Government Printing Office, 1933. _______. Fifteenth Census of the United States: 1929. distribution, Vol.II; Wholesale Distribution. Washington: Government Printing Office, 1933. . Manufactures: 1929. Vol. Ill, Reports by States. Washington: Government Printing Office, 1933• . Census of Business: 1935. Vol. I, Retail Trade. Washington: Government Printing Office, 1937. . Census of Business: 1935. Vol. II, Wholesale Distribution. Washington: Government Printing Office, T937I--------- Census of Business: 1935. Vol. Ill, Service Establishments• Washington: Government Printing Office , “ 1937. Sixteenth Census of the United States: 1939. Census of Business. VoTT 1, RetafT~Trade~Pt. 1 and ~ 3 T . Washington: Government Printing Office, 1943. Sixteenth Census of the United States: 1939. Cehsus of business. VoTT If. Wholesale Trade. Washington: Government Printing Office, 1943. Sixteenth Census of the United States: 1939. of Business. VoT7 III. Service Establishments. Washington: Government Printing Office, 1942. . Census of Business: 1948. Vol. I. Retail Trade, Pts. 1 and 2. Washington: Government Printing Office, 1951. 136 United States Bureau of the Census, Census of Business: 1948. vol. II. Retail Trade, PtiTT"aria~2“------- Washington: Government Printing Office, 1952, . Census of Business; 1948. Vol. III. Retail Trade: Area Statistics. Washington: Government Print Tng’ TJffTceT ----- . Census of Business: 1948. Vol. IV. Wholesale Trade. Washington: Government Printing Office, 1952. . Census of Business: 1948. Vol. V. Wholesale Trade: Area Statistics. Washington: Government PHnElng^fice, Igl. . Census of Business: 19^8. Vol. VI. Service Trade: General-Statistics. Washington: Government "Printing Office,' "1955.--- Census of Business: 1948. Vol. VII. Service Trade: Area Statistics. Washington: Government Print ing Office, 1952. Census of Manufactures: 1947. Vol. I. General Summary! Washington: Government Printing Office, 1950. . Census of Manufactures: 1947. Vol. III. Statistics by~~gtates. Washington: Government Print- ing Office,1950. Census of Business: 1954. Vol. I. Retail Trade: Summary Statistics. Washington: Government PrinTingUffice, ' i ' 9 ' 5 ' 7 .--- Census of Business: 1954. Vol. II. Retail Trade :~"Area Statistics. Washington: Government Printing-Office, 195b. Census of Business: 1954. Vol. III. Wholesale Trade: Summary Statistics. Washington: Government "Printing Office,T957.--- Census of Business: 1954. Vol. IV. Wholesale Trade: Area Statistics. Washington: Government Printing Office, 195&. Census of Business: 1954. Vol. V. Selected Services: Summary Statistics; Washington: Government Printing Office, 1957. 137 United States Bureau of the Census. Census of Business: 1954. Vol. VI. Selected Services: Area iStat1sties. Washington: Government Printing Office, 195b. . Census of Manufactures: 1954. Vol. I. Summary ‘ Statistics. Washington: Government Printing Office. 1957:----- . Census of Manufactures: 1954. Vol. II. Area Statistics. Washington: Government Printing Office. T957I----- . Census of Business: 1958. Vol. I. Retail Trade: ~ ~5ummary Statistics. Washington: Government Printing Office, 19bl. . Census of Business: 1958. Vol. II. Retail Trade: Area Statistics. Washington: Government TrErtingnSTf 1 ce",“T98I. " Census of Business: 1958. Vol. III. Wholesale Trade: Summary Statistics. Washington: Government Printing <2>Ffice,HT95T.--- . Census of Business: 1958. Vol. IV. Wholesale Trade: AreaStatistics. Washington: Government Printing Office, l9bl. Census of Business: 1958. Vol. V. Selected Services: Summary 'Statistics. Washington: Government Printing Office, 1061. Census of Business: 1958. Vol. VI. Selected Services: Area Statistics. Washington: Government' Printing Office, 19bl. . Census of Manufactures: 1958. Vol. I. Summary Statistics. Washington: Government Printing Office. T96T.----- . Census of Manufactures: 1958. Vol. III. Area Statistics. Washington: Government Printing Office, jg s r .----- . Abstract of the Eleventh Census: 1890. Washington: Government Printing Office. Abstract of the Census of the Manufactures: I9I4. Washington: Govemment~Printing Office,' T917. United States Bureau of the Census. Abstract of the Census of Manufactures: 1919. Washington:HTovemment Printing Office, 1923. . Statistical Abstract Supplement: 1890. Washington: Government Printing Office. _______ • Statistical Abstract of the United States: 1932j 1942, and 1961. Washington: Government Printing Office. . Biennial Census of Manufactures: 1923 (1926), — 1955 mST}, i9#iri93tfL ), 1931 (1933), 1933 (19365, 1935 (1938}, 1937 (1939;• Washington: Government Printing Office. C. PERIODICALS Andrews, Richard B. "Mechanics of the Urban Economic Base: A Classification of Base Types," Land Economics XXIX (November, 1953), 343-50. -------------- . "Mechanics of the Urban Economic Base: Historical Development of the Base Concept," Land Economics, XXIX (May, 1953), 161-67. . "Mechanics of the Urban Economic Base: Special Problems of Base Identification," Land Economics, XXX (August, 1954), 260-69. "Mechanics of the Urban Economic Base: The Concept of Base Ratios," Land Economics, XXXI (February, 1955), 47-53. "Mechanics of the Urban Economic Base: The Problem of Base Area Delimitation," Land Economics, XXX (November, 1954), 309-19. . "Mechanics of the Urban Economic Base: The Problems of Identification," Land Economics, XXX (February, 1954), 52-60. Bluemraenfeld, Hans. "The Economic Base of the Metropolis Journal of the American Institute of Planners, XXI (November, 1955), 114-32. 139 Bort, George H. "An Approach to Measuring Regional Growth Differentials," Regional Science Association Papers and Proceedings, IV, 1950. 207-20. Carrothers, Gerald A, "Population Projection by Means of Income Potential Models," Regional Science Association Papers and Proceedings, IV, 1950, 121-52. Greenhut, Melvin L. "Comments on Economic Base Theory," Land Economics, XXXV (February, 1959), 71-75. Hildebrand, George H., and Arthur Mace, Jr. "The Employ ment Multiplier in an Expanding Industrial Market: Los Angeles County, 1940-47,” Review of Economics and Statistics, XXXII (August, 195^7, 541^49” Hotelling, Harold. "New Light on the Correlation Coefficient and Its Transforms," Journal of the Royal Statistical Societies, Series B. XV, No. 2, 1553. Hoyt, Homer. "Homer Hoyt on the Economic Base," Land Economics, XXX (May, 1954), 182-86. ---- Levein, Charles L. "An Appropriate Unit for Measuring the Urban Economic Base," Land Economics, XXX (November, 1954), 360-71. Morrissett, Irving. "The Economic Structure of American Cities," Regional Science Association Papers and Proceeding's, IV. 1954. -'«qi=5g:------------------ North, Douglas C. "Location Theory and Regional Growth," Journal of Political Economy, LXIII (June, 1955), 243-50. Palmer, Edgar Z., and others. "The Economic Base Multiplier," University of Nebraska Business Research Bulletin, No. 637~l958. Pfouts, R. W. "An Empirical Testing of the Economic Base Theory," Journal of the American Institute of Plan ners, xxiii (May,"T957), 64-69. _______, and Erie Curtis, "Limitations of the Economic Ease Analysis," Social Forces, XXXVI (1958), 303-10. Tiebout, Charles M. "Exports and Regional Economic Growth," Journal of Political Economy, LXIV (April, 1956), ie&m:-------------------- APPENDIXES APPENDIXES All basic information and statistical measurements necessary for this study were included in Appendixes. If; one approves of the methodologies described in Chapter III, he would come to about the same conclusions as those of mine sifter an examination of the seven appendixes. Thus the backbone of this study consisted of information and statistical analyses provided in Appendixes A through 0. Therefore, it is necessary to make an explanation on each appendix. Appendixes A through D provide statistical information stnd measurements for population, manu- facturing employment, retail employment, wholesale employment, and service employment. The basic statis tical raw materials in Tables X-A through XXVT-A in Appendix A and in the second columns of Tables XXVII through LXXVII in Appendixes B, C, and D were all information obtainable from the U.S. census publications for the necessary statistical analysis. Prom these basic sources of information, population and employment figures in Tables X-B through XXVT-B in Appendix A and in the third columns of Tables XXVII through LXXVII in • 142 Appendixes B, C, and D were computed under the 2 assumption made in Chapter III. The last columns In Tables X-B through XXVT-B, Tables XXVII through LXXVII In Appendixes A, B, C, and D show the percentages of employment in each category among population. In computing the percentages of employment for the United States (see Table XXVT-A in Appendix A), urban I population rather than the total population was used to i exclude rural population, for employment in the four industries (particularly manufacturing) is more or less of urban character. The percentages of employment were graphically presented in Figures 12-B through 28-B in Appendix A and Figures 24 through 79 in Appendixes B, C, and D. The dots represent the percentages and the line in each figure was drawn according to the least-squares fitting techniques. Each trend line was accompanied by a corresponding trend function (linear) with coefficients of the function computed. In view of the fact that manufacturing industry All figures computed from the original informa tion were rounded off to some extent but it should not affect the results of any meaningful extent. p 1929 statistics for service employment for cities were not available. The figures for 1929 and 1931 in Appendix D are estimates (see Chapter III). is most important in providing employment opportunity, Figures 12-A through 28-A were prepared in Appendix A to enable a quick impression on the movements of the | | manufacturing employment and population for each city and the nation. In those Figures the logarithmic scale was ; used for Y axis in order to be able to manage within a limited space and also for a better visual aid. Tables LXXVIII through XCIV in Appendix E are the results of the multiple correlation and regression 3 analysis for employment in the four industries and the city size. In Tables XCV through CXI in Appendix F, the percentages of employment of the four industries were added. These combined percentages were graphically presented in Figures 80 through 96. In each Figure, the trend line with the coefficients of the regression function were given. In Tables CXII through CXXV the increases in the 4 payroll and population indexes were given. Also were the coefficients of determination and the product-moment %ie BIMD No. 06 of the University of California, Los Angeles, was used for the multiple correlation and regression analysis. 