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The changing geographies of concentrated poverty and concentrated affluence in the United States, 1990-2000

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The changing geographies of concentrated poverty and concentrated affluence in the United States, 1990-2000

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Content THE CHANGING GEOGRAPHIES OF CONCENTRATED POVERTY AND CONCENTRATED AFFLUENCE IN THE UNITED STATES, 1990-2000 by Nathan J. Sessoms A Dissertation Presented to the FACULTY OF THE USC CRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (GEOGRAPHY) May 2010 Copyright 2010 Nathan J. Sessoms Dedication This dissertation is, first and foremost, dedicated to my parents, my father, the late Arnold J. Sessoms, and my mother, Jonette J. Sessoms. It is only because of their love, sacrifice, dedication, encouragement, and teaching that I was in the position to both undertake and complete this endeavor. Indeed, they have truly blessed me. As educators, they made certain that I had every opportunity to succeed academically. Anything good that ever happens in my life is due to their everlasting and indelible influence. Therefore, while this work bears my name, all of the credit for its completion belongs to them. My father is the greatest man that I will ever know. He was the ultimate teacher, professional, and provider. In good health and in bad, he was a steadfast husband to his wife and an outstanding role model to his son. I will never be able to articulate the intense pain associated with his death and absence from my life. However, my desire to see him and speak with him again has grown daily since I was fourteen years old. In all that I do, I wish to make him proud by living up to the example that he set. My mother is the strongest individual that I will ever know. In the toughest of times, she picked-up the pieces, held our family together, and made sure that I was taken care of - all while demonstrating beauty, class, and dignity. She is the ultimate cheerleader, and has been there for me throughout as Mom and as Dad. Her sacrifice and generosity have known no bounds. I hope that one day, I will be able to bless her as she has blessed me. I also dedicate this work to two of my brothers, who lost their lives during my journey, but were influential during various points of my life: Albert Forney and Terry ii Sloan. Both of these men left this world far too soon. I would also like to acknowledge Jim McDermott and Travon Shotlow. These individuals are sorely missed. However, their memory lives on in the minds of their family members and those who knew them well. iii Acknowledgements This work represents the end of a lengthy journey during which I have been positively influenced by many wonderful individuals. Long before arriving at USC, I was encouraged by Marc Francioli, one of my high school English teachers, who inspired me by constantly reminding me that I was talented and had options. Through, his innovative teaching methods, my writing skills were enhanced and I began to believe that academic success through writing was, in fact, achievable. Special thanks to Fr. Arthur Bacher for spiritual guidance and support. The foundation for my professional success was constructed by the staff of INROADS Northeast Ohio, Inc. It was there, under the tutelage of my close friend, mentor, and advisor, Jacquelyne E. Bailey, that I was granted exposure to a lengthy list of corporate and community leaders, who would change my life. My daily interactions with these individuals helped me to believe that I could, one day, be a leader and positively impact the lives of others, just as mine had been positively impacted. Special thanks to Zac Harris, George Golden, and Greg Thomas for their insight and guidance as well. In the Spring of 1990, during my freshman year at Ohio University, I was introduced to a group of men that, like me, were simply interested in making a difference. They were diverse in their interests, yet committed to the common ideals of leadership, scholarship, and community service. Through my interaction with them, I learned to not only accept life’s challenges, but to approach them with a sense of optimism and confidence. iv To the Romantic Warriors of the Epsilon Lambda Chapter of Kappa Alpha Psi, Incorporated, I thank you for providing me with the discipline and intestinal fortitude to begin and complete this work. I am honored to follow in the footsteps of chapter scholars, Drs. Rex Crawley, Ricardo D. Hall, and Eric S. Miller. To my Spec, Ric, my Dean, Eric, my main-man E.O., my Spec. Fred, my KLUB Ed, and Joe – this work is a direct result of your mentoring and teaching. Thank you for investing in me. To my fellow Knights, Ryan, Tony, Damon, and Donnie, I thank you for your support over the years. Your Love has been stronger than the 2,400 miles that separates us geographically. To Jeff, thank you for being the older brother that I never had and for always being there. We’ve shared each other’s struggles, we’ll share each other’s successes too. The Human Resources staff at KeyBank in Cleveland, Ohio during the early to mid-1990s provided me with an opportunity to learn various aspects of the banking industry and, in many ways, shape my dreams, while gaining valuable professional experience. In particular, Theron Sumpter and Barb Folger hired me and played a significant role in not only coordinating my varied internship experiences, but providing me with my first full-time employment opportunity. Also, the late Janet Bullard and Jerome McClain of KeyBank spent a great deal of their valuable time developing and encouraging me, while educating me about the unwritten rules of corporate America. As executives, they had no responsibility to do this, but selflessly invested in me. These individuals had a tremendous impact on the construction of my professional dreams and aspirations. The INROADS, Northeast Ohio - KeyBank Partnership was, in every way, my professional foundation. v My career as an urban planner began in MidTown in Cleveland, Ohio. There, I was shaped and molded by the legendary Judge Jean Murrell Capers, as well as stakeholders Rob Laskey, Board Chairman Robert Munson, and Central Middle School teacher Mary Pultz. These individuals taught me a great deal about relationship-building and allowed me to make a difference in my hometown. I am eternally grateful for their contributions to my professional development. Additionally, I benefitted from the mentoring of Professor Norman Krumholz of the Levin College of Urban Affairs at Cleveland State University. His concept of Equity Planning is at the heart of my scholarly pursuits and community work. I thank him for believing in me, as well as his many contributions to my own ideas regarding the provision of options to those who have few. The faculty in the Department of Geography and Planning at the University of Toledo provided support early in my graduate career in the form of mentoring, training, encouragement. I would like to thank Dr. Samuel Attoh, Dr. David “Jim” Nemeth, and Drs. Tim Bailey and Catherine Hooey for their time and commitment to my development as a social scientist, as well as my research agenda. My transition to Los Angeles was made easier by Tom Leahy, who was one of the first people that I met upon my arrival. He worked tirelessly to make my transition a smooth one and remains a close friend. Of course, had it not been for the Sustainable Communities Leadership Program, I may never have met him. Through this particular program, within three months of arriving in Los Angeles, I had traveled to Sacramento, San Francisco (twice), San Diego, Tijuana, Mexico, and developed a brand new network vi of colleagues with similar interests as mine! Special thanks to Odin Zackman, Peter Kim, Susan Klein, and the entire SCLP Family and Environmental Careers Organization. Similarly, my USC experience would not have been nearly as enjoyable had it not been for the faculty and