4 / The payroll index here is the modified one (see Chapter III). The modified payroll index was computed from Table VII in Chapter IX. 144 correlation coefficients included in those Tables. The increases in the payroll and the population indexes were graphically illustrated in order to show the movements of the two variables. APPENDIX A MANUFACTURING EMPLOYMENT AND CITY SIZE TABLE X-A MEMPHIS, TBNNs POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ. 1920 162,351 1929 15,921 1930 253,143 1935 14,668 1937 16,741 1939 13,921 1940 292,942 1947 34,107 1950 396,000 1954 40,053 1958 39,098 1960 497,524 ■p c 0 ) & T3 O fl-H C t f Pu ^ e f l < D O •H bO t a 3^ pu-p o o Pl. (0 «H 3 C c d s Pop, Manuf. N L 1930 1940 1950 1960 FIGURE 12-A MEMPHIS, TENN: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) % o f pop 147 TABLE X-B MEMPHIS: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. employ. Employ. % of pop. 1929 244,000 15,920 6.5 1931 256,900 15,500 6.0 1933 264,500 15,080 5.7 1935 272,300 14,670 5.4 1937 280,300 16,740 6.0 1939 288,600 13,920 4.8 1941 301,900 17,400 5.8 1943 320,620 21,750 6.8 1945 340,500 27,190 8.0 1947 361,700 34,110 9.4 1949 384,200 35,700 9.3 1951 405,100 37,400 9.2 1953 424,200 39,100 9.2 1955 444,200 39,810 9.0 1957 465,000 39,330 8.5 15 Ncs 7.31 ♦ .31X 10 1930 1940 1950 1960 FIGURE 12-B MEMPHIS: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 TABLE XI-A ATLANTA, 6A: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ• 1920 200,616 1929 18,509 1930 270,366 1935 17,124 1937 20,223 1939 20,857 1940 302,288 1947 36,172 1950 331,314 1954 47,903 1958 48,662 1960 487,455 - p s 6. TJ o I ^ O i s c ® o t t O c ■H o o Oh C 0 1 S •P < 0 6 Pop 5 Manuf. N 4 X X J 1930 1940 1950 FIGURE 13-A 1960 ATLANTA, GAi POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) dod jo ^ 149 TABLE XI-B ATLANTA: POPULATION AND MANUFACTURING EMPLOYMENT BSTIMATBS, 1929-1957 Year Pop. Manuf. employ. Employ. % of pop. 1929 262,000 18,510 7.1 1931 275,200 18,050 6.6 1933 281,400 17,580 6.2 1935 287,500 17,120 6.0 1937 293,800 20,220 6.9 1939 300,000 20,860 7.0 1941 303,960 24,690 8.1 1943 310,210 28,520 9.2 1945 316,360 32,500 10.3 1947 322,410 36,170 11.2 1949 328,360 39,520 12.0 1951 345,910 42,880 12.4 1953 376,210 46,230 12.3 1955 405,210 48,090 11.9 1957 435,710 48,400 11.1 15 9.2 + .506X 1930 1940 1950 1960 FIGURE 13-B ATLANTA: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 150 TABLE XII-A COLUMBUS, OHIO: POPULATION AND MANUFACTURING EMPLOYMENT I Year Population Manuf.employ. 1920 237,031 1929 26,565 1930 290,564 1935 21,342 1937 23,311 1939 21,752 1940 306,087 1947 41,367 1950 375,901 1954 58,373 1958 54,772 1960 471,316 ■ p S 3 < D T j O S 3 r-1 « ft S a o © bO a •H 3 5 1 ftp O o ft t O 3 S 3 c t f S Pop, ^^9 Manuf. N 1930 1940 1950 FIGURE 14-A 1960 COLUMBUS, OHIO: POPULATION AND MANUFACTURING EMPLOYMENT (in log. sclae) f o o f pop 151 TABLE XII-B COLUMBUS: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop, Manuf. employ. Employ. % of pop. 1929 284,500 26,570 9.3 1931 292,100 24,820 8.5 1933 295,400 23,080 7.8 1935 298,700 21,340 7.1 1937 302,000 23,310 7.7 1939 305,000 21,750 6.7 1941 312,500 26,650 8.5 1943 325,870 31,560 9.7 1945 339,900 36,470 10.7 1947 354,500 41,370 11.7 1949 369,700 46,220 12.5 1951 384,540 51,080 13.3 1953 402,230 55,940 13.9 1955 420,730 57,470 13.7 1957 440,080 55,670 12.6 15r 10 10.3 * .486X 1960 1940 1930 1950 FIGURE 14-B COLUMBUS: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 152 TABLE XIII-A SEATTLE, WASH: POPULATION AND MANUFACTURING EMPLOYMENT Year population Manuf. employ. 1920 315,312 1929 23,003 1930 365,583 1935 16,717 1937 20,306 1939 20,352 1940 368,302 1947 50,214 1950 467,591 1954 65,150 1958 81,944 1960 557,087 c a ) £ •o o C 5 rH t o ft B a ) a o •rH P tO rH 3 bO C •H u ftp o o ft t o 1 a 6 Pop 5 'Manuf. N 4 X X J 1930 1940 FIGURE 15-A 1950 1960 SEATTLE, WASH: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) % o f pop 153 TABLE XIII-B SEATTLE* POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf• Employ. employ. % of pop. 1929 360,480 23,000 6.4 1931 365,850 20,900 5.7 1933 366,390 18,810 5.1 1935 366,930 16,720 4.6 1937 367,400 20,300 5.5 1939 368,010 20,400 5.5 1941 378,200 27,850 7.4 1943 398,070 35,300 8.9 1945 417,930 42,750 10.2 1947 437,800 50,210 11.5 1949 457,680 54,470 11.9 1951 476,390 58,740 12.3 1953 494,090 63,000 12.8 1955 511,890 69,350 13.5 1957 529,740 77,750 14.7 151 9 + .74X 1960 1940 1930 1950 FIGURE 15-B SEATTLE: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND* 1929-1957 154 TABLE XIV-A DENVER, COLO: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ. 1920 256,491 1929 16,239 1930 287,861 1935 11,884 1937 12,810 1939 11,477 1940 322,412 1947 30,876 1950 415,786 1954 33,458 1958 34,628 1960 493,887 p s & TJ o £ 3 H f l j Pi S £ 3 0 ) O •H hO P C 3 (|J *H rH £ h g S Pip O O Ph r t s c 6 Pop 5 Manuf• N 4 J J . 1930 1940 FIGURE 16-A 1950 1960 DENVER, COLO: POPULATION AND MANUFACTURING EMPLOYMENT (In log. scale) % o f pup 155 TABLB XIV-B DENVER: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf• employ. Employ. % of pop. 1929 284,650 16,200 5.7 1931 291,000 14,720 5.1 1933 297,900 13,310 4.5 1935 304,800 11,900 3.9 1937 311,800 12,800 4.1 1939 318,750 11,500 3.6 1941 331,200 16,350 4.9 1943 350,000 21,200 6.1 1945 368,800 26,050 7.1 1947 387,000 30,880 8.0 1949 406,000 31,610 7.8 1951 423,200 32,350 7.6 1953 438,900 33,090 7.5 1955 454,600 33,750 7.4 1957 470,250 34,330 7.3 15r NC= 6.04 + .275X 10 1930 1940 1950 FIGURE 16-B DENVER: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 156 TABLE XV-A CINCINNATI, OHIO: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ. 1920 401,247 1929 63,986 1930 451,160 1935 50,425 1937 61,116 1939 52,847 1940 455,610 1947 97,511 1950 503,998 1954 88,603 1958 76,383 1960 502,550 •P d 0 1 •d o C rH ( 0 &. a § •rH •P c d < D ho c •H u d d d.+> o o Ph ( 0 d a c d a Pop. Manuf. N 1$30 1940 1950 I960 FIGURE 17-A CINCINNATI, OHIO: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) f o o f pop 15? TABLE XV-B CINCINNATI: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf• Employ. employ• % of pop. 1929 446,100 64,000 14.3 1931 451,600 59,480 VOL3.3 1933 452,490 54,950 12.1 1935 453,380 50,430 11.1 1937 454,270 61,120 13.5 1939 455,160 52,850 11.6 1941 460,450 64,000 13.9 1943 470,120 75,170 16.0 1945 479,800 86,340 18.0 1947 489,400 97,510 19.9 1949 499,160 94,960 19 .0 1951 503,850 92,420 18.3 1953 503,560 89,880 17.8 1955 503,270 85,550 17.0 1957 502,980 79,440 15.8 20r 15 Nc= 15.43 t .456X 10 1930 1940 1950 1960 FIGURE 17-B CINCINNATI: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 158 TABLE XVI-A MINNEAPOLIS, MINN: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ. 1920 380,582 1929 35,704 1930 464,356 1935 26,602 1937 30,877 1939 26,109 1940 492,370 1947 61,942 1950 521,718 1954 65,732 1958 58,472 1960 482,872 C O •H ■P rH U 3 5 5 P - P O O Ph f l j <H c c f l 6 6 •p g R O C r H « J p. a C D bO a Pop, Manuf. N 1930 1940 1950 1960 FIGURE 18-A MINNEAPOLIS, MINN: POPULATION AND MANUFACTURING EMPLOYMENT dod j o g 159 TABLE XVI-B MINNEAPOLIS: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year pop. 1929 455,900 1931 467,150 1933 472,760 1935 478,360 1937 483,960 1939 489,560 1941 495,300 1943 501,170 1945 507,040 1947 512,910 1949 518,780 1951 517,800 1953 510,100 19 55 502,300 1957 494,500 Manuf. employ. Employ. % of pop. 35,700 7.8 32,670 7,0 29,640 6.3 26,600 5.6 30,880 6.4 26,110 5.3 35,060 7.1 44,020 8.9 52,980 10.4 61,940 12.1 63,020 12.1 64,100 12.4 65,180 12.8 63,920 12.7 60,290 12.2 15r 10 9.27 + .566X 1930 1940 1950 FIGURE 18-B MINNEAPOLIS: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 __i 1960 160 TABLE XVII-A BUFFALO, N.Y.: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf .employ. 1920 506,775 1929 68,854 1930 573,076 1935 59,758 1937 56,958 1939 45,869 1940 575,901 1947 87,568 1950 580,132 1954 86,568 1958 70,827 1960 532,759 ■p a a > 9 c o •H •P <0 6r a, § b0 C •H S h p, p O O a. t o <H 9 § Pop, Manuf. N 1930 1940 1950 1960 FIGURE 19-A BUFFALO, N.Y.: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) % o f pop 161 TABLE XVII-B BUFFALO: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. Employ. employ. % of pop* 1929 566,700 68,850 12.1 1931 573,300 62,490 10.9 1933 573,900 56,120 9.8 1935 574,500 49,760 8.7 1937 575,100 56,960 9.9 1939 575,600 45,870 8.0 1941 576,300 56,230 9.8 1943 577,200 66,580 11.5 1945 578,000 76,930 13.3 1947 578,900 87,280 15.1 1949 579,700 87,070 15.0 1951 575,400 86,870 15.1 1953 565,900 86,670 15.3 1955 556,500 82,630 14.8 1957 547,000 74,760 13.7 20 15 10 Nc- 12.2 ♦ .43X 1960 1930 1950 1940 FIGURE 19-B BUFFALO: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 162 TABLE XVI11-A HOUSTON, TEX: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ. 1920 138,276 1929 16,264 1930 292,352 1935 13,581 1937 17,086 1939 15,618 1940 384,514 1947 40,563 1950 596,163 1954 55,198 1958 65,187 1960 938,219 Pop C H r d Ph _ S S3 0) Manuf. N 1940 1950 1930 FIGURE 20-A HOUSTON, TEX: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) % o f pop 163 TABLE XVIII-B HOUSTON: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. employ. Employ. % or pop. 1929 276,000 16,260 5.9 1931 301,000 15,370 5.1 1933 319,800 14,480 4.5 1935 338,300 13,580 4.0 1937 356,700 17,090 4.8 1939 375,200 15,620 4.2 1941 405,000 21,850 5.4 1943 447,500 28,090 6.3 1945 489,900 34,330 7.0 1947 532,300 40,570 7.6 1949 574,700 44,740 7.8 1951 629,000 48,920 7.8 1953 697,800 53,100 7.6 1955 766,400 57,690 7.5 1957 835,000 62,680 7.5 15 6.2 + .263X 10 1960 1940 1950 1930 FIGURE 20-B HOUSTON: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 TABLE XIX-A BALTIMORE, MD: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ. 1920 733,826 1929 85,655 1930 804,874 1935 70,758 1937 80,386 1939 76,556 1940 859,100 1947 120,929 1950 949,708 1954 117,582 1958 111,757 1960 939,024 -p § & T> O G r H Cfl Pi G O •H ■P C O E < D & 0 G •H 2 3 P i +5 o o p. r t 'h G G c O B Pop, Manuf. N 1930 1940 1950 1960 FIGURE 21-A BALTIMORE, MD: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) % o f pop 165 TABLE XIX-B BALTIMORE: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf• employ. Employ. % of pop. 1929 797,670 85,660 10.7 1931 810,270 80,690 10.0 1933 821,080 75,730 9.2 1935 831,900 70,760 8.5 1937 842,740 80,390 9.5 1939 853,590 76,560 9.0 1941 868,000 87,640 10.1 1943 885,000 98,730 11.2 1945 903,790 109,820 12.2 1947 921,700 120,920 13.1 1949 939,800 119,970 12.8 1951 946,500 119,020 12.6 1953 944,360 118,060 12.5 1955 942,230 116,130 12.3 1957 940,090 113,210 12.0 15 10 Nc= 11.09 + .273X 1960 1940 1950 1930 FIGURE 21-B BALTIMORE: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 166 TABLE XX-A CLEVELAND, OHIO: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ. 1920 796,841 1929 146,881 1930 900,429 1935 114,161 1937 132,481 1939 112,092 1940 878,336 1947 223,640 1950 914,808 1954 204,773 1958 174,628 1960 876,050 a o •H + 3 a j i—I £ P h+5 O O P h CO 6 +» £ a > I x) o £ rH (0 P , B a ) W) £ • r l u £ L Pop, Manuf, N 1930 1940 1950 FIGURE 22-A 1960 CLEVELAND, OHIO: POPULATION AND MANUFACTURING EMPLOYMENT (in log, scale) dod j o ^ 16? TABLE XX-B CLEVELAND: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. Employ. employ. % of pop. 1929 890,060 146,900 16.5 1931 898,220 135,990 15.1 1933 893,800 125,070 14.0 1935 889.380 114,160 12.8 1937 884,960 132,480 15.0 1939 880,540 112,090 12.7 1941 881,900 139,970 15,9 1943 889,200 167,850 18.9 1945 896,500 195,730 21.8 1947 903,800 223,640 24.7 1949 911,000 218,300 24.0 1951 910,930 212,860 23.4 1953 907,050 207,500 22.9 1955 903,180 197,230 21.8 1957 899,300 182,200 20.3 25r • 20 Nc= 18.65 ♦ .752X 15 10 1930 1940 1950 1960 FIGURE 22-B CLEVELAND: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 168 TABLE XXI-A LOS ANGBLBS, CALIF: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf.employ• 1920 576,673 1929 76,023 1930 1,238,048 1935 57,446 1937 76,995 1939 71,366 1940 1,504,277 1947 167,156 1950 1,970,358 1954 268,806 1958 288,546 1960 2,479,015 • p S R o C H £fl P h _ a c s o o •H bO +2 a B.S o o d. r t 2 c a t ...... 1930 Pop, Manuf. N 1940 FIGURE 23 »A 1950 1960 L.A., CALIF: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) dod jo $ TABLE XXI-B LOS ANGBLBS: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. employ. Bmploy. % of pop. 1929 1.170,000 76,020 6.5 1931 1,263,000 69,840 5.5 1933 1,317,000 63,650 4.8 1935 1,371,000 57,470 4.2 1937 1,424,000 77,000 5.4 1939 1,477,000 71,370 4.8 1941 1,550,000 95,310 6.1 1943 1,644,000 119,260 7.3 1945 1,737,000 143,210 8.2 1947 1,830,000 167,160 9.1 1949 1,923,000 196,190 10.2 1951 2,020,000 225,230 11.2 1953 2,122,000 254,270 12.0 1955 2,224,000 273,730 12.3 1957 2,325,000 283,600 12.2 15 10 Nc= 7.99 + .61X 1930 1940 1950 1960 FIGURE 23-B LOS ANGELES: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND TOE TREND, 1929-1957 TABLE XXII-A NEW YORK, N.Y.s POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf ^employ. 1920 5,620,048 1929 563,249 1930 6,930,984 1935 474,756 1937 506,208 1939 512,666 1940 7,454,995 1947 940,235 1950 7,891,957 1954 947,847 1958 895,838 1960 7,781,984 ■p § R o C r H C t f & bO d • r l U a o •H P n J rH d d dtp o o p - t d «H d Pop, — •— •' Manuf• N 1930 1940 FIGURE 24-A 1950 1960 NEW YORK, N.Y.s POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) f o o f pop 171 TABLE XXII-B NEW YORK: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. employ. Employ. X of pop. 1929 6,805,000 563,250 8.3 1931 6,983,000 533,750 7.6 1933 7,088,000 504,260 7,1 1935 7,193,000 474,760 6.6 1937 7,298,000 506,210 6.9 1939 7,403,000 512,670 6.9 1941 7,499,000 619,560 8.3 1943 7,586,000 726,450 9.6 1945 7,673,000 833,340 10.9 1947 7,761,000 940,230 12.1 1949 7,848,000 942,400 12.0 1951 7,881,000 944,580 12.0 1953 7,859,000 946,750 12.0 1955 7,837,000 934,840 11.9 1957 7,815,000 908,840 11.6 15r 10 9.59 + .44X 1940 1930 1950 1960 FIGURE 24-B NEW YORK: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 TABLE XXI11-A DETROIT, MICH: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf•employ* 1920 993,678 1929 219,551 1930 1,568,662 1935 194,422 1937 235,341 1939 182,373 1940 1,623,452 1947 338,373 1950 1,849,568 1954 296,517 1958 204,409 1960 1,670,144 • p C a > & o §3 c § o W) ■p a c t 5 *H i H f n PhP o o pL, C t f c ( 0 a Pop. Manuf. N 1930 1940 1950 FIGURE 25-A 1960 DETROIT, MICH: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) dod j o % 173 TABLB XXIII-B DETROIT: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. Employ. .sa?1®*.!.. % of pop. 1929 1,510,000 219,550 14.5 1931 1,573,000 211,170 13.4 1933 1,584,000 202,790 12.8 1935 1,595,000 194,420 12.2 1937 1,607,000 235,340 14.6 1939 1,618,000 182,370 11.3 1941 1,645,000 221,370 13.5 1943 1,690,000 260,370 15.4 1945 1,735,000 299,370 17.3 1947 1,780,000 338,370 19.0 1949 1,826,000 326,420 18.0 1951 1,832,000 314,460 17.9 1953 1,796,000 302,500 16.9 1955 1,760,000 273,490 15.5 1957 1,724,000 227,440 13.2 20 15 Nc= 15.3 + .272X 10 1930 1940 1950 FIGURE 25-B 1960 DETROIT: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 174 TABLE XXIV-A CHICAGO, ILL: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf•employ. 1920 2,701,705 1929 405,399 1930 3,376,438 1935 311,599 1937 391,185 1939 347,839 1940 3,396,808 1947 667,407 1950 3,620,962 1954 615,737 1958 534,498 1960 3,550,404 •p c 0 } T3 O c © o •H bO + 2 c rH U 3 * o o p L , ( f l 1 OS s Pop. Manuf. N 1930 1940 FIGURE 26-A 1950 1960 CHICAGO, ILL: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) dod j o $ m TABLE XXIV-B CHICAGO: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. Employ. employ. % of pop. 1929 3,308,000 405,400 12.3 1931 3,378,000 374,100 11.1 1933 3,382,000 342,900 10.1 1935 3,386,000 311,600 9.2 1937 3,391,000 391,200 11.5 1939 3,395,000 347,800 10.2 1941 3,319,000 427,700 12.5 1943 3,464,000 507,600 14.7 1945 3,509,000 587,500 16.7 1947 3,554,000 667,400 18.8 1949 3,598,000 652,600 18.1 1951 3,614,000 637,900 17.7 1953 3,600,000 623,100 17.3 1955 3,586,000 595,400 16.6 1957 3,572,000 554,800 15.5 20 15 NC= 14.15 ♦ .595X 10 1940 1950 1960 1930 FIGURB 26-B CHICAGO: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 17 6 TABLE XX-A PHILADELPHIA, PA: POPULATION AND MANUFACTURING EMPLOYMENT Year Population Manuf. employ. 1920 1,823,777 1929 246,908 1930 1,950,961 1935 199,261 1937 213,851 1939 196,356 1940 1,931,334 1947 328,630 1950 2,071,605 1954 309,792 1958 287,027 1960 2,002,512 p £ < D -£ O £ rH n J P, £ o •H P n J i - l £ § bO £ •H U . £ P,P o o p l , t a «H £ £ £ a Pop, Manuf. N 1930 1940 1950 FIGURE 27-A 1960 PH I LA, PA: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) f a O f pop 17? TABLE XXV-B PHILADELPHIA: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf• Employ• employ. % of Pop. 1929 1,938,000 246,900 12.7 1931 1,949,000 231,020 11.9 1933 1,945,000 215,140 11.1 1935 1,941,000 199,260 10.3 1937 1,937,000 213,850 11.0 1939 1,933,000 196,360 10.2 1941 1,943,000 229,430 11.8 1943 1,972,000 262,490 13.3 1945 2,000,000 295,560 14.8 1947 2,029,000 328,630 16.2 1949 2,057,000 323,240 15.7 1951 2,065,000 317,860 15.4 1953 2,051,000 312,480 15.2 1955 2,037,000 304,100 14.9 1957 2,023,000 292,720 14.5 20r 15 Nq= 13.26 + .36X 10 1930 1940 1950 1960 FIGURE 27-B PHILADELPHIA: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 178 TABLE XXVI-A UNITED STATES: POPULATION AND MANUFACTURING EMPLOYMENT Year Population* Manuf.employ. 1920 54,305,000 1929 9,660,000 1930 69,161,000 1935 8,262,000 1937 9,786,000 1939 9,527,000 1940 74,705,000 1947 14,294,000 1950 89,306,000 1954 16,126,000 1958 15,394,000 1960 113,056,000 *Urban population in terms of the old definition. ■ p 5 R o So. s •H P 0 5 a Q ) g a 8 bO •H iH P .-P O O Ph 05 Pop. Manuf. N 1930 1940 1950 FIGURE 28-A 1960 UNITED STATES: POPULATION AND MANUFACTURING EMPLOYMENT (in log. scale) dod j o $ 179 TABLE XXVI-B UNITED STATES: POPULATION AND MANUFACTURING EMPLOYMENT ESTIMATES, 1929-1957 Year Pop. Manuf. employ. Employ. % of pop 1929 67,674,000 9,660,000 14.3 1931 69,715,000 8,109,000* 11.6 1933 70,819,000 6,558,000 9.3 1935 71,929,000 8,262,000 11.5 1937 73,037,000 9,786,000 13.4 1939 74,147,000 9,527,000 12.8 1941 76,164,000 10,718,000* 14.1 1943 79,083,000 11,909,000* 15.1 1945 82,003,000 13,100,000* 16.0 1947 84,924,000 14,294,000 16.8 1949 87,846,000 13,567,000 15.4 1951 91,680,000 15,310,000 16.7 1953 96,427,000 16,693,000 17.3 1955 101,176,000 15,583,000* 15.4 1957 105,926,000 15,457,000* 14.9 *The Bureau of Census estimates. 20 15 Nc= 14.3 ♦ .37X 10 1940 1950 1930 1960 FIGURE 28-B UNITED STATES: PERCENTAGE OF MANUFACTURING EMPLOYMENT AND THE TREND, 1929-1957 APPENDIX B RETAIL EMPLOYMENT AND CITY SIZE TABLE XXVII MEMPHIS: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 16,572 16,570 6.8 1931 12,870 5.0 1933 9,163 9,160 3.5 1935 14,121 14,120 5.2 1937 15,680 5.6 1939 17,226 17,230 6.0 1941 19,540 6.5 1943 21,850 6.8 1945 24,160 7.1 1947 26,470 7.3 1948 27,633 1949 27,830 7.2 1951 28,250 7.0 1953 28,660 6.8 1954 28,872 1955 29,380 6.6 1957 30,410 6.5 1958 30,915 • • • • • • ■— • • ( ■ - • • • i l Nca 6.26 + I I • « • 14X i 1930 1940 1950 FIGURE 29 MEMPHIS: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 1960 % o f pop 182 TABLE XXVIII ATLANTA: RETAIL EMPLOYMENT 1929-1958 Year Actual Estimate * of pop. 1929 21,575 21,580 8.2 1931 17,520 6.4 1933 13,461 13,460 4.8 1935 19,570 19,570 6.8 1937 21,710 7.4 1939 23,845 23,850 7.9 1941 26,390 8.7 1943 28,930 9.3 1945 31,480 10.0 1947 34,040 10.6 1948 35,318 1949 35,650 10.9 1951 36,330 10.5 1953 37,000 9.8 1954 37,339 1955 39,900 9.9 1957 45,290 10.4 1958 47,939 8.77 + .334X 5 1930 1940 1950 FIGURE 30 ATLANTA: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 J 1960 % o f pop 183 TABLE XXIX COLUMBUS: RETAIL EMPLOYMENT. 