staff of the Department of Geography. In particular, I wish to thank my advisor, Dr. Jennifer Wolch, for her vision, direction, insight, advice, and patience. Her keen eye and attention to detail have taught me a great deal about responsible scholarship. Additionally, Michael Dear provided me outstanding academic and personal support during difficult times. Curt Roseman, Rod McKenzie, Carolyn Cartier, and David Pepper all provided insight and encouragement, as well as meaningful learning opportunities. Extra special thanks to Billie Shotlow, the very first person that I met in the department, for always looking out for and encouraging me, and remaining loyal until the end. Maria Muratalla was always very pleasant and supportive as well. My Irvine Foundation mentor and dissertation committee member, Laura Pulido, was influential in my personal, professional, and academic development. Her attention to my writing and scholarly voice as well as my views on issues of race and the construction of my research agenda have meant everything. I love her like a sister. Additionally, she and her partner Mike Murishige regularly made me feel like I was a part of their family and were there for me in immeasurable ways during some difficult personal struggles. For that, I am eternally grateful to them, as well as Amani and Leela. Similarly, the addition of Ruthie Gilmore to the Department of Geography and PASE faculties had a tremendous impact on me. The presence of an African American vii scholar served as a constant reminder that I could, in fact, complete the journey. Her infectious attitude and take no prisoners mentality inspired me to achieve. I thank Dr. George Sanchez for his dedication and passion for developing under- represented minority scholars and providing a safe space in which to both grow and air our concerns. His development of the Center for American Studies & Ethnicity (now the Program in American Studies & Ethnicity) brought students and faculty of diverse racial and ethnic backgrounds together. This was extremely beneficial, particularly during the early years of my journey. Thank you to my mentors at Heritage Hall, David “Pops” Scott and Russ Romano, as well as their staffs, for making me an official member of the Trojan Family. Their constant encouragement and genuine interest in my well-being as a person (first) and scholar (second) on what seemed like my worst days were extremely important. I thank them for always seeing me as being better than I saw myself a great deal of the time. I would also like to thank my colleagues, who were kind enough to include me in their daily meetings in the Physical Education Building and allowed me to relieve tremendous amounts of stress during Noonball. These included Troy Lord, Darryl Mayo, James Kelley, Guy Hunter, and Gary Painter. Also important were the staff members at the USC Health Center, who refrained from laughing at me as I sustained various injuries while continuing my fledgling pick-up basketball career and contracted other ailments. I appreciate their encouragement and am grateful that they saw me as more than a patient. They treated me as if I was a member of their own family! viii Dr. Richard Andalon served as a trusted mentor and provided invaluable support and insight, as well as the opportunity to continue my work with the USC McNair Scholars Program. This allowed me to contribute to the development of younger minority scholars and share information that I was gathering as I matriculated through my program. While this, for me, was therapeutic in many ways, I hope that it enables other young scholars of color to rise above their own circumstances, fears, etc. and chase their dreams - whatever they may be. I thank him for his time and generosity. There were, of course, many days when the sheer desire to obtain a doctoral degree just wasn’t enough to combat the intense criticism that often accompanied my status as a student. It was during those times that I leaned on an empathetic group of colleagues for knowledge, understanding, support, and the opportunity to vent! I would like to offer my most sincere thanks and appreciation to Rigoberto Rodriguez, Lorena Munoz, Shiela Akinleye, Dean Campbell, Jake Peters, Andrew Burridge, Jacqueline Holzer, and Paz Oliverez. A very special thank you to Melissa Contreras-McGavin and Brad McGavin for their support and encouragement. Their fight, as well as their successes, have been inspirational. I would also be remised if I didn’t thank my colleague Jason Byrne, who taught me how to survive inside the interesting world that is USC Geography. Thanks so much for everything, Roomie! My colleague Mona Seymour trusted me and was willing to learn from all of the mistakes that I made prior to her arrival! Her outstanding work ethic inspired me and seperates her from other scholars. Patricia Literte is one of the brightest minds that I’ve ever encountered and, more importantly, one of the greatest people I’ve ever met. I admire her for her courage and ix strength, but also for her compassion and willingness to give unconditionally. Her friendship and support have meant more than she will ever know. I look forward to collaborating on many research projects with her in the future! In closing, I would also like to acknowledge those organizations that supported me throughout this journey, including the Urban Land Institute of Los Angeles, Dunbar Economic Development Corporation, Abode Communities, and the Brotherhood Crusade. These organizations allowed me to further develop and enhance my organizational and program management skills while providing real world experience. To Charisse Bremond-Weaver, thank you for taking a chance on me when others wouldn’t. I sincerely appreciate your confidence in me and my ability. Thanks also for providing multiple opportunities for growth and development. On a daily basis, you reaffirm for me the importance of the word legacy. Ultimately, I am grateful to you for the opportunity to help others help themselves. Dr. Sharon Rabb helped me to rebuild my psyche from a personal perspective, as well as a academic one. Thank you for taking an interest in me, for assisting in the healing process, and for challenging me to be a better person in every aspect of my life. Thanks, also, to my good friends at the City of Pico Rivera. Jim Basham was supportive of my development, invested in me, and provided personal and professional guidance. Nancy Cabada believed in me from the beginning. She was loyal and remained so throughout. Finally, I would like to thank those individuals that I met toward the very end of my journey, who were extremely supportive of this work and cared enough to inquire x about my personal well-being as well as my progress on a regular basis. Sandra Bernabe regularly reminded me that there is no place for pride amongst friends. Laurie Dickey understood the significance of the journey. Enku Gelaye appreciated the fight, as well as its source. All regularly offered kind words during particularly difficult and draining moments. They have no idea how much their support meant. I am truly grateful. Wendy Ascencio is a blessing that was unforeseen, but is greatly respected and appreciated. Thank you for trusting in me, for bringing your talents to the table, and for using them without reservation. Your honesty and encouragement have meant a great deal. In closing, as a scholar of color, it has and always will be of the utmost importance that I remain engaged in the community. That is where my journey started and where I hope to cross paths with and positively influence young people of various backgrounds who are struggling to find themselves as I once was. Chapter 3 was published as “Measuring Concentrated Poverty in a Global Metropolis: Lessons from Los Angeles,” in The Professional Geographer 60(1):70-86. xi Table of Contents Dedication ii Acknowledgements iv List of Tables xv List of Figures xvi Abstract xvii Dissertation Overview 1 Research Questions 4 Data and Methods 5 Overview of