1929-1958 Year Actual Estimate % of pop. 1929 18,987 18,990 6.7 1931 15,570 5.3 1933 12,144 12,140 4.1 1935 17,007 17,010 5.7 1937 18,800 6.2 1939 20,584 20,580 6.7 1941 22,440 7.2 1943 24,310 7.5 1945 26,180 7.7 1947 28,050 7.9 1948 28,988 1949 29,410 8.0 1951 30,260 7.9 1953 31,110 7.7 1954 31,533 1955 31,570 7.5 1957 31,640 7.2 1958 31,683 6.7 ♦ .185X 1930 1940 1950 1960 FIGURE 31 COLUMBUS: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 184 TABLE XXX SEATTLE: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 27,093 27,090 7.5 1931 21,660 5.9 1933 16,229 16,230 4.4 1935 21,185 21,190 5.8 1937 22,650 6.2 1939 24,111 24,110 6.6 1941 26,350 7.0 1943 28,590 7.2 1945 30,830 7.4 1947 33,070 7.6 1948 34,186 1949 34,540 7.5 1951 35,230 7.4 1953 35,930 7.3 1954 36,276 1955 36,940 7.2 1957 38,280 7.2 1958 38,950 10 r 118X 1930 1940 1950 1960 FIGURE 32 SEATTLE: PERCENTAGE OP RETAIL EMPLOYMENT AND THE TREND, 1929-1957 dod j o % 185 TABLE XXXI DENVER: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 21,932 21,930 7.7 1931 17,730 6.1 1933 13,522 13,520 4.5 1935 15,741 15,740 5.2 1937 18,660 6.0 1939 21,582 21,580 6.8 1941 23,820 7.2 1943 26,060 7.4 1945 28,290 7.7 1947 30,530 7.9 1948 31,651 1949 31,740 7.8 1951 31,940 7.5 1953 32,120 7.3 1954 32,218 1955 33,160 7.3 1957 35,040 7.4 1958 35,980 10 Nr» 6.92 + .127X 1930 1940 1950 1960 FIGURE 33 DENVER: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 186 TABLE XXXII CINCINNATI: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 29,979 29,980 6.7 1931 25,360 5.6 1933 20,733 20,730 4.6 1935 26,517 26,520 5.8 1937 27,570 6.1 1939 28,605 28,610 6.3 1941 30,830 6.7 1943 33,050 7.0 1945 33,270 7.4 1947 37,500 7.7 1948 38,622 1949 38,280 7.7 1951 37,590 7.5 1953 36,900 7.3 1954 36,555 1955 36,790 7.3 1957 37,270 7.4 1958 37,508 10 Nce 6.74 + .156X 1930 1940 1950 1960 FIGURE 34 CINCINNATI: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop. 187 TABLE XXXIII MINNEAPOLIS: RETAIL EMPLOYMENT. 1929-1958 Year Actual Estimate % Of Pop. 1929 32,694 32,690 7.2 1931 27,350 5.9 1933 21,997 22,000 4.7 1935 30,114 30,110 6.3 1937 31,540 6.5 1939 32,958 32,960 6.7 1941 35,960 7.3 1943 38,970 7.8 1945 41,990 8.3 1947 45,020 8.8 1948 46,536 1949 45,880 8.8 1951 44,550 8.6 1953 43,220 8.5 1954 42,554 1955 42,010 8.4 1957 40,920 8.3 1958 40,382 10 7.47 + .225X 1930 1940 1950 1960 FIGURE 35 MINNEAPOLIS: PERCENTAGE OP RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 188 TABLE XXXIV BUFFALO: RETAIL EMPLOYMENT. 1929-1958 Year Actual Estimate % of pop. 1929 31,000 31,000 5.5 1931 24,950 4.4 1933 18*890 18,890 3.3 1935 26,434 26,430 4.6 1937 27,790 4.8 1939 29,136 29,140 5.1 1941 31,760 5.5 1943 34,380 6.0 1945 37,000 6.4 1947 39,620 6.8 1948 40,927 1949 40,880 7.1 1951 40,820 7.1 1953 40,760 7.2 1954 40,734 1955 39,850 7.2 1957 38,100 7.0 1958 37,220 10 Nca 5.87 4 .243X 1930 1940 1950 1960 FIGURE 36 BAFFALO: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 189 TABLE XXXV HOUSTON; RETAIL EMPLOYMENT; 1929-1958 Year Actual Estimate % of pop. 1929 18,411 18,410 6.7 1931 15,540 5.2 1933 12,657 12,660 4.0 1935 15,358 15,360 4.5 1937 19,210 5.4 1939 23,056 23,060 6.1 1941 26,760 6.6 1943 30,470 6.8 1945 34,200 7.0 1947 37,930 7.1 1948 39,809 1949 41,070 7.1 1951 43,600 6.9 1953 46,130 6.6 1954 47,388 1955 48,760 6.4 1957 51,510 6.2 1958 52,882 10 Nc= 6.17 « • .085 5 1930 1940 1950 1960 FIGURE 37 HOUSTON; PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop. 190 TABLE XXXVI BALTIMORE: RETAIL EMPLOYMENT; 1929-1958 Year Actual Estimate % of pop. 1920 42,238 42,240 5,3 1931 36,200 4.5 1933 30,164 30,160 3.7 1935 41,495 41,500 5.0 1937 43,870 5.2 1939 46,240 5.4 1941 51,340 5.9 1943 56,440 6.4 1945 61,550 6.8 1947 66,670 7.2 1948 69,230 1949 68,780 7.3 1951 67,880 7.2 1953 66,990 7.1 1954 66,542 1955 67,050 7.1 1957 68,070 7.2 1958 68,576 10 r 234X 1930 1940 1950 1960 FIGURE 38 BALTIMORE: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 $ o f pop 191 TABLE XXXVII CLEVELAND: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 51,611 51,610 5.8 1931 42,640 4.7 1933 33,658 33,660 3.8 1935 47,601 47,600 5.4 1937 48,900 5.5 1939 50,198 50,200 5.7 1941 54,350 6.2 1943 58,500 6.6 1945 62,650 7.0 1947 66,810 7.4 1948 68,888 1949 67,950 7.5 1951 66,060 7.3 1953 64,170 7.1 1954 63,225 1955 62,900 7.0 1957 62,250 6.9 1958 61,922 10 Nc« 6.26 4 .199X 1930 1940 1950 1960 FIGURE 39 CLEVELAND: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 192 TABLE XXXVIII LOS ANGELES: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 84,477 84,480 7.2 1931 70,550 5.6 1933 56,608 56,610 4.3 1935 78,424 78,420 5.7 1937 85,650 6.0 1939 92,882 92,880 6.3 1941 101,520 6.6 1943 110,150 6.7 1945 118,790 6.8 1947 1948 131,737 127,420 7.0 1949 130,800 6.8 1951 128,920 6.4 1953 1954 126,092 127,030 6.0 1955 132,120 5.9 1957 144,190 6.2 1958 150,220 10 — * -------------- ; r Nc= 6*2 + .036X 1___________ 1___________ 1___________ 1___________ 1__ 1930 1940 1950 FIGURB 40 __1 1960 LOS ANGELES: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 193 TABLE XXXIX NEW YORK! RETAIL EMPLOYMENT* 1929-1958 Year Actual Estimate % of pop. 1929 344,817 344,820 5.1 1931 290,580 4.2 1933 236*344 236,340 3.3 1935 323,590 323,590 4.5 1937 329*710 4.5 1939 335,833 335,830 4.5 1941 356,410 4.8 1943 376,990 5.0 1945 397,580 5.2 1947 418,170 5.4 1948 428*480 1949 423,630 5.4 1951 413,920 5.3 1953 404,220 5.1 1954 399,371 1955 403,860 5.2 1957 412,850 5.3 1958 417,343 10- * , * * : * ■ • r ' --] ' ' 1 Nc= 4.9 4 .088X 1 __________ I ___________I ___________1 __________ I ___________! — 1930 1940 1950 FIGURE 41 __i 1960 NEW YORK: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 194 TABLE XL DETROIT: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1989 74,180 74,180 4.9 1931 60,520 3.8 1933 46,847 46,850 3.0 1935 68,033 68,030 4.3 1937 73,910 4.6 1939 79,780 79,780 4.9 1941 87,380 5.3 1943 94,990 5.6 1945 102,610 5.9 1947 110,230 6.2 1948 114,038 1949 113,060 6.2 1951 111,100 6.1 1953 109,140 6.1 1954 108,163 1955 104,750 6.0 1957 97,920 5.8 1958 94,500 10 Nc» 5.25 + .151X 1930 1940 1950 1960 FIGURE 42 DETROIT: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 195 TABLE XLI CHICAGO: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 200,602 200,600 6.1 1931 161,580 4.8 1933 122,551 122,550 3.6 1935 159,173 159,170 4.7 1937 171,810 5.1 1939 184,449 184,450 5.4 1941 198,740 5.8 1943 213,030 6.1 1945 227,330 6.5 1947 241,620 6.8 1948 248,763 1949 244,560 6.8 1951 236,150 6.5 1953 227,750 6.3 1954 223,545 1955 223,950 6.2 1957 224,750 6.3 1958 225,158 10r Nc= 5.8 + .141X 1930 1940 1950 1960 FIGURE 43 CHICAGO: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 f o o f pop 196 TABLE XLII PHILADELPHIA: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 110,483 110,480 5.7 1931 90,610 4.6 1933 70,738 70,740 3.6 1935 90,006 90,010 4.6 1937 90,370 4.7 1939 90,731 90,730 4.7 1941 99,730 5.1 1943 108,730 5.5 1945 117,730 5.9 1947 126,740 6.2 1948 131,251 1949 128,530 6.2 1951 123,090 6.0 1953 117,640 5.7 1954 114,919 1955 114,200 5.6 1957 112,770 5.6 1958 112,049 10r Nc= 5.3 * .106X 1930 1940 1950 1960 FIGURE 44 PHILADELPHIA: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 197 TABLB XLIII UNITED STATES: RETAIL EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 4,287,000 4,287,000 6.3 1931 3,861,000 5.5 1933 3,436,000 3,436,000 4.9 1935 3,898,000 3,898,000 5.4 1937 4,250,000 5.8 1939 4,600,000 4,600,000 6.2 1941 5,150,000 6.8 1943 5,700,000 7.2 1945 6,250,000 7.6 1947 6,800,000 8.0 1948 7,084,000 1949 7,090,000 8.1 1951 7,100,000 7.7 1953 7,110,000 7.4 1954 7,124,000 1955 7,320,000 7.2 1957 7,710,000 7.3 1958 7,911,000 10 6.76 + .179X 1930 1940 1950 1960 FIGURE 45 UNITED STATES: PERCENTAGE OF RETAIL EMPLOYMENT AND THE TREND, 1929-1957 APPENDIX C WHOLESALE EMPLOYMENT AND CITY SIZE % o f pop TABLfi XLXV MEMPHIS: WHOLESALE EMPLOYMENT; 1929-1958 Year Actual Estimate % of pop. 1929 9,449 9,450 3.9 1931 8,140 3.2 1933 6,843 6,840 2.6 1935 7,465 7,470 2.7 1937 8,200 2.9 1939 8,937 8,940 3.1 1941 10,310 3.4 1943 11,680 3.6 1945 13,050 3.8 1947 14,420 4.0 1948 15,111 1949 15,610 4.1 1951 16,610 4.1 1953 17,620 4.2 1954 18,119 1955 18,040 4.1 1957 17,870 3.8 1958 17,781 10 05X 1930 1940 1950 1960 PIGURE 46 MEMPHIS: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 f o o f pop 200 TABLE XLV ATLANTA: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 11,602 11,600 4.4 1931 9,570 3.5 1933 7,543 7,540 2.7 1935 9,473 9,470 3.3 1957 10,970 3.7 1939 12,473 12,470 4.2 1941 15,300 5.0 1943 18,140 5.8 1945 20,970 6.6 1947 23,810 7.4 1948 25,420 1949 25,710 7.8 1951 26,680 7.7 1953 27,650 1954 28,132 1955 28,490 7.0 1957 29,230 6.7 1958 29,601 10 Nc* 5.5 ♦ .35X 1930 1940 1950 1960 PIGURB 47 ATLANTA: PERCENTAGE OP WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 201 TABLE XLVI COLUMBUS: WHOLBSALB EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 6,584 6,580 2.3 1931 5,750 2.0 1933 >4,922 4,920 1.7 1935 4,519 4,520 1.5 1937 5,120 1.7 1939 5,717 5,720 1.9 1941 6,620 2.1 1943 7,520 2.3 1945 8,420 2.5 1947 9,320 2.6 1948 9,777 1949 9,910 2.7 1951 10,170 2.6 1953 10,440 2.6 1954 10,568 1955 10,810 2.6 1957 11,290 2.6 1958 11,533 10 Nc= 2.2 ♦ .069X 1940 1930 1950 1960 FIGURE 48 COLUMBUS: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 202 TABLE XLVII SEATTLE: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % Of pop. 1929 14,421 14,420 4.0 1931 12,010 3.3 1933 9,602 9,600 2.6 1935 10,969 10,970 3.0 1937 12,200 3.3 1939 13,449 13,450 3.7 1941 14,900 3.9 1943 16,370 4.1 1945 17,840 4.3 1947 19,300 4.4 1948 20,045 1949 20,420 4.5 1951 21,180 4.4 1953 21,940 4.4 1954 22,328 1955 22,710 4.4 1957 23,460 4.4 1958 23,842 10 Ncs 3.9 + .105 1930 1940 1950 1960 FIGURB 49 SEATTLE: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 f o o f pop 203 TABLE XLVIII DENVER: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 10,119 10,120 3*6 1931 8,910 3.1 1933 7,710 7,710 2.6 1935 7,431 7,430 2.4 1937 8,670 2.8 1939 9,930 9,930 3.1 1941 11,990 3.6 1943 14,050 4.0 1945 16,120 4.4 1947 18,180 4.7 1948 19,222 1949 18,910 4.7 1951 18,300 4.3 1953 17,690 4.0 1954 17,379 1955 18,170 4.0 1957 19,750 4.2 1958 20,539 10 r NC= 3.7 ♦ .121X 1930 ' 1940 ' 1950 FIGURE 50 1960 DENVER: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 204 TABLE XLIX CINCINNATI: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 16,574 16,570 3.7 1931 14,680 3.3 1933 12,784 12,780 2.8 1935 13,090 13,090 2.9 1937 13,780 3.0 1939 14,472 14,470 3.2 1941 15,820 3.4 1943 17,180 3.7 1945 18,530 3.9 1947 19,890 4.1 1948 20,574 1949 20,680 4.1 1951 20,900 4.1 1953 21,150 4.2 1954 21,235 1955 21,150 4.2 1957 20,960 4.2 1958 20,867 10 Nc« 3.7 ♦ .095X 1930 1940 1950 1960 FIGURB 51 CINCINNATI: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 TABLE L MINNEAPOLIS: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 17,423 17,420 3*8 1931 18,400 3.9 1933 19,393 19,390 4.1 1935 21,195 21,200 4.4 1937 22,670 4.7 1939 24,154 24,150 4.9 1941 24,510 4.9 1943 24,870 5.0 1945 25,240 5.0 1947 25,600 5.0 1948 25,804 1949 25,830 5.0 1951 25,880 5.0 1953 25,940 5.1 1954 25,964 1955 26,080 5.2 1957 26,340 5.3 1958 26,465 Pu o c x o 10 Nc= 4,8 ♦ .096X 1930 1940 FIGURE 52 1950 MINNEAPOLIS: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 205 1960 % o f pop TABLE LI BAPPALO: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 14,257 14,260 2.5 1931 12,300 2.1 1933 10,331 10,330 1.8 1935 9,080 9,080 1.6 1937 9,860 1.7 1939 10,639 10,640 1.8 1941 12,140 2.1 1943 13,640 2.4 1945 15,140 2.6 1947 16,640 2.9 1948 17,388 1949 17,600 3.0 1951 18,020 3.1 1953 18,440 3.3 1954 18,653 1955 18,480 3.3 1957 18,130 3.3 1958 17,962 10 2.5 + .118X I960 1940 1930 1950 FIGURE 53 BUFFALO: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 f o o f pop 207 TABLE LII HOUSTON: WHOLESALE EMPLOYMENT; 1929-1958 Year Actual Estimate % of pop. 1929 7,354 7,350 2.7 1931 7,260 2,4 1933 7,167 7,170 2,2 1935 7,259 7,260 2,1 1937 9,100 2,6 1939 10,904 10,900 2.9 1941 13,280 3.3 1943 15,660 3.5 1945 18,040 3.7 1947 20,420 3.8 1948 21,618 1949 22,600 3.9 1951 24,570 3.9 1953 26,550 3.8 1954 27,335 1955 28,910 3.8 1957 31,640 3.8 1958 33,007 10 N(j* 3.2 + .134X 1930 1940 1950 1960 FIGURE 54 HOUSTON: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 208 TABLE LIII BALTIMORE: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 18,038 18,040 2.3 1931 16,600 2.0 1933 15,149 15,150 1.8 1935 15,072 15,070 1.8 1937 16,390 1.9 1939 17,715 17,720 2.1 1941 19,600 2.3 1943 21,490 2.4 1945 23,380 2.6 1947 25,270 2.7 1948 26,209 1949 26,190 2.8 1951 26,150 2.8 1953 26,120 2.8 1954 NA 1955 26,080 2.8 1957 26,040 2.8 1958 26,015 NOTE: NA means Not Available. 10 Ncr 2.4 + .077X 1930 1940 1950 1960 FIGURE 55 BALTIMORE: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 209 TABLB LIV CLEVELAND: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 23,403 23,400 2.6 1931 20,880 2.3 1933 18,362 18,360 2.1 1935 21,502 21,500 2.4 1937 22,520 2.5 1939 23,539 23,540 2.7 1941 26,500 3.0 1943 29,450 3.3 1945 32,400 3.6 1947 35,360 3.9 1948 36,482 1949 37,300 4.1 1951 38,240 4.2 1953 39,180 4.3 1954 39,650 1955 39,300 4.4 1957 38,590 4.3 1958 38,231 10 r Nc= 3.3 ♦ .18X 1930 1940 1950 1960 FIGURE 56 CLEVELAND: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 TABLE LV LOS ANGELES: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 37,314 37,310 3.2 1931 36,630 2.9 1933 28,745 28,750 2.2 1935 34,820 34,820 2.5 1937 38,110 2.7 1939 41,411 41,410 2.8 1941 46,880 3.0 1943 52,360 3.2 1945 57,840 3.3 1947 63,320 3.5 1948 66,063 1949 67,290 3.5 1951 69,750 3.5 1953 72,210 3.4 1954 73,444 1955 75,180 3.4 1957 78,660 3.4 1958 80,405 ior • o. o P h < H o \ s 5 . Nc* 3.1 t .066X - ■ • — » • ■ — • 1930 1940 FIGURE 57 1950 LOS ANGELES: PERCENTAGE OP WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 210 1960 % o f pop 211 TABLE LVI NEW YORK: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of POP* 1929 222,257 222,260 3.3 1931 188,490 2.7 1933 154,714 154,710 2.2 1935 199,318 199,320 2.8 1937 206,860 2.8 1939 241,405 241,410 2.9 1941 239,400 3.2 1943 264,400 3.5 1945 289,390 3.8 1947 314,390 4.1 1948 326,896 1949 320,320 4.1 1951 307,170 3.9 1953 294,020 3.7 1954 287,443 1955 289,660 3.7 1957 294,090 3.8 1958 296,305 10 Nc= 3*4 + .065X ■ » * * • • • • • 1930 1940 1950 1960 FIGURE 58 NEW YORK: PERCENTAGE OP WHOLESALE EMPLOYMENT AND TOE TREND, 1929-1957 % o f pop 212 TABLE LVII DETROIT: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 24,263 24,260 1.6 1931 22,580 1.4 1933 20,890 20,890 1.3 1935 22,727 22,730 1.4 1937 25,040 1.6 1939 27,350 27,350 1.7 1941 31,280 1.9 1943 35,220 2.1 1945 39,160 2.3 1947 1948 45,079 43,110 2.4 1949 45,360 2.5 1951 45,920 2.5 1953 1954 46,759 46,480 2.6 1955 1957 1958 45,722 46,500 45,980 2.6 10 Nc= 2 + ,108X 1930 1940 1950 1960 FIGURE 59 DETROIT: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 TABLE LYIII CHICAGO: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 135,083 135,080 4.1 1931 102,690 3.0 1933 70,294 70,290 2.1 1935 83,349 83,350 2.5 1937 89,420 2.6 1939 95,494 95,490 2.8 1941 104,980 3.1 1943 114,470 3.3 1945 123,960 3.5 1947 133,450 3.8 1948 138,194 1949 137,060 3.8 1951 134,800 3.7 1953 132,540 3.7 1954 131,412 1955 131,630 3.7 1957 132,080 3.7 1958 132,302 10 * • ft o ft « H o 5 • Ncr 3.3 ♦ .026X , • • • • • • ----- a • --------- 9 • • * .1 1 1930 1940 FIGURE 1950 60 CHICAGO: PERCENTAGE OP WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 213 ! 1960 % o f pop 214 TABLE LIX PHILADELPHIA: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 50,801 50,800 2.6 1931 42,390 2.2 1933 33,980 33,980 1.7 1935 37,347 37,350 1.9 1937 39,800 2.1 1939 42,257 42,260 2.2 1941 47,590 2.4 1943 52,920 2.7 1945 58,260 2.9 1947 63,590 3.1 1948 66,265 1949 66,140 3.2 1951 65,880 3.2 1953 65,620 3.2 1954 65,479 19 55 64,910 3.2 1957 63,760 3.2 1958 63,178 p Nc= 2.7 ♦ , .— 1_— *--• - • 102X # - -----• a ---- • . • • 1 -1 -- 1 1930 1940 1950 FIGURE 61 PHILADELPHIA: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND, 1929-1957 1960 % o f pop 215 TABLE LX UNITED STATES: WHOLESALE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 1,510,494 1,510,000 2.2 1931 1,304,000 1.9 1933 1,096,977 1,097,000 1.5 1935 1,260,553 1,261,000 1.8 1937 1,411,000 1.9 1939 1,561,948 1,562,000 2.1 1941 1,761,000 2.3 1943 1,961,000 2.5 1945 2,161,000 2.6 1947 2,362,000 2.8 1948 2,463,433 1949 2,484,000 2.8 1951 2,526,000 2.8 1953 2,568,000 2.7 1954 2,590,236 1955 2,642,000 2.6 1957 2,745,000 2.6 1958 2,797,341 10 r Nc= 2.3 ♦ .076X -i 8 1930 1940 1950 1960 FIGURE 62 UNITED STATES: PERCENTAGE OF WHOLESALE EMPLOYMENT AND THE TREND. 1929-1957 APPENDIX D SERVICE EMPLOYMENT AND CITY SIZE f o o f pop 217 TABLE LXI MEMPHIS: SERVICE EMPLOYMENT 1929-1958 Year Actual Estimate % of pop. 1929 1,880 .77 1931 1,600 .62 1933 1,321 1,320 .50 1935 2,185 2,190 .80 1937 3,880 1.38 1939 5,584 5,580 1.93 1941 5,820 1.93 1943 6,070 1.89 1945 6,320 1.86 1947 6,570 1.82 1948 6,701 1949 7,360 1.92 1951 8,680 2.14 1953 10,000 2.36 1954 10,679 1955 11,330 2.55 1957 12,630 2.72 1958 13,283 Nc= 1.55 ♦ .147X 1930 1940 1950 1960 FIGURE 63 MEMPHIS: PERCENTAGE OF SERVICE EMPLOYMENT AND THE TREND, 1929-1957 % of pop 218 TABLE LXII ATLANTA: SBRVICB EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 3,390 1.29 1931 2,890 1.05 1933 2,388 2,390 • 85 1935 3,508 3,510 1.22 1937 5,520 1.88 1939 7,531 7,530 2.51 1941 8,150 2.68 1943 8,780 2.83 1945 9,410 2.97 1947 10,040 3.11 1948 10,355 1949 11,130 3.39 1951 12,680 3.67 1953 14,230 3.78 1954 15,012 1955 16,270 4.02 1957 18,790 4.31 1958 20,051 10 r Nc* 2.63 + .247X 1950 1940 1930 FIGURE 64 ATLANTA: PERCENTAGE OP SERVICE EMPLOYMENT AND THE TREND, 1929-1957 / 219 TABLE LXIII COLUMBUS: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 2,030 .71 1931 1*730 .59 1933 1,432 1,430 .48 1935 2,092 2,090 .70 1937 3,040 1.01 1939 3,995 4,000 1.31 1941 4,360 1.40 1943 4,720 1.45 1945 5,090 1.50 1947 5,450 1.54 1948 5,639 1949 6,450 1.74 1951 8,090 2.10 1953 9,730 2.42 1954 10,546 1955 10,640 2.53 1957 10,840 2.46 1958 10,941 10 P h o (X « H o NC= 1.46 * .15X 1930 1940 1950 1960 FIGURE 65 COLUMBUS: PERCENTAGE OF SERVICE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 220 TABLE LXIV SEATTLE: SERVICE EMPLOYMENT* 1929-1958 Year Actual Estimate % of pop. 1929 3,800 1.05 1931 3,240 .89 1933 2,678 2,690 .73 1935 4,925 4,930 1.34 1937 8,040 2.19 1939 11,147 11,150 3.03 1941 10,230 2.70 1943 9,320 2.34 1945 8,400 2.01 1947 7,490 1.71 1948 7,034 1949 8,090 1.77 1951 10,230 2.15 1953 12,370 2.30 1954 13,440 1955 14,360 2.81 1957 16,220 3.06 1958 17,147 10r Nc= 2.02 ♦ .118X 1930 1940 1950 1960 FIGURE 66 SEATTLE: PERCENTAGE OF SERVICE EMPLOYMENT AND THE TREND, 1929-1957 % of pop 221 TABLE LXV DENVER: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate * of pop. 1929 2,790 .98 1931 2,380 • 82 1933 1,972 1,970 .66 1935 2,848 2,850 .94 1937 4,490 1.41 1939 5,917 5,920 1.86 1941 6,180 1.87 1943 6,450 1.84 1945 6,720 1.82 1947 6,990 1.81 1948 7,127 1949 7,950 1.96 1951 9,600 2.27 1953 11,250 2.56 1954 12,074 1955 12,890 2.84 1957 14,540 3.09 1958 15,359 10 Nc* 1.78 ♦ .154X 1930 1940 1950 1960 PIGURE 67 DENVER: PERCENTAGE OP SERVICE EMPLOYMENT AND THE TREND, 1929-1957 f o o f pop 222 TABLB LXVI CINCINNATI: SERVICB EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 4,590 1.03 1931 3,910 .87 1933 3,228 3,230 .71 1935 4,395 4,400 .97 1937 5,880 1.29 1939 7,345 7,350 1.61 1941 7,820 1.70 1943 8,290 1.76 1945 8,760 1.83 1947 9,230 1.89 1948 9,468 1949 10,630 2.13 1951 12,960 2.57 1953 15,290 3.04 1954 16,445 1955 16,720 3.32 1957 17,270 3.43 1958 17,537 10 Nc- 1.88 + J.88X 1930 1940 1950 1960 FIGURE 68 CINCINNATI: PERCENTAGE OF SERVICE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop. 223 TABLE LXVII MINNEAPOLIS: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 * 4,010 .88 1931 3,420 .73 1933 2,826 2,830 .60 1935 3,975 3,980 .83 1937 5,780 1.19 1939 7,594 7,590 1.55 1941 7,870 1.59 1943 8,160 1.63 1945 8,450 1.67 1947 8,740 1.70 1948 8,887 1949 10,000 1.93 1951 12,220 2.36 1953 14,440 2.83 1954 15,554 1955 16,230 3.23 1957 17,600 3.56 1958 18,282 10 192X 1.75 1930 1940 1950 1960 FIGURE 69 MINNEAPOLIS: PERCENTAGE OF SERVICB