Dissertation 12 Introductory Conclusions and Policy Implications 14 Chapter One: Contemplating Concentration: Geography and the New Concentrated Poverty 17 The Reprise of Concentrated Poverty 17 Conceptualizing Concentrated Poverty – Past and Present 19 Changing Geographies of Poverty Concentration in the U.S. 26 Measuring and Assessing Concentrated Urban Poverty 31 Alternative Measures of Concentrated Urban Poverty 36 From Poverty Concentration to Economic Polarization 39 Conclusions and Suggestions for the Study of the New Concentrated Poverty 41 Poverty Concentration and Globalization 41 Spatial Measures of Poverty Concentration 42 Concentrated Poverty and Metropolitan Form 43 Concentrated Affluence 44 Chapter Two: From Urban Segregation to Economic Polarization: Trends in the Spatial Distribution of Poverty and Affluence Concentration in the United States 47 Chapter Two Introduction 47 The Changing Landscape of Poverty Concentration 50 xii Conceptualizing Affluence Concentration 53 Data and Methodology 62 Exploring Regional Trends in Poverty and Affluence Concentration in the U.S., 1990-2000 74 Northeast/Midwest 77 Southeast 78 Southwest/West 79 Northwest 80 Characterizing Regional Trends in Poverty and Affluence Concentration in the U.S., 1990-2000 80 Understanding Poverty Concentration and Suburban Poverty Concentration in the U.S., 1990-2000 84 Poverty Concentration, 1990-2000 84 Suburban Poverty Concentration, 1990-2000 96 Chapter Two Conclusion 105 Chapter Three: The Changing Face of Concentrated Poverty 108 The Changing Landscape of Concentrated Poverty 108 The Origins and Usage of the 40 Percent Threshold 110 Empirical Focus and Methodological Approach 114 The Differentiation of Concentrated Poverty Neighborhoods in Los Angeles 123 Baldwin Park 126 Cudahy 127 Long Beach 128 Monterey Park 129 Chapter Three Conclusion and Suggestions for Future Research 135 Chapter Four: How the Other Half Lives: An Analysis of Concentrated Affluence Neighborhoods in Los Angeles County 140 Rethinking Affluence, Rethinking Concentration 140 Understanding Affluence, Concentration, and Defensiveness 143 Empirical Context and Methodological Approach 152 The Differentiation of Concentrated Affluence Neighborhoods in Los Angeles 166 La Canada Flintridge 167 Diamond Bar 174 xiii Manhattan Beach 177 Santa Clarita 181 Chapter Four Conclusions and Suggestions for Future Research 187 Affluent Landscapes, Residential Behavior, Defensiveness 194 and the Differentiation of Wealth in Upscale Neighborhoods 195 Conclusion 197 Measuring Poverty and Affluence Concentration 200 Taking Affluence Concentration Seriously 203 Policy Implications 206 Bibliography 210 xiv List of Tables Table 2.1a: Two Stage Least Squares Regression Analysis - Variables and 71 Descriptions Table 2.1b: Two Stage Least Squares Regression Analysis - Instrumental Variables and Descriptions (Affluence Cleansing) 72 Table 2.2: Poverty and Affluence Concentration Rates and Rate Changes for the 50 Largest U.S. Metropolitan Statistical Areas, 1990 and 2000 76 Table 2.3a: Final Regression Results - Concentrated Poverty, 1990 89 Table 2.3b: Final Regression Results - Concentrated Poverty, 2000 90 Table 2.4a: Final Regression Results - Suburban Concentrated Poverty, 1990 98 Table 2.4b: Final Regression Results - Suburban Concentrated Poverty, 2000 99 Table 3.1: Comparison of Selected Tracts Using Alternative Definitions of 150% and 100% of Poverty 118 Table 3.2: Definition of Underclass Behaviors (Ricketts and Sawhill 1988) 120 Table 3.3: Demographic Profile for Selected Concentrated Poverty Tracts 121 Table 3.4: Socioeconomic Profile for Selected Concentrated Poverty Tracts 121 Table 3.5: Housing Profile for Selected Concentrated Poverty Tracts 122 Table 3.6: U.S. Tract Analysis of Concentrated Poverty Characteristics 124 Table 4.1: Audit Instrument for Selected Concentrated Affluence Neighborhoods 161 Table 4.2: Demographic Profile for Selected Concentrated Affluence Tracts 163 Table 4.3: Socioeconomic Profile for Selected Concentrated Affluence Tracts 164 Table 4.4: Housing Profile for Selected Concentrated Affluence Tracts 165 Table 4.5: U.S. Tract Analysis of Concentrated Affluence Characteristics 167 xv List of Figures Figure 2.1: MSA Concentrated Poverty Matrix, 1990-2000 67 Figure 2.2: MSA Concentrated Affluence Matrix, 1990-2000 68 Figure 2.3: MSA Economic Polarization Matrix, 1990-2000 69 Figure 3.1: Concentrated Poverty Quadrant Analysis – Inner Suburban Municipalities, 1990-2000 118 Figure 3.2: Percent Concentrated Poverty within Selected Municipalities 131 Figure 3.3: Percent Foreign-Born Population within Selected Municipalities 132 Figure 3.4: Percent Unemployment within Selected Municipalities 134 Figure 3.5: Percent Race/Poverty within Selected Municipalities 135 Figure 4.1: Concentrated Affluence Quadrant Analysis - Los Angeles County, 1990-2000 157 xvi Abstract Employing a mixed methodology, this dissertation investigates emerging trends in the spatial distribution of concentrated poverty and concentrated affluence at the nation- state, regional, and local levels of scale during the 1990s. Drawing from quantitative exploration of census data, including comparative analyses of spatial indices of segregation and multivariate regression analyses, it examines trends in poverty and affluence concentration through a comparative analysis of fifty of the nation’s largest metropolitan areas, assesses the extent to which the concentration of poverty within suburban zones explains – and is explained by – concentration of affluence patterns, and questions the heterogeneity of concentrated poverty and affluence landscapes through an in-depth study of the Los Angeles metro-area. In addition, qualitative techniques, including structured observations, and photography are be utilized to further understand, illustrate, and articulate the material and lived social realities of landscapes of poverty and affluence concentration. Long regarded as an ‘urban’ phenomenon and intimately linked to research focused on the ‘Black Urban Underclass’, the face and landscape of concentrated poverty has undergone dramatic changes. In stark contrast to its dramatic increase within urban areas during the 1970s and 1980s, recent research has highlighted its substantial decrease within the Midwest and Southern regions of the United States, while increasing within inner-suburban areas and, in particular, the West during the 1990s. Such findings portray concentrated poverty as a phenomenon that carries implications for not only urban areas, but entire regions as well. Moreover, they suggest that poor areas are becoming xvii increasingly differentiated. Therefore, previous assumptions regarding their physical make-up and demographic composition may be in need of revision. Finally, they raise questions as to whether conventional methods of measurement may be unable to adequately depict the increasingly complex landscape of poverty, particularly in globalizing cities such as Los Angeles, Chicago, and New York. Meanwhile, in light of its predominant focus on the poor, their spatial distribution, and perceived behavioral tendencies, urban geographic scholarship has rarely discussed the notion of affluence concentration. Therefore, little is known about this particular stratum. However, in light of new developments in the spatial distribution of concentrated poverty, numerous questions regarding their spatial distribution, their social characteristics, as well as those of their physical landscapes, and their behavioral responses to the suburbanization of concentrated poverty remain which warrant further consideration. Finally, how might these responses impact poverty policy? These and related questions, although foundational, remain critical to the development of a greater understanding of emerging conditions of economic polarization. xviii 1 Dissertation Overview  Conducted in the Rustbelt/Snowbelt areas of the Midwest and Northeast, early work on poverty concentration was multi-faceted and revolved