EMPLOYMENT AND THB TREND, 1929-1957 % o f pop 224 TABLE LXVIII BUFFALO: SERVICE EMPLOYMENT, 1929-1938 Year Actual Estimate % of pop. 1929 3,830 • 68 1931 3,210 .56 1933 2,587 2,590 .45 1935 3,040 3,040 .53 1937 4,600 .80 1939 6,157 6,160 1.07 1941 6,520 1.13 1943 6,880 1.19 1945 7,240 1.25 1947 7,610 1.31 1948 7,789 1949 8,620 1.49 1951 10,290 1.79 1953 11,960 2.11 1954 12,791 1955 12,950 2.33 1957 13,270 2.43 1958 13,426 10 Nc= 1.27 + .139X 1940 1930 1950 1960 FIGURE 70 BUFFALO: PERCENTAGE OF SERVICE EMPLOYMENT AND THE TREND, 1929-1957 i c o f pop. 225 TABLE LXIX HOUSTON: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 3,570 1.29 1931 3,040 1.01 1933 2,508 2,510 .78 1935 4,321 4,320 1.28 1937 7,540 2.11 1939 10,746 10,750 2.87 1941 10,730 2.65 1943 10,720 2.40 1945 10,700 2.18 1947 10,690 2.01 1948 10,676 1949 11,980 2.08 1951 14,580 2.32 1953 17,190 2.46 1954 18,487 1955 20,090 2.62 1957 23,290 2.79 1958 24,887 10 Nc« 2.06 + .109X 1930 1940 1950 1960 FIGURE 71 HOUSTON: PERCENTAGE OF SERVICB EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 226 TABLE LXX BALTIMORE: SERVICE EMPLOYMENT; 1929-1958 Year Actual Estimate % of pop. 1929 6,030 .76 1931 5,140 • 63 1933 4,250 4,250 .52 1935 6,009 6,010 .72 1937 9,810 1.16 1939 13,606 13,610 1.59 1941 13,650 1.57 1943 13,700 1.55 1945 13,740 1.52 1947 13,790 1.50 1948 13,809 1949 15,110 1.61 1951 17,730 1.87 1953 20,350 2.15 1954 21,661 1955 23,490 2.50 1957 27,160 2.89 1957 28,994 10 NC= 1.5 * .143X 1940 1950 1930 1960 FIGURE 72 BALTIMORE: PERCENTAGE OP SERVICE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 227 TABLE LXXI CLEVELAND: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 7,810 .88 1931 6,660 .74 1933 5,508 5,510 • 62 1935 8,198 8,200 .92 1937 10,610 1.20 1939 13,006 13,010 1.48 1941 13,660 1.55 1943 14,310 1.61 1945 14,970 1.67 1947 15,620 1.73 1948 15,945 1949 17,830 1.96 1951 21,600 2.37 1953 25,380 2.80 1954 27,255 1955 28,150 3.12 1957 29,950 3.33 1958 30,850 10 Nc= 1.73 ♦ .182X 1930 1940 1950 1960 FIGURE 73 CLEVELAND: PERCENTAGE OP SERVICE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 228 TABLE LXXII LOS ANGELES: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 13,470 1.15 1931 11,480 .94 1933 9,494 9,490 .72 1935 19,886 19,890 1.45 1937 28,330 1.99 1939 36,767 36,770 2.49 1941 36,120 2.33 1943 35,470 2.16 1945 34,820 2.00 1947 34,170 1.87 1948 33,848 1949 40,710 2.12 1951 54,450 2.70 1953 68,190 3.21 1954 75,058 1955 81,000 3.64 1957 92,890 4.00 1958 98,839 10 Nc= 2*18 + .187X 5 1930 1940 1950 1960 FIGURE 74 LOS ANGELES: PERCENTAGE OF SERVICE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop TABLE LXXIII NBW YORK: SERVICB EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 110,000 1.62 1931 95,000 1.36 1933 81,568 81,570 1.15 1935 100,310 100,310 1.39 1937 120,140 1.65 1939 139,971 139,970 1.89 1941 145,130 1.94 1943 150,300 1.98 1945 155,470 2.03 1947 160,630 2.07 1948 163,216 1949 180,980 2.31 1951 216,520 2.75 1953 252,060 3.21 1954 269,832 1955 279,590 3.57 1957 299,130 3.83 1958 308,894 10r 2.19 ♦ .164X 1930 1940 1950 1960 FIGURB 75 NEW YORK: PERCENTAGE OP SERVICE EMPLOYMENT AND THE TREND, 1929-1957 dod jo 230 TABLE LXXIV DETROIT: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 10,520 .70 1931 8,960 .57 1933 7,397 7,400 .47 1935 12,263 12,260 .77 1937 17,010 1.06 1939 21,757 21,760 1.34 1941 24,130 1.47 1943 26,500 1.57 1945 28,870 1.66 1947 31,240 1.76 1948 32,429 1949 34,570 1.89 1951 38,860 2.12 1953 43,160 2.40 1954 45,295 1955 46,740 2.66 1957 49,640 2.88 1958 51,089 10 5 Ncs 1.55 ♦ .166X 1930 1940 1950 1960 FIGURE 76 DETROIT: PERCENTAGE OF SERVICE EMPLOYMENT AND THE TREND, 1929-1957 % o f pop 231 TABLE LXXV CHICAGO: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 27,000 • 81 1931 22,600 .67 1933 18,669 18,670 .55 1935 32,528 32,530 .96 1937 47,460 1.40 1939 62,390 62,390 1.84 1941 64,250 1.88 1943 66,110 1.91 1945 67,970 1.94 1947 69,830 1.96 1948 70,760 1949 77,610 2.16 1951 91,310 2.53 1953 105,020 2.92 1954 111,874 1955 115,000 3.21 1957 121,250 3.39 1958 124,383 10 5 Nc= 1.87 ♦ .196X 1960 1930 1940 1950 FIGURB 77 CHICAGO: PERCENTAGE OF SBRVICE EMPLOYMENT AND THE TREND, 1929-1957 i o o f pop 232 TABLE LXXVI PHILADELPHIA: SERVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 12,000 •62 1931 10,000 .51 1933 8,250 8,250 .42 1935 16,820 16,820 .87 1937 21,680 1.12 1939 26,551 26,550 1.37 1941 27,140 1.40 1943 27,730 1.41 1945 28,330 1.42 1947 28,930 1.43 1948 29,233 1949 31,120 1.51 1951 34,910 1.69 1953 38,700 1.89 1954 40,590 1955 43,030 2.11 1957 47,930 2.37 1958 50,376 10 Nc= 1.34 ♦ .121X 1930 1940 1950 1960 FIGURE 78 PHILADELPHIA: PERCENTAGE OP SERVICE EMPLOYMENT AND THB TREND, 1929-1957 % o f pop 233 TABLE LXXVII UNITED STATES: SBRVICE EMPLOYMENT, 1929-1958 Year Actual Estimate % of pop. 1929 860,000 1.27 1931 860,000 1.23 1933 860,000 860,000 1.21 1935 634,232 634,230 .88 1937 1,065,670 1.46 1939 1,497,112 1,497,110 2.02 1941 1,631,000 2.14 1943 1,764,900 2.23 1945 1,898,800 2.32 1947 2,032,730 2.39 1948 2,099,692 1949 2,143,370 2.44 1951 2,230,750 2.43 1953 2,318,130 2.40 1954 2,361,821 19 55 2,493,660 2.46 1957 2,757,340 2.60 1958 2,889,183 10 1.97 ♦ .116X 1930 1940 1950 1960 FIGURE 79 UNITED STATES: PERCENTAGE OF SERVICE EMPLOYMENT AND THE TREND, 1929-1957 APPENDIX E CITY SIZE AND EMPLOYMENT IN MANUFACTURING INDUSTRY, RETAIL, WHOLESALE, AND SERVICE TRADES: MULTIPLE CORRELATION ANALYSIS 235 TABLE LXXVIII MEMPHIS: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION, 1929-1957 independent variable Dependent variable Coefficient of deterraination(r2) Multiple Correlation coeff.(r) Variance of estimate Standard error of estimate(Sy) Intercept(A value) Standard error of intercept(Sa ) Proportion of variance Manufacturing employment(Nm) Retail employment(Nr) Wholesale employment(NW) Service employment(Ns) Employment Population 0.98880 0.99440 184223.87500 429.21309 -13716.02710 1653.61221 0.92098 0.03952 0.02651 0.00179 TABLE LXXIX ATLANTA: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION, 1929-1957 r2 0.98790 r 0.99390 Var. est. 421126.00000 Sy 648.94221 A value -11225.61646 Sy 5793.96185 Prop. var. Nm 0.91995 Nr 0.04166 Nw 0.02574 NS 0.00054 TABLE LXXX COLUMBUS: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION, 1929-1957 r2 0.97640 r 0.98810 Var. est. 346799.62500 Sy 588.89696 A value -16974.68457 sA 3587.88046 Prop. var. Nm 0.95792 Nr 0 .00000 Nw 0.00997 Ns 0.00849 TABLE LXXXI SEATTLE: MULTIPLE CORRELATION ANALYSIS OF EMPLOYMENT AND POPULATION, 1929-1957 r2 0.63100 r 0.79430 Var. est. 269838.00000 Sy 2696.26370 A value -40269.57520 Sa 39194.97656 Prop. var. N« 0.54172 Nr 0.00066 Nw 0.07621 Ns 0.01238 237 TABLE LXXXII DENVER: MULTIPLE CORRELATION ANALYSIS OF EMPLOYMENT AND POPULATION, 1929-1957 r2 0.99220 r 0.99610 Var. est. 161162.00000 Sy 401.44987 A value -24242.30371 sA 2278.91531 Prop, var. Nm 0.92168 Nr 0.05469 N«# 0.01581 NS 0.00002 TABLE LXXXIII CINCINNATI: MULTIPLE CORRELATION ANALYSIS OF EMPLOYMENT AND POPULATION, 1929-1957 r2 0.96760 r 0.98360 Var. est. 996764.00000 Sy 998.38068 A value -19997.52954 sA 32542.41309 Prop. var. Nm 0.82218 Nr 0.08434 Nw 0.02593 NS 0.03511 TABLE LXXXIV MINNEAPOLIS: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION, 1929-1957 *2 r Var* est* Sy A value Sa Prop, var, Nm Nr Nw NS 0*96200 0*98080 147145.00000 1071.04855 46749.68066 36144.94189 0.32006 0.37461 0.10424 0.16309 TABLE LXXXV BUPPALO: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION, 1929-1957 r2 0.98090 r 0.99040 Var* est. 349427.00000 Sy 591.12350 A value 59150.28027 SA 17594.40430 Prop. var. Nn 0.47176 Nr 0.37553 Nw 0.11185 Ns 0.02174 I 239 TABLE LXXXVIII CLEVELAND: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION, 1929-1957 r2 0.99040 r 0.99520 Var. est. 807138.00000 Sy 898.40859 A value 157445.25391 sA 58876.28467 Prop. var. Nm 0.35331 Nr 0.08435 N* 0.11770 Ms 0.43507 TABLE LXXXIX LOS ANGELES: MULTIPLE CORRELATION ANALYSIS OF EMPLOYMENT AND POPULATION, 1929-1957 r2 0.96220 r 0.98090 Var. est. 382336.00000 Sy 5690.54791 A value -287621.99609 Sa 86451.33887 Prop. var. Nm 0.86523 Nr 0.01309 Nw 0.07569 Ns 0.00812 240 TABLE LXXXVI HOUSTON: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION, 1929-1957 r2 0.99030 r 0.99510 Var. est. 489306.00000 Sy 699.50410 A value -14475.46411 sA 3009.66125 Pro. var. Nm 0.89966 Nr 0.03314 N* 0.05665 Ns 0.00084 TABLE LXXXVII BALTIMORE: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION, 1929-1957 r2 0.88800 r 0.94280 Var. est. 774546.00000 Sy 2602.79578 A value -46111.38086 sA 2414.45801 Prop. var. Nm 0.71365 Nr 0.12890 N* 0.00121 Ns 0.04502 TABLE XC NEW YORK: MULTIPLE CORRELATION ANALYSIS OF EMPLOYMENT AND POPULATION, 1929-1957 r Var. est. Sy A value sa Prop. var. Nm Nr Nw N* 0.85770 0.92610 545184.00000 31182.71094 -3858878.68750 18880.68750 0.69553 0.00240 0.04621 0.11359 TABLE SCI DBTROITs MULTIPLE CORRELATION ANALYSIS OF EMPLOYMENT AND POPULATION, 1929-1957 ' r’ 2 ........... ............... 0.98620 r 0.99310 Var. est. 535584.00000 Sy 1880.31487 A value 63822.22852 sA 42083.98047 Prop. var. Nm 0.64888 Nr 0.15889 Nw 0.04771 Ns 0.13069 242 TABLE XCII CHICAGO: MULTIPLE CORRELATION ANALYSIS OF EMPLOYMENT AND POPULATION, 1929-1957 r2 0.95450 r 0.97700 Var, est. 515072.00000 Sy 7906.64734 A value 604456.78125 sA 15878.88281 Prop. var. Nm 0.69760 Nr 0.04327 Nw 0.09266 NS 0.12093 TABLE XCIII PHILADELPHIA: MULTIPLE CORRELATION ANALYSIS OF EMPLOYMENT AND POPULATION* 1929-1957 x2 0.95730 r 0.97840 Var. est. 110876.00000 Sy 2666.62256 A value 157664.61133 6679.50781 Prop. var. Nm 0.50508 Nr 0.00002 Nw 0.06699 Ns 0.38518 243 TABLE XCIV UNITED STATES: MULTIPLE CORRELATION ANALYSIS OP EMPLOYMENT AND POPULATION. 