around relationships between race and class. In particular, this research tended to confirm a dramatic increase in concentrated poverty during the 1970s and 1980s, a simultaneous increase in the number of poor people residing in poor neighborhoods, and that these conditions occurred primarily within African American neighborhoods. However, poverty scholars expressed diverging ideas regarding the central catalysts involved, including deindustrialization and the attendant loss of manufacturing jobs, a history of racism in residential housing markets, and metropolitan inequalities associated with general economic change (Wilson 1987; Massey and Denton 1993; Jargowsky 1997). Such causes of poverty concentration were not mutually exclusive, however. Rather, the lack of local employment opportunities, combined with an exodus of upwardly mobile African Americans to suburban communities as racial restrictions in residential housing markets eased, led to deepening intrametropolitan disparities, economic and social disinvestment in central cities, and blight, decay and concentrated poverty in many older urban neighborhoods. Moreover, the strategic location of public housing within such areas worked to reinforce the concentration of low-income African- Americans there. During the 1990s, however, several factors combined to combat the effects of institutional racism as well as levels of concentrated poverty within these regions. In addition to a bolstered U.S. economy, reductions in unemployment, and the expansion of 2 the Earned Income Tax Credit (EITC), a number of federal initiatives such as the Hope VI, Moving to Opportunity (MTO), and “Portfolio Reengineering” programs were implemented with the goal of mitigating both the concentration of public housing and poverty within such neighborhoods (Goetz 2000, 2003; Jargowsky and Yang 2006). In light of these findings, more recent research has expanded the discourse on poverty concentration, breaking from ‘historical’ studies in the areas of conceptualization, geographic focus, and measurement. Building upon the dramatic decrease in concentrated poverty during the 1990s, Jargowsky and Yang’s (2006) investigation of the contemporary ‘state of the underclass 1 ’ revealed that “fewer neighborhoods now resemble the depressing descriptions of the inner city that were commonplace in journalistic and scholarly accounts of previous years” (p. 67). These findings demonstrate that the changes in concentrated poverty neighborhoods are two- fold; not only have such neighborhoods decreased in number, but they are not necessarily disproportionately home to residents with dysfunctional behaviors or social ills either. Similarly, research by Sessoms and Wolch (2008) assessed the relevance of traditional poverty measurement tools - namely the 40 percent threshold - to denote neighborhoods of extreme poverty, concentrations of social ills, and degraded physical landscapes. Their analysis of inner-suburban concentrated poverty landscapes in Los Angeles underscored the inability of the 40 percent criterion to highlight emerging trends in the landscape of concentrated poverty, and demonstrated that the effects of globalization and attendant economic and demographic restructuring processes were the 1 As defined by Ricketts and Sawhill (1988) 3 primary catalysts for conditions of impoverishment, rather than social pathologies or specific economic problems associated with the Urban Underclass debate. Finally, and again diverging from historical research on concentrated poverty, which focused primarily on African Americans, Strait (2006) investigated poverty concentration among not only Blacks, but Whites, Latinos, and Asians as well. Findings highlighted the relevance of compositional and redistributive forces in the production of concentrated poverty. Also of note, the geographic setting of Los Angles represents another significant departure from historical research, which focused on the Midwest and East Coast. However, characterized by globalization, racial/ethnic diversity, as well as extreme levels of social and economic fragmentation, it represents the “signal case of the American urban future” (p. 73) and, therefore, serves as an ideal locale in which to analyze burgeoning conditions of economic polarization, as well as associated catalysts. In short, much of we know about poverty concentration in the United States has been called into question. Meanwhile, and in sharp contrast to concentrated poverty and diverging from studies focused on the ‘sociology of affluence’ (see Phillips 1989, Oliver and Shapiro 1997, Conley 2003, Shapiro 2004), little research has focused on affluence concentration and its spatial distribution. This, in some ways, is understandable given long-standing notions such as the American Dream, which demonstrate the reverence that affluence has been afforded in the United States. However, when viewed in tandem with poverty concentration, the negative aspects associated with this particular phenomenon become more evident. Chief among these is the unequal distribution of resources, such as quality 4 of housing, employment opportunities, schools, as well as amenities and municipal services. Also, given increasing population diversity in affluent suburban communities, conventional notions of what constitutes an upscale community may warrant modification. Some have focused on this topic of affluence concentration exclusively (Shaw 1997, St. John 2002). However, the majority of the research focusing on this phenomenon has analyzed it in relationship to concentrated poverty within the largest U.S. metropolitan areas (Massey and Eggers 1990, Massey 1996, Coulton et al. 1996). The first analysis of concentrated affluence, (Massey and Eggers 1993) revealed that, during the 1970s, this particular phenomenon increased at a rate that was far greater than that of concentrated poverty. Building upon this notion, additional research has supported these findings, emphasizing global economic restructuring as the primary catalyst for increasing levels of economic polarization, while advancing the notion of a mutually supportive relationship between concentrated poverty and concentrated affluence (Massey 1996). Additional research, however, has refuted this notion and instead argued that the two phenomena are unrelated (Coulton et al.1996). Research Questions This dissertation advances the hypothesis that - much like concentrated poverty - concentrated affluence is becoming increasingly suburbanized. This process is perpetuated by similar factors working to suburbanize concentrated poverty, including the suburbanization of employment opportunities, racial residential segregation in the form of expensive, homogenous housing developments and gated communities that 5 exclude less affluent people of color, but rely on their low-wage service labor, and deepening income inequality. The research questions listed below enable me to address my hypotheses with additional focus and clarity. (1) a. During the 1990s, did increasing levels of affluence concentration accompany the suburbanization of concentrated poverty in the United States? b. What is the relationship between poverty and affluence concentration? c. What factors are responsible for recent trends? (2) a. How do landscapes of concentrated poverty and concentrated affluence compare with traditional characterizations of ‘underclass neighborhoods’ and ‘upscale communities’? Data and Methods Consistent with its multifaceted nature, this dissertation relies upon a mixed methodology, including the quantitative manipulation of census data, the use of spatial indices of segregation, and multivariate regression models, as well as qualitative techniques, including structured observations and photography. In light of recent research highlighting the significant decrease in poverty concentration during the 1990s and simultaneous increase within some inner-ring suburbs (Jargowsky 2003, Kingsley and Petit 2003), this dissertation begins with an analysis of national trends in the spatial distribution of suburbanizing concentrated poverty, as well as trends in the concentration of affluence within the 50 largest Metropolitan Statistical Areas of the U.S. 6 First, Geolytics software is utilized to attain normalized, tract-level data from the 1990 and 2000 Census of Population and Housing. The metro-scale has been utilized in similar analyses of both poverty and affluence concentration and is sufficient to provide both regional diversity and robust statistical findings. Previous studies of poverty and affluence concentration, have utilized statistical indices to assess the pattern and degree to which economic segregation exists within various spatial units of analysis (block groups, census tracts, etc.). Therefore, this research utilizes the Concentration Index (C = Σ k i=1 Pi/P) and 40 percent threshold to define concentration and extreme poverty, respectively. However, due to the longstanding debate surrounding the inadequacy of the official poverty threshold 2 , which is unable to distinguish between regional variations in poverty associated with costs of living differentials (and housing costs in particular). Therefore, this aspect of the research relies upon an alternative threshold based on 150 percent of the official poverty benchmark to provide a more accurate picture of the poverty population. Once concentrated poverty tracts have been identified, those considered suburban (with the proportion of its housing stock built after 1960 above the regional average) were delineated, yielding suburban concentrated poverty tracts and allowing for the analysis of increases/decreases between the 1990 and 2000 levels. Meanwhile, unlike poverty, there is no threshold for affluence provided by the U.S. Census, nor does a federally defined benchmark exist. Therefore, this particular 2 see Orchansky 1978; Levitan and Shapiro 1987; O’Hare et al. 1990; Ruggles 1990, 1991; Schwarz and Volgy 1992; Fisher 1992, 1992; Citro and Michael 1995; Joassart-Marcelli and Wagle 2005 7 aspect of the analysis defines affluence as those households with median income levels that are six times the poverty rate for a family of four in 1989 ($12,674/$76,044) and 1999 ($17,029/$102,174), as well as the 40 percent threshold to denote concentration. Again, those tracts with the proportion of its housing stock built after 1960 above the regional average are considered suburban. Findings from this portion of the dissertation reveal the, while demonstrating that metropolitan regions commonly characterized by the presence of poverty concentration can also be characterized by their increasing levels of affluence concentration. Next, following the analysis of poverty and affluence suburbanization in the US during the 1990s, four multivariate regression models (poverty concentration 1990 and 2000, suburban poverty concentration 1990 and 2000) were constructed to examine the specific factors responsible for recent changes within various regions of the US. More specifically, this aspect of the chapter relies upon Two-Stage Least Squares multivariate regression models to unearth and explain the interdependent nature of relationship between concentrated poverty and concentrated affluence. Following the development of the 1990 and 2000 poverty concentration models, additional models were developed to explain the. However, these utilized different independent variables than those relied upon in the construction of the poverty models, and generated estimated affluence variable values. These values were then substituted into the poverty model. This particular ‘cleansing’ technique is often utilized in order to control bias associated with endogeneity. 8 The remaining two chapters of the dissertation argue that - used alone - conventional (quantitative) methods of poverty and affluence measurement are unable to adequately depict the specific, everyday politics of place associated with such landscapes, particularly in globalizing regions such as southern California. Additionally, these chapters interrogate the meanings of such stereotypes as ‘underclass neighborhood’ and ‘upscale community’ by examining the material and lived social realities present within inner-suburban neighborhoods of poverty concentration (Chapter 3) and suburbs characterized by the presence of concentrated affluence (Chapter 4). Both chapters rely upon long-standing quantitative methods, as well as qualitative techniques. First, using data from the 1990 and 2000 Census of Population and Housing, municipalities in Los Angeles County were selected for analysis. In Chapter 3, utilizing the Concentration Index, thirty of Los Angeles’ inner- suburbs were selected, analyzed, and grouped into one of four quadrants based on their 2000 concentrated poverty rate and the growth/decline in rate change that occurred between 1990 and 2000. One city was, then, selected from each quadrant for in-depth comparative analysis (Monterey Park, Cudahy, Long Beach, and Baldwin Park) and to ensure a solid cross-section of inner-suburban areas in various economic conditions and experiencing different economic trajectories. Within each city, tracts with concentrated poverty rates greater than forty percent were selected for detailed analysis (sixteen tracts in total). Additionally, given cost of living differentials - and increased cost of living incurred by southern California residents in particular (for ex: housing, transportation, etc.) - an alternative threshold based on 150 9 percent of the official poverty benchmark was utilized to provide a more accurate depiction of the poverty population within the selected study areas. Next, characteristics commonly associated with ‘extreme poverty’ neighborhoods were selected and measured. In doing so, I ascertain whether or not the selected areas meet these criteria and, thereby, validate the myriad assumptions of behavioral deviance and physical dilapidation commonly associated with them. The social and economic characteristics are defined as any census tract with high proportions (one standard deviation above the U.S. mean) of unemployment, high school drop-outs, welfare recipients, and female-headed households (see Ricketts and Sawhill 1988). Following an analysis of all U.S. tracts, the sum, mean, standard deviation, and upper threshold for high proportions of each behavioral category within each of the selected sixteen tracts are calculated. Lastly, given that such areas have been characterized by their “…threatening appearance, marked by dilapidated housing, vacant units with boarded-up windows, abandoned and burned-out cars, and men hanging-out on street corners” (Jargowsky 1997, p. 11), observational field work was conducted within each of the selected neighborhoods in order to better characterize the physical conditions present. In particular, the condition of the existing infrastructure, delivery of public services, and nature of economic activity in each area was analyzed. All tracts were visited at various times of the day and night to ensure accurate observations. Finally, in order to provide a more detailed assessment of poverty concentration, as well as greater insight into the changing topography of poverty landscapes in the region, tract profiles were constructed 10 using data from the 2000 U.S. These highlight demographic, socio-economic, and housing characteristics within each study area and aid in the discussion of findings. Chapter 4 relies upon many of the same quantitative tasks and quantitative techniques. Given the aforementioned data constraints associated with affluence measurement and consistent with previous studies, affluent households are defined as those with income levels that are six times the poverty rate or more for a family of four in 1989 and 1999. Again, the 40 percent threshold and Concentration Index were utilized to locate census tracts in which 40 percent of the households with income levels greater than the specified cutoff levels constitute neighborhoods of concentrated affluence in 1990 and 2000, and measure the ratio of affluent households within affluent census tracts. These steps yielded concentrated affluence rates for all eighty-eight municipalities in Los Angeles County for the years 1990 and 2000. Tract levels of affluence concentration were, then, aggregated to the city-level to allow for municipal comparisons and to assist in highlighting any changes in the levels of affluence concentration during the 1990s. Again, similar to Chapter 3, each municipality was, then, grouped into one of four quadrants based on their 2000 concentrated affluence rate and the growth/decline in rate change that occurred between 1990 and 2000, and one city was, then, selected from each quadrant for in-depth comparative analysis (Diamond Bar, La Canada Flintridge, Manhattan Beach, and Santa Clarita). This ensured a solid cross-section of municipalities in various economic conditions and experiencing different economic trajectories. Within each city, tracts with concentrated poverty rates greater than forty percent were selected for detailed analysis. In this particular chapter, twenty-one tracts were chosen. 