1929-1957 r2 0.96240 r 0.98100 Var. est. 746496.00000 Sy 152417.52734 A value 617316.21875 sA 71511.60937 Prop. var. Nm 0.85595 Nr 0.05578 N* 0.03673 Ns 0.01385 APPENDIX P ANALYSIS OP EMPLOYMENT IN MANUFACTURING INDUSTRY, RETAIL, WHOLESALE, AND SERVICE TRADES COMBINED, AND CITY SIZE 245 TABLE XCV MEMPHIS: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf• Retail Wholesale Service Total 1929 6.5 6.8 3.9 .77 17.97 1931 6.0 5.0 3.2 • 62 14.82 1933 5.7 3.5 2.6 .50 12.30 1935 5.4 5.2 2.7 •80 14.10 1937 6.0 5.6 2.9 1.38 15.88 1939 4.8 6.0 3.1 1.93 15.83 1941 5.8 6.5 3.4 1.93 17.63 1943 6.8 6.8 3.6 1.89 19.09 1945 8.0 7.1 3.8 1.86 20.76 1947 9.4 7.3 4.0 1.82 22.52 1949 9.3 7.2 4.1 1.92 22.52 1951 9.2 7.0 4.1 2.14 22.44 1953 9.2 6.8 4.2 2.36 22.56 1955 9.0 6.6 4.1 2.55 22.25 1957 8.5 6.5 3.8 2.72 21.52 b .310 .140 .050 .147 .647 A 7.31 6.20 3.60 1.55 18.72 f o o f population 246 25 Total 20 Nc= 18.72 ♦ .647X 15 10 Manuf Retail Wholesale Service 1930 1940 1950 1960 FIGURE 80 MEMPHIS: PERCBNT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 247 TABLE XCVI ATLANTA: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 7.1 8.2 4.4 1.29 20.99 1931 6.6 6.4 3.5 1.05 17.55 1933 6.2 4.8 2.7 .85 14.55 1935 6.0 6.8 3.3 1.22 17.32 1937 6.9 7.4 3.7 1.88 19.88 1939 7.0 7.9 4.2 2.51 21.61 1941 8.1 8.7 5.0 2.68 24.48 1943 9.2 9.3 5.8 2.83 27.13 1945 10.3 10.0 6.6 2.97 29.87 1947 11.2 10.6 7.4 3.11 32.31 1949 12.0 10.9 7.8 3.39 34.09 1951 12.4 10.5 7.7 3.67 34.27 1953 12.3 9.8 7.3 3.78 33.18 1955 11.9 9.9 7.0 4.02 32.82 1957 11.1 10.4 6.7 4.31 32.51 b .506 .334 .350 .247 1.437 A 9.20 8.77 5.50 2.63 26.10 % o f population 243 40 Total 35 30 Nc= 26.1 + 1.437X 25 20- 15 Manuf. Retail 10 Wholesale Service 1930 1960 1940 1950 FIGURE 81 ATLANTA: PERCENT OF POPULATION ENPLOYED IN SPECIFIED CATEGORIES, 1929-1957 249 TABLE XCVII COLUMBUS: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 9.3 6.7 2.3 .71 19.01 1931 8.5 5.3 2.0 .59 16.38 1933 7.8 4.1 1.7 .48 14.08 1935 7.1 5.7 1.5 .70 15.00 1937 7.7 6.2 1.7 1.01 16.61 1939 6.7 6.7 1.9 1.31 16.61 1941 8.5 7.2 2.1 1.40 19.20 1943 9.7 7.5 2.3 1.45 20.95 1945 10.7 7.7 2.5 1.50 22.40 1947 11.7 7.9 2.6 1.54 23.74 1949 12.5 8.0 2.7 1.74 24.94 1951 13.3 7.9 2.6 2.10 25.90 1953 13.9 7.7 2.6 2.42 26.62 1955 13.7 7.5 2.6 2.53 26.33 1957 12.6 7.2 2.6 2.46 24.86 b .486 .185 .069 .150 .890 A 10.30 6.90 2.20 1.46 20.88 % o f population 250 1 30 Total 25 Nc* 20.88 ♦ .89X 20 15 Manuf• 10 Retail I960 1940 1950 1930 FIGURE 82 COLUMBUS: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 251 TABLE XCVIII SEATTLE: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATBGORIBS AND THE GROWTH RATES, 1929-1957 Year Manu£ Retail Wholesale Service Total 1929 6.4 7.5 4.0 1.05 18.95 1931 5.7 5.9 3.3 .89 15.79 1933 5.1 4.4 2.6 .73 12.83 1935 4.6 5.8 3.0 1.34 13.74 1937 5.5 6.2 3.3 2.19 17.19 1939 5.5 6.6 3.7 3.03 18.83 1941 7.4 7.0 3.9 2.70 21.00 1943 8.9 7.2 4.1 2.34 22.54 1945 10.2 7.4 4.3 2.01 23.91 1947 11.5 7.6 4.4 1.71 25.11 1949 11.9 7.5 4.5 1.77 25.67 1951 12.3 7.4 4.4 2.15 26.25 1953 12.8 7.3 4.4 2.50 27.00 1955 13.5 7.2 4.4 2.81 27.91 1957 14.7 7.2 4.4 3.06 29.36 b .740 .118 .105 .118 1.081 A 9.00 6.80 3.90 2.02 21.72 f o o f population 252 Total 30 25- Nc= 21.72 ♦ 1.081X 15- Manuf 1C Retail Service 1930 1940 1950 1960 FIGURE 83 SEATTLE: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 253 TABLE XCIX DENVER: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 5.7 7.7 3.6 .98 17.98 1931 5.1 6.1 3.1 .82 15.12 1933 4.5 4.5 2.6 .66 12.26 1935 3.9 5.2 2.4 .94 12.44 1937 4.1 6.0 2.8 1.41 14.31 1939 3.6 6.8 3.1 1.86 15.36 1941 4.9 7.2 3.6 1.87 17.57 1943 6.1 7.4 4.0 1.84 19.34 1945 7.1 7.7 4.4 1.82 21.02 1947 8.0 7.9 4.7 1.81 22.41 1949 7.8 7.8 4.7 1.96 22.26 1951 7.6 7.5 4.3 2.27 21.67 1953 7.5 7.3 4.0 2.56 21.36 1955 7.4 7.3 4.0 2.84 21.54 1957 7.3 7.4 4.2 3.09 21.99 b .275 .127 .121 .154 .677 A 6.04 6.92 3.70 1.78 18.44 % o f population 254 25r Total 20 18.44 + .677X 15- 10 lanuf • etail Wholesale Service 1960 1940 1930 1950 FIGURE 84 DBNVER: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 255 TABLE C CINCINNATI: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 14.3 6.7 3.7 1.03 25.73 1931 13.2 5.6 3.3 .87 22.97 1933 12.1 4.6 2.8 .71 20.21 1935 11.1 5.8 2.9 .97 20.77 1937 13.5 6.1 3.0 1.29 23.89 1939 11.6 6.3 3.2 1.61 22.71 1941 13.9 6.7 3.4 1.70 25.70 1943 16.0 7.0 3.7 1.76 28.46 1945 18.0 7.4 3.9 1.83 31.13 1947 19.9 7.7 4.1 1.89 33.59 1949 19.0 7.7 4.1 2.13 32.93 1951 18.3 7.5 4.1 2.57 32.47 1953 17.8 7.3 4.2 3.04 32.34 1955 17.0 7.3 4.2 3.32 31.82 1957 15.8 7.4 4.2 3.43 30.83 b .456 .156 .095 .188 • 895 A 15.43 6.74 3.70 1.88 27.75 Population 256 35 30 27.75 + .895X 25 20 o 1930 1940 1950 I960 FIGURE 85 257 TABLE Cl MINNEAPOLIS: PERCBNT OF POPULATION EMPLOYED IN SPECIFIBD CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service TOtAl 1929 7.8 7.2 3.8 .88 19.68 1931 7.0 5.9 3.9 .73 17.53 1933 6.3 4.7 4.1 .60 15.70 1935 5.6 6.3 4.4 .83 17.13 1937 6.4 6.5 4.7 1.19 18.79 1939 5.3 6.7 4.9 1.55 18.45 1941 7.1 7.3 4.9 1.59 20.89 1943 8.9 7.8 5.0 1.63 23.33 1945 10.4 8.3 5.0 1.67 25.37 1947 12.1 8.8 5.0 1.70 27.60 1949 12.1 8.8 5.0 1.93 27.83 1951 12.4 8.6 5.0 2.36 28.36 1953 12.8 8.5 5.1 2.83 29.23 1955 12.7 8.4 5.2 3.23 29.53 1957 12.2 8.3 5.3 3.56 29.36 b .566 .225 .096 .192 1.079 A 9.27 7.47 4.80 1.75 23.29 % o f population 253 35 30 Total 25 23.29 + 1.079X 20 15 Manuf 10 etail Wholesale Service 1930 1940 1950 1960 FIGURE 86 MINNEAPOLIS: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 259 TABLE ClI BUFFALO: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 12.1 5.5 2.5 • 68 20.78 1931 10.9 4.4 2.1 • 56 17.96 1933 9.8 3.3 1.8 .45 15.35 1935 8.7 4.6 1.6 .53 15.43 1937 9.9 4.8 1.7 .80 17.20 1939 8.0 5.1 1.8 1.07 15.97 1941 9.8 5.5 2.1 1.13 18.53 1943 11.5 6.0 2.4 1.19 21.09 1945 13.3 6.4 2.6 1.25 23.55 1947 15.1 6.8 2.9 1.31 26.11 1949 15.0 7.1 3.0 1.49 26.59 1951 15.1 7.1 3.1 1.79 27.09 1953 15.3 7.2 3.3 2.11 27.91 1955 14.8 7.2 3.3 2.33 27.63 1957 13.7 7.0 3.3 2.43 26.43 b .430 .243 .118 .139 .930 A 12.20 5.87 2.50 1.27 21.84 % o f population 260 30 r Total 25 21.84 ♦ *93X Manuf 1* 1C' Retail plesale Service 1960 1940 1950 1930 FIGURE 87 BUFFALO: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 TABLE CIII HOUSTON: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 5.9 6.7 2.7 1.29 16.59 1931 5.1 5.2 2.4 1.01 13.71 1933 4.5 4.0 2.2 .78 11.48 1935 4.0 4.5 2.1 1.28 11.88 1937 4.8 5.4 2.6 2.11 14.91 1939 4.2 6.1 2.9 2.87 16.07 1941 5.4 6.6 3.3 2.65 17.95 1943 6.3 6.8 3.5 2.40 19.00 1945 7.0 7.0 3.7 2.18 19.88 1947 7.6 7.1 3.8 2.01 20.51 1949 7.8 7.1 3.9 2.08 20.88 1951 7.8 6.9 3.9 2.32 20.92 1953 7.6 6.6 3.8 2.46 20.46 1955 7.5 6.4 3.8 2.62 20.32 1957 7.5 6.2 3.8 2.79 20.29 b • 263 .085 .134 .109 .591 A 6.20 6.17 3.20 2.06 17.63 % O f population 262 25 20 Total Nc= 17.63 ♦ .59XX 15 10 JJanuf — Retail .Wholesale Service 1930 1940 1950 1960 263 TABLE CIV BALTIMORE: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 10.7 5.3 2.T .76 19.06 1931 10.0 4.5 2.0 • 63 17.13 1933 9.2 3.7 1.8 • 52 15.22 1935 8.5 5.0 1.8 .72 16.02 1937 9.5 5.2 1.9 1.16 17.76 1939 9.0 5.4 2.1 1.59 18.09 1941 10.1 5.9 2.3 1.57 19.87 1943 11.2 6.4 2.4 1.55 21.55 1945 12.2 6.8 2.6 1.52 23.12 1947 13.1 7.2 2.7 1.50 24.50 1949 12.8 7.3 2.8 1.61 24.51 1951 12.7 7.2 2.8 1.89 24.59 1953 12.5 7.1 2.8 2.16 24.56 1955 12.3 7.1 2.8 2.49 24o69 1957 12.0 7.2 2.8 2.87 24.87 b .273 • 234 .077 .143 .727 A 11.09 6.10 2.40 1.50 21.05 % o f population 264 1 30 Total 25 21.05 ♦ .727X 20 15 Manuf 10 Retail Wholesale "“Service 1930 1940 1950 1960 FIGURE 89 BALTIMORE: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 265 TABLE CV CLEVELAND: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 16,5 5.8 2.6 .88 25.78 1931 15.1 4.7 2.3 .74 22.84 1933 14.0 3.8 2.1 •62 20.52 1935 12.8 5.4 2.4 .92 21.52 1937 15.0 5.5 2.5 1.20 24.20 1939 12.7 5.7 2.7 1.48 22.58 1941 15.9 6.2 3.0 1.55 26.65 1943 18.9 6.6 3.3 1.61 30.41 1945 21.8 7.0 3.6 1.67 34.07 1947 24.7 7.4 3.9 1.73 37.73 1949 24.0 7.5 4.1 1.96 37.56 1951 23.4 7.3 4.2 2.37 37.27 1953 22.9 7.1 4.3 2.80 37.10 1955 21.8 7.0 4.4 3.12 36.32 1957 20.3 6.9 4.3 3.33 34.83 b .752 .199 .180 .182 1.313 A 18.65 6.26 3.30 1.73 29.94 % o f population 2 66 Total 35 30] Ncr 29.94 + 1.313X 25 Manuf 20 15 101 Retail Wholesale Service 1930 1940 1950 1960 CLEVELAND: PBRCBNT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 267 TABLE CVI LOS ANGELES; PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 6.5 7.2 3.2 1.15 18.05 1931 5.5 5.6 2.9 .94 14.94 1933 4.8 4.3 2.2 .72 12.02 1935 4.2 5.7 2.5 1.45 13.85 1937 5.4 6.0 2.7 1.99 16.09 1939 4.8 6.3 2.8 2.49 16.39 1941 6.1 6.6 3.0 2.33 18.03 1943 7.3 6.7 3.2 2.16 19.36 1945 8.2 6.8 3.3 2.00 20.30 1947 9.1 7.0 3.5 1.87 21.47 1949 10.2 6.8 3.5 2.12 22.62 1951 11.2 6.4 3.5 2.70 23.80 1953 12.0 6.0 3.4 3.21 24.61 1955 12.3 5.9 3.4 3.64 25.24 1957 12.2 6.2 3.4 4.00 25.80 b .610 .360 .066 .187 .899 A 7.99 6.20 3.10 2.18 19.47 % o f population 268 30 Total 25- Ncb 19,47 ♦ .899X 20 15 Manuf 10- Retail Wholesale "Service 5- ± X i i960 1930 1940 1950 PIGURE 91 LOS ANGELES: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 269 TABLE CVII NEW YORK: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 8.3 5.1 3.3 1.62 18.32 1931 7.6 4.2 2.7 1.36 15.86 1933 7.1 3.3 2.2 1.15 13.75 1935 6.6 4.5 2.8 1.39 15.29 1937 6.9 4.5 2.8 1.65 15.85 1939 6.9 4.5 2.9 1.89 16.19 1941 8.3 4.8 3.2 1.94 18.24 1943 9.6 5.0 3.5 1.98 20.08 1945 10.9 5.2 3.8 2.03 21.93 1947 12.1 5.4 4.1 2.07 23.67 1949 12.0 5.4 4.1 2.31 23.81 1951 12.0 5.3 3.9 2.75 23.95 1953 12.0 5.1 3.7 3.21 24.01 1955 11.9 5.2 3.7 3.57 24.37 1957 11.6 5.3 3.8 3.83 24.53 b .440 •088 .065 .164 .757 A 9.59 4.90 3.40 2.19 15.49 % o f population 270 ! i 30 25 Total 20.08 ♦ .757X 20 15 Manuf 10 Retail Wholesale “Service 1940 1930 1950 1960 FIGURE 92 NEW YORK: PERCENT OF POPULATION EMPLOYED IN SPBCIFIED CATEGORIES, 1929-1957 271 TABLE CVIII DETROIT: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 14.5 4.9 1.6 .70 21.70 1931 13.4 3.8 1.4 .57 19.17 1933 12.8 3.0 1.3 .47 17.57 1935 12.2 4.3 1.4 .77 18.67 1937 14.6 4.6 1.6 1.06 21.86 1939 11.3 4.9 1.7 1.34 19.24 1941 13.5 5.3 1.9 1.47 21.36 1943 15.4 5.6 2.1 1.57 24.67 1945 17.3 5.9 2.3 1.66 27.16 1947 19.0 6.2 2.4 1.76 29.36 1949 18.0 6.2 2.5 1.89 28.59 1951 17.9 6.1 2.5 2.12 28.62 1953 16.9 6.1 2.6 2.40 28.00 1955 15.5 6.0 2.6 2.66 26.76 1957 13.2 5.8 2.7 2.88 24.58 b .272 .151 .108 .166 .697 A 15.30 5.25 2.00 1.55 23.83 % o f population 272 TPtal 25 Nca 23.83 + .697X 20 Manuf 15 Retail Wholesale Service 1930 1940 1950 1960 FIGURE 93 DETROIT: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 273 TABLE CIX CHICAGO: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 12.3 6.1 4.1 • 80 23.30 1931 11.1 4.8 3.0 .67 19.57 1933 10.1 3.6 2.1 .55 16.35 1935 9.2 4.7 2.5 .96 17.36 1937 11.5 5.1 2.6 1.40 20.60 1939 10.2 5.4 2.8 1.84 20.24 1941 12.5 5.8 3.1 1.88 23.28 1943 14.7 6.1 3.4 1.91 26.01 1945 16.7 6.5 3.5 1.94 28.64 1947 18.8 6.8 3.8 1.96 31.36 1949 18.1 6.8 3.8 2.16 30.86 1951 17.7 6.5 3.7 2.53 30.43 1953 17.3 6.3 3.7 2.92 30.22 1955 16.6 6.2 3.7 3.21 29.71 1957 15.5 6.3 3.7 3.39 28.89 b .595 .141 •026 .196 .958 A 14.15 5.80 3.30 1.87 25.12 % o f population 274 ! 