11 Research on poverty concentration has ascribed social, economic, and physical characteristics to extreme poverty neighborhoods (census tracts with high proportions of unemployment, high school drop-outs, welfare recipients, and female-headed households). However, such linkages have yet to be developed between the concentrated affluence literature and upscale communities. Therefore, in Chapter 4, the rationale is applied that neighborhoods of extreme affluence are the opposite of extreme poverty neighborhoods. To that end, the social and economic characteristics of concentrated affluence areas are defined as tracts with high proportions of residents that are (1) married, (2) employed in professional, scientific, and technical services, (3) possessors of master’s, professional, or doctoral degrees, and (4) recipients of interest, dividends, and net rental income. These represent the inverse of the measures utilized to denote areas of extreme poverty (in Chapter 3). Again, following an analysis of all U.S. census tracts, the sum, mean, standard deviation, and upper threshold for high proportions of each behavioral category within the selected twenty-one tracts was calculated. Lastly, given the dearth of research on affluence concentration, descriptive characteristics of extreme affluence neighborhoods have rarely been offered. Instead, smaller spaces, such as gated communities, have served as exemplars and been utilized to advance notions of the physical characteristics present within affluent locales (see Blakely and Snyder 1997). However, such broad generalizations may ignore the increasing differentiation of affluence areas and over-emphasize the levels of social cohesion that exist, while under-emphasizing the social costs imposed upon those excluded. 12 To that end, a series of characteristics were developed, including the presence of elements of control (ex: parking regulations, homeowner’s associations, etc.), the presence and frequency of enhancements to neighborhood aesthetics (condition of housing stock, manicured lawns and gardens, etc.), the presence and frequency of indicators of privatization (security systems, cameras, etc.), and the presence, frequency, and attractiveness of Amenities (upscale shopping, golf courses, etc.). Relying on these characteristics, observational field work was conducted within each of the selected neighborhoods of affluence in order to better characterize the condition of the existing infrastructure, delivery of public services, and nature of economic activity. To ensure accurate observations, all tracts were visited at various times of the day and night. Again, using data from the 2000 U.S. Census, tract profiles were constructed in order to provide a more detailed assessment of affluence concentration and greater insight into the changing topography of affluence landscapes in the region. Findings from both chapters may reveal that neither poverty nor affluence is monolithic and, as a result, conceptualizations of ‘concentration’ must be flexible, depending upon the place - specific politics embedded within their complex social and built environments. Overview of Dissertation Previous studies of poverty concentration have focused on the tenuous relationship between race and class-based catalysts and sought to assess their detrimental effects upon the physical and social make-up of urban neighborhoods of the Midwest and East Coast. However, given the dramatic changes that beset the landscape of concentrated poverty, this initial chapter of the dissertation proposes a new agenda for 13 the study of concentrated poverty, including the investigation of new catalysts, geographic foci, and methods of measurement in order to accurately depict and articulate emerging conditions of economic polarization. Next, building upon previous analyses of affluence concentration - and considering the aforementioned trends in the spatial distribution of concentrated poverty - I analyze trends in both the ‘suburbanization’ of concentrated poverty and the concentration of affluence within the 50 largest Metropolitan Statistical Areas of the U.S. during the 1990s. In particular, this chapter seeks to ascertain whether or not trends in the suburbanization of concentrated poverty were accompanied by parallel trends in the concentration of affluence. In doing so, it (1) investigates the changing metropolitan geography of concentrated poverty, as well as shifts in the geography of concentrated affluence, (2) examines the specific factors responsible for recent changes in the landscapes of poverty and affluence concentration, and (3) assesses the extent to which poverty concentration within suburban zones both explains - and is explained by - patterns of affluence concentration. Based upon research conducted in the Los Angeles metro-region, the following chapter interrogates the meaning of concentrated poverty, which has been based on a 40 percent benchmark. This threshold defines ‘extreme poverty’ census tracts (neighborhoods) as those in which 40 percent or more of the population lives below the federal poverty threshold. However, given recent changes in the topography of poverty, traditional notions of ‘extreme poverty’ neighborhoods, as well as inherent assumptions about their character, may no longer apply. The chapter assesses whether or not selected 14 neighborhoods of ‘extreme poverty’ match traditional ideas of such areas as portrayed in previous research employing the 40 percent threshold. Additionally, it investigates the physical environments of these spaces, as well as the social profiles of their residents in order to compare with traditional conceptualizations. Finally, urban geographic research on economic segregation has rarely focused on affluence concentration, rendering our understanding of this particular phenomenon and general conditions of inequality incomplete. However, changes in the spatial distribution of poverty concentration during the 1990s may have also influenced the landscape of affluence concentration in profound ways. Also based upon research conducted in the Los Angeles metro-region, this chapter investigates the presence and levels of residential defensiveness that exist within selected affluent neighborhoods. In doing so, it moves beyond previous analyses of affluence concentration, by providing insight on the behavior of affluent residents and challenging long-standing ideas regarding the material and lived social realities of extreme affluence landscapes. Introductory Conclusions and Policy Implications This research seeks to investigate geographic trends in the suburbanization of concentrated poverty, as well as parallel trends in the concentration of affluence during the 1990s. In addition to enhancing our understanding of the factors that reinforce and maintain conditions of economic polarization, results make significant contributions to