35 Total 30 25.12 ♦ .958X 25 20 Manuf 15 10 Retail Wholesale ""Service 1930 1940 1960 1950 FIGURE 94 CHICAGO; PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 275 TABLE CX PHILADELPHIA: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 12.7 5.7 2.6 .62 21.62 1931 11.9 4.6 2.2 .51 19.21 1933 11.1 3.6 1.7 • 42 16.82 1935 10.3 4.6 1.9 .87 17.67 1937 11.0 4.7 2.1 1.12 18.92 1939 10.2 4.7 2.2 1.37 18.47 1941 11.8 5.1 2.4 1.40 20.70 1943 13.3 5.5 2.7 1.41 22.91 1945 14.8 5.9 2.9 1.42 25.02 1947 16.2 6.2 3.1 1.43 26.73 1949 15.7 6.2 3.2 1.51 26.61 1951 15.4 6.0 3.2 1.69 26.29 1953 15.2 5.7 3.2 1.89 25.99 1955 14.9 5.6 3.2 2.11 25.81 1957 14.5 5.6 3.2 2.37 25.67 b .360 .106 .102 • 121 • 689 A 13.26 5.30 2.70 1.34 22.60 % o f population 276 30 Total 25 Nc= 22.6 ♦ .689X 20 Manuf 15 10 Retail Wholesale Service 1930 1940 1950 1960 FIGURE 95 PHILADELPHIA: PERCENT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 277 TABLE CXI UNITBD STATES: PERCENT OP POPULATION EMPLOYED IN SPECIFIED CATEGORIES AND THE GROWTH RATES, 1929-1957 Year Manuf. Retail Wholesale Service Total 1929 14.3 6.3 2.2 1.27 24.07 1931 11.6 5.5 1.9 1.23 20.23 1933 9.3 4.9 1.5 1.21 16.91 1935 11.5 5.4 1.8 .88 19.58 1937 13.4 5.8 1.9 1.46 22.56 1939 12.8 6.2 2.1 2.02 23.12 1941 14.1 6.8 2.3 2.14 25.34 1943 15.1 7.2 2.5 2.23 27.03 1945 16.0 7.6 2.6 2.32 28.52 1947 16.8 8.0 2.8 2.39 29.99 1949 15.4 8.1 2.8 2.44 28.74 1951 16.7 7.7 2.8 2.43 29.63 1953 17.3 7.4 2.7 2.40 29.80 1955 15.4 7.2 2.6 2.46 27.66 1957 14.9 7.3 2.6 2.60 27.40 b .370 .179 .076 .098 .735 A 14.30 6.76 2.30 2.02 25.33 % o f population 278 30 Total 25 Nc= 25.33 + .735X 20 Manuf 15 10 • — Retail 1930 1940 1950 1960 FIGURE 96 UNITBD STATES: PERCBNT OF POPULATION EMPLOYED IN SPECIFIED CATEGORIES, 1929-1957 APPENDIX 6 INCOMB AND CITY SIZE Indexes 280 1 TABLB CXII ! MEMPHIS: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935sl00) Year Pay. index(X) Pop. j2 index(Y) Y2 XY 1939 5.5 7 30*3 36 33.0 1947-48 35.0 35 1225.0 1225 1225.0 1954 53.3 59 2841.0 3881 3144.7 1958 76.0 75 5776.0 5625 5700.0 Totals 175.7 175 9872.3 10367 10102.7 X ■ 42.45 Y • 43.75 E X 2 a sX2 - XcX ■ 2664 x:y2 s e Y2 - 7 e y ■ 2711 z:xy ssXY - XcY a 2674 2 Coefficient of determination r2 ■ = *99 jpx* cy Coefficient of correlation r » .99* Regression coefficient b a — s 1.003 Intercept A a Y - bX ■ -.13____________________ 80 *Pay Top 70 60 40 30 20 10 1935 1940 1945 FIGURE 97 1950 1955 1960 MEMPHIS: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes 281 TABLE CXI 11 ATLANTA: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935*100) Year PaY* index (X) Pop. v2 index(Y) * Y2 XY 1939 5,1 4 26.01 16 20.4 1947-48 21.5 13 462.25 169 279.5 1954 33.2 36 1102.24 1296 1195.2 1958 40.2 57 1616.04 3249 2291.4 Totals 100.0 110 3206.54 4730 3786.5 7 ■ 25 Y ■ 27.5 z: x2 s 706.54 c y 2 ■ 1705 E x y : 1036.5 r2 * .89 b * 1.467 r = .94 A s -9.2 60 /Pop 50 40 Pay 30 20- 10- 1935 1940 1945 1950 1955 1960 FIGURE 98 ATLANTA: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes 282 TABLE CXIV COLUMBUS: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935*100) Year PaT* index(X) Pop. y2 index(Y) Y2 XY 1939 3.7 1947-48 19.0 1954 38.0 1958 41.0 2 13.69 20 361.00 38 1444.00 50 1681.00 4 400 1444 2500 7.4 380.0 1444.0 2050 .0 Totals 101.7 110 3499.69 4348 3881.4 X - 25.4 Y * 27.5 E x2 a 898 E y2 * 1323 Exy ■ 1076 r2 » .97 b s 1.198 r s .98 A s -3.1 60 50 ' Pop 40 30 20 10 1935 1940 1945 1950 1955 1960 FIGURE 99 COLUMBUS: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes TABLE CXV I ! SEATTLE: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935=100) Year Pa*‘ Year index(X) Pop. 2 index(Y) * Y2 XY 1939 5 1947-48 21 1054 34 1958 47 1 25 21 441 37 1156 47 2209 1 441 1369 2209 5 441 1258 2209 Totals 107 106 3831 4020 3913 X - 26.8 Y s 26.5 E x2 a 954.4 3C y2 S 1211 z: xy i 1072.2 r2 = .994 b s 1.086 r s .99 A = -2.1 40 ay. 20 10 1935 1940 1945 1950 1955 1960 FIGURE 100 SEATTLE: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes 284 TABLE CXVI i DENVER: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935-100) Year Pay. index(X) Pop. y2 index(Y) A Y2 XY 1939 6 1947-48 31 1954 42 1958 51 5 36 29 961 47 1764 57 2601 25 841 2209 3249 30 899 1974 2907 Totals 130 138 5362 6324 5810 T L m 32.5 Y = 34.5 E x2 m 1072 z : y2 « 1494 n xy S 1256 00 O' • II 03 U b > 1.171 r s .99 A = -3.5 50 ay 40 30 20 10 1935 1940 1945 1950 1955 1960 FIGURE 101 DENVER: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes 285 TABLE CXVII HOUSTON: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935=100) Year index (X) Pop. index(Y) X2 Y2 XY 1939 14 1947-48 60 1954 105 1958 135 11 60 116 157 196 3600 11025 18225 121 3600 13456 24649 154 3600 12180 21195 Totals 314 344 33046 41826 37129 X - 78.5 Y b 86 T Z x2 e 8397 z: y2 = 12242 E x y a 10125 r2 = .997 b « 1.171 r b .99 A s -8• 6 160 /• Pop 140 ay 120 100 80 60 40 20 1935 1940 1945 1950 1955 1960 FIGURE 102 HOUSTON: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes 286 TABLE CXVIII LOS ANGELES: STATISTICAL ANALYSIS OP -PAYROLL AND POPULATION INDEXES, 1935-1958 (1935.100) Year index(X) Pop. 2 index(Y) x Y2 XY 1939 7.4 1947-48 31.0 1954 60.0 1958 76.0 8 54.8 35 961.0 58 3600.0 73 5776.0 64 1225 3364 5329 59.2 1085.0 3480.0 5584.0 Totals 174.4 174 10391.8 9982 10172.2 X = 43.6 Y ■ 43.5 Z: x2 r 2736 n y 2 = 2326 E*y * 2516 r2 = .99 b = .919 r = .99 A = 3.5 80 Pay 70 'Pop 40 30 20 10 1935 1940 1945 1950 1955 1960 FIGURE 103 LOS ANGELES: PAYROLL AND POPULATION INDEXES. 1935-1958 Indexes 237 TABLE CXIX CINCINNATI: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935«100) Year Pay. index(X) Pop. index(Y) X2 y2 XY 1939 1.7 1 2.9 1 1.7 1947-48 8.0 8 64.0 64 64.0 1954 11.0 11 121.0 121 121.0 1958 11.0 11 121.0 121 121.0 Totals 31.7 31 308.9 307 307 .7 3 s 7.93 Y s 7.75 E x2 ■ 58 z: y 2 s b 66.7 z;xy s 61.9 r2 . .989 b = 1.067 r s .99 A = -.71 15 10 Pay 1935 1940 1945 1950 1955 1960 FIGURE 104 CINCINNATI: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes 288 TABLE CXX MINNEAPOLIS: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 <1935h100) Year Pay* index(X) Pop. Y2 index(Y) x y2 XY 1939 1.0 2 1.0 4 2.0 1947-48 4.6 8 21.2 64 36.8 1954 6.5 6 42.3 36 39.0 1958 6.7 3 44.9 9 20.1 Totals 18.8 19 109.4 113 97.9 J ± 4.7 Y * 4.75 7 Z x2 r 21 2 s 22.75 T Z xy * 10•4 r2 = .226 b = .495 00 • ii u A r 2.4 10 Pay Pop 1935 1945 1940 1950 1955 1960 FIGURE 105 MINNEAPOLIS: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes TABLE CXXI NEW YORK: STATISTICAL ANALYSIS OP PAYROLL AND POPULATION INDEXES, 1935-1958 (1935sl00) Year Pay. index(X) Pop. index(Y) X2 Y2 XY 1939 1.9 3 3.6 6 5.7 1947-48 7.9 8 62.4 64 63.2 1954 9.0 9 81.0 81 81.0 1958 9.8 8 96.0 64 78.4 Totals 28.6 28 243.0 218 228.1 X = 7.15 Y ■ 7 H x2 r 38.5 23 y2 r 22 Exy * 27.9 r2 s .926 b = .724 r = .96 A s 1.8 -.Pay Pop. 10r 1945 1955 1935 1950 1940 1960 FIGURB 106 NEW YORK: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes 290 TABLE CXXII DETROIT: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935sl00) Year Pay. Year index(X) Pop. v2 index(Y) A Y2 XY 1939 1.7 1947-48 9.0 1954 10.8 1958 8.0 1 2.9 12 81.0 11 116.6 7 64.0 1 144 121 49 1.7 108.0 118.8 56.0 Totals 29.5 31 264.5 315 284.5 X s 7.38 Y s 7.75 23 x2 « 46.8 E y2 s 75.75 Exy s 55.72 r2 = .875 b = 1.19 r s .94 A s -1.03 20 15 10 1935 1940 1945 1950 1955 1960 FIGURE 107 DETROIT: PAYROLL AND POPULATION INDEXES, 1935-1958 Indexes 291 TABLE CXXIII CHICAGO: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935*100) Year Pay. index(X) P°P. y2 index(Y) A Y2 XY 1939 1.0 1 1.0 1 1 1947-48 5.0 5 25.0 25 25 1954 6.0 6 36.0 36 36 1958 5.8 5 33.6 25 29 Totals 17.8 17 95.6 87 91 5 . 4 .45 Y - 4.25 z: x2 * 16.4 z: y2 ■ 14.75 n xy * 15.5 r2 * .977 b = .939 r = .99 <n o • i i < Pay Pop 1^60 1935 1940 1945 1950 1955 FIGURE 108 CHICAGO: PAYROLL AND POPULATION INDEXES, 1935-1958 TABLB CXXIV PHILADELPHIA: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935sl00) Year Pay. index(X) Pop. index(Y) X2 Y2 XY 1939 0.7 1 4.9 1 0.7 1947-48 4.4 5 19.4 25 22.0 1954 5.4 5 29.2 25 27.0 1958 5.6 4 31.4 16 22.4 Totals 16,1 15 84.9 67 72.1 a * .03 Y s 3.75 e; x2 s 20 z: y2 = 14.7 el xy s 11.6 r2 * .457 b a .58 r s •67 A = 1.4 6 5 4 3 2 1 •Pay Pop 1935 1940 1945 1950 1955 1960 FIGURE 109 PHILADELPHIA: PAYROLL AND POPULATION INDEXES* 1935-1958 Indexes 293 TABLE CXXV UNITED STATES: STATISTICAL ANALYSIS OF PAYROLL AND POPULATION INDEXES, 1935-1958 (1935-100) Year . index(X) Pop. y2 index(Y) A y2 XY 1939 7 1947-48 25 1954 37 1958 42 3 49 19 625 37 1369 51 1764 9 361 1369 2601 21 475 1369 2142 Totals 111 110 3807 4340 4007 3 s 27.75 Y s 27.5 E X 2 s 726.75 E y2 s 1315 E x y s 954.5 r2 s .962 b = 1.313 00 O' . i i A s -8.9 60 50 40 30 20 10 1935 1940 1945 1950 1955 1960 FIGURE 110 UNITED STATES: PAYROLL AND POPULATION INDEXES, 1935-1958

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Creator Park, David Junewhan (author)

Core Title Employment Distribution, Income, And City Size: A Statistical Analysis

Degree Doctor of Philosophy

Degree Program Economics

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

Tag Economics, Finance,OAI-PMH Harvest

Language English

Contributor Digitized by ProQuest (provenance)

Advisor Grey, Arthur Leslie, Jr (committee chair), Elliott, John E. (committee member), Van Arsdol, Maurice D., Jr. (committee member)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c18-282608

Unique identifier UC11358930

Identifier 6304238.pdf (filename),usctheses-c18-282608 (legacy record id)

Legacy Identifier 6304238.pdf

Dmrecord 282608

Document Type Dissertation

Rights Park, David Junewhan

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