theories of urban poverty and metropolitan form, as well as globalization. First, this research will contribute to our understanding of spatially concentrated poverty - a topic that has received little attention from geographers. While challenging 15 long-standing assumptions regarding their urban nature and ties to so-called ‘underclass’ populations, it demonstrates that - within the globalizing southern California region - landscapes of concentrated poverty are in fact diverse. Such diversity would lead us to rethink conventional notions of urban form and dynamics that are foundational to much of human geographic scholarship on cities. Meanwhile, the spatial concentration of affluence represents a topic that has received even less attention within urban geographic literature. However, this research reveals that suburbs and exurbs are also deserving of our attention, as they may have become the locales most impacted by burgeoning conditions of economic polarization. Additionally, by providing insight into the behavioral tendencies of those residing within affluent neighborhoods, it illuminates the varied social, economic, and political costs that such concentrations impose upon the general public. Third, this research challenges various aspects of globalization theory by linking trends in the global economy to changes in the metropolitan geographies of poverty and affluence segregation and, in particular, social outcomes at the local level. By articulating the complexities reflected within the social and built environments of both poor and affluent neighborhoods, it emphasizes that the impacts of ‘concentration’ on urban/inner- suburban and suburban/exurban fiscal capacity and service delivery will vary significantly as well. Finally, from a policy perspective, this dissertation considers the ways that conventional methods of measurement will continue to shape public perceptions - and, more importantly, the nation’s policy debates - in inappropriate ways, given its inability 16 to accurately characterize landscapes of poverty and affluence concentration as they become increasingly variegated. Moreover, by demonstrating that, during the 1990s, that affluent households engaged in various forms of residential defensiveness in order to isolate themselves from crime, decreasing property values, and an increasing poverty population - often comprised of people of color - in order to secure a disproportionate share of vital resources, it signifies the need for stronger regional policies in the areas of housing and governance. 17 CHAPTER 1  CONTEMPLATING CONCENTRATION:   GEOGRAPHY AND THE NEW CONCENTRATED POVERTY   The Reprise of Concentrated Poverty Recent research demonstrates that much of what we knew about poverty concentration no longer holds true. Over twenty years ago, William Julius Wilson produced what is considered by many to be the most influential work on concentrated poverty. His account of the Truly Disadvantaged (1987) awakened the discourse surrounding poverty from its lengthy slumber, and returned it to the nation’s urban policy agenda. The extensive canon of research which followed included a substantive debate regarding the causes and determinants of poverty concentration, its spatial distribution, as well as its perceived behavioral impacts and social ramifications. Later, however, in light of the negative response generated by the urban underclass debate, which in the minds of many scholars was intimately linked to perceived social pathologies and the urban nature of poverty concentration, research on this particular topic declined significantly. In contrast, more recent analyses of poverty concentration have signaled its re- emergence as a prominent field of academic inquiry. Diverging from previous studies, this work has sought to both re-focus and expand the discourse, given the emergence of globalization and attendant economic and demographic restructuring, salient changes in the geography of concentrated poverty and, in particular, its growth within inner- suburban areas, and questions regarding the efficacy of standard methods of measurement. While these analyses demonstrate that historical conceptualizations and 18 measurement strategies lag behind present-day realities, they also represent a significant need to move the discourse forward in several important respects. To that end, this research aims to set forth a new agenda for the study of concentrated poverty. While acknowledging the contributions of and building upon historical research, I advocate for a more inclusive conversation that incorporates contributions from various social science perspectives and geographers in particular. More specifically, I argue that broadening our horizons to accommodate emerging viewpoints and additional perspectives, will lead to a more substantive discourse, as well as the development of more informed policies designed to address the increasingly complex landscape of poverty concentration in the United States. The progressive nature of such a discourse is the first step in moving beyond pointless discussions regarding the salience of race-based versus class-based catalysts and, instead, highlighting the role played by more recent factors such as globalization and attendant economic and demographic restructuring processes. Additionally, although rarely considered, factors that lead to the concentration of affluence may also work to create and maintain conditions that characterize the emerging landscape of concentrated poverty. To that end, future analyses of economic polarization may be more appropriate, as the focus of previous urban studies have generally been ‘one-sided’ in nature. I begin by reviewing the dominant theoretical conceptualizations of poverty concentration in the United States, including its primary drivers. Next, I examine research concerning the urban geography of concentrated poverty. This body of literature discusses the nature and impacts of the spatial distribution of poverty concentration 19 within the nation’s largest metropolitan areas. Following, I focus on the various methods and specific techniques aimed at the quantification and qualification of concentrated poverty. In doing so, I provide a historical perspective on the measures - both traditional and alternative - that have been employed to assess the extent and degree of this particular phenomenon. Additionally, considering the one-sided nature of urban geographic studies of income segregation, which have focused on the poor and the perceived social pathologies commonly associated with urban poverty, I briefly summarize research on affluence concentration in the United States. In suggesting that this phenomenon may serve as a catalyst for concentrated poverty, I also raise the possibility that an interdependent relationship exists between the two. In doing so, I highlight the need for future research to consider a broader focus on economic polarization, rather than poverty segregation alone. Finally, I offer a research agenda that centers on these and related issues that stand to affect the study of poverty concentration, as well as poverty policy. Conceptualizing Concentrated Poverty – Past and Present Although, more recent research has investigated its impacts upon Whites (see Mulherin 2000), traditional analyses of poverty concentration have primarily centered upon African Americans, while focusing on the Rustbelt/Snowbelt areas of the Midwestern and Northeastern areas of the United States. In stark contrast, this expansive canon of research contains the contributions of economists, historians, and poverty researchers writing from various social science perspectives. However, the vast majority of these studies have been conducted by sociologists. 20 Provocative in its presentation of a liberal and race-neutral view of urban poverty and its increasingly concentrated nature, the work of William Julius Wilson stands as, arguably, the most noteworthy entry. In particular, this research has served as the catalyst for major debates regarding the causes and determinants of concentrated urban poverty. While multi-faceted, these perspectives have revolved around the influence of structural forces situated at the nation-state level of scale such as race, class and income inequality, as well as local-level political, cultural, and economic forces that are geographically specific in nature, and individual-level characteristics. Wilson’s Chicago-based empirical research revealed three basic findings: (1) Poverty became more spatially concentrated during the 1970’s; (2) Structural changes within the economy were primarily responsible for the exacerbation of poverty, especially within impoverished, African American neighborhoods; and (3) Taking advantage of affirmative action programs, members of the African American middle- class fled the ghetto, distancing themselves from working-class African Americans. According to Wilson, this separation fostered a sense of hopelessness that resulted in the formation of an urban underclass population that was isolated, both economically and socially. Moreover, although it described the plight of impoverished African Americans per se, the central focus this research was the way in which transformations in the structure of the US economy significant altered the class-structure of inner-city neighborhoods resulting in a growing schism between non-poor, black middle and working classes. 21 Later, Wilson (1991) altered his argument slightly, emphasizing that the causes of social dislocation were numerous and deeply rooted, only one of which being the structural transformation of the U.S. economy. While highlighting the effects of such factors as occupational bifurcation, political processes, racial discrimination, shifts in family organization, a decrease in the number of marriageable men, and variations in the distribution of income and employment, he subsequently re-named the underclass population the ghetto poor (although the term underclass continued to be widely and often pejoratively used – see Gans 1990). Wilson’s conceptual framework and nuanced findings served as a template for subsequent research which, in many cases, confirmed his general hypothesis (see Rickets and Sawhill 1988, Jargowsky and Bane 1991, Kasarda 1993, Galster and Mincy 1993). However, others levied sharp criticism toward some of the more detailed components of his analysis. For example, Sanchez-Jankowski (1999) argued that Wilson “may have overemphasized the importance of the middle class’ absence from these (impoverished) areas in exacerbating isolation and hopelessness…” (p. 635). Meanwhile, others have regarded the proposed correlation between the perceived social pathologies of the ghetto poor and minorities as being an exaggeration (Alex-Assensoh 1997). Still others directed their criticism toward Wilson’s concept of an urban underclass. For example, Hughes (1989) asserted that although “…these distinct groups share a physical attribute (ghetto residence), …it is an heroic inference that therefore these groups share a fundamental acculturation toward work and family and so on” (p. 191). While these debates are deserving of considerable elaboration, they have been taken up elsewhere (see, for 22 example, Gilbert 1997). Here, I instead focus on critiques regarding the causes and determinants of concentrated urban poverty. Sociologist Douglas Massey and his co-workers have offered the most notable opposition to Wilson’s hypothesis regarding poverty concentration per se. Massey and Denton (1993) asserted that residential segregation fueled by racist practices within the residential housing market were the primary catalysts for increasing levels of concentrated poverty. Later, Massey et al. (1994) were even more assertive in their refutation of Wilson’s hypothesis. Based on their empirical analysis of in and out- migration patterns within poor neighborhoods, they asserted that “…geographically concentrated poverty ultimately stems from racially segregated U.S. housing markets” (p. 442). These sentiments are salient for two reasons in particular. While subsequent studies of poverty concentration often duplicated Wilson’s (1987) methodology, these researchers argued that such analyses were incomplete and inaccurate, as the methods of measurement used in had not fully utilized the data available to convey the spatial distribution of income. Instead, utilizing indices of segregation, they argued that a rise in poverty concentration had not been validated. Additionally, they demonstrated that Wilson’s primary focus on class failed to acknowledge the ways in which race and, in particular, historical, institutional racism and white privilege in the residential housing market, had on socio-economic status. In the years following, a long-standing debate ensued between these scholars regarding the primacy of race-based versus class-based catalysts. However, others 23 posited that the catalysts for increasing levels of concentrated poverty were multifaceted in nature. Historian Thomas Segrue (1996) argued that “…no one social program or policy, no single force, whether housing segregation, social welfare programs, or deindustrialization could have driven Detroit and other cities like it from their positions of economic and political dominance…” (p. 5). Emphasizing the effects of capitalism and the inherent conditions of economic inequality that disproportionately affected African Americans (such as the loss of entry-level manufacturing jobs), he posited that the “…coincidence and mutual reinforcement of race, economics and politics in a particular historical moment from the 1940s through the 1960s set the stage for the fiscal, social and economic crises that confront urban America today” (p. 5). Similarly, economist Paul Jargowsky (1997) advanced the notion that, “…the primary factors behind the increasing concentration of poverty are metropolitan economic growth and the general processes that create and sustain segregation by race and class” (p. 185). By emphasizing that the contributions of race and class were not mutually exclusive, these hypotheses partially shifted the focus of concentrated urban poverty research away from a discourse centered on individual-level causes at a time when many researchers were emphasizing individual behavior and perceived social pathology as integral to poverty concentration, or arguing for the primacy of race in the dynamics of concentrated poverty neighborhoods. Theoretical conceptualizations of concentrated poverty have revolved around the tenuous relationship between race and class, as well as the notion that these social constructs often work in tandem with fluctuations in metropolitan economies to influence 24 levels of inequality, while focusing on the plight of Blacks and their perceived behavioral tendencies. As these analyses became intimately related to investigations of the urban underclass, concentrated poverty has often been portrayed as a Black problem. However, such a focus demonstrates a limited racial perspective, given the increasing globalization of the economy and attendant transformations in the economic, social, and demographic composition that has occurred and continues within several globalizing US city-regions (Los Angeles, New York, Miami). In particular, the deindustrialization and reindustrialization of key sectors, as well the rise of the service sector have significantly altered metropolitan labor markets, as positions traditionally occupied by the middle- class, have been replaced by low-wage, non-unionized jobs and high-skill, high-wage positions, often contributing to severe income polarization. In light of such modifications, the globalizing economy has rendered these and other metro-areas major destinations for international labor migration flows as burgeoning levels of poverty and inequality have become characterized by a rapidly growing working-poor population. Largely comprised of Latinos and recent immigrants of other national origins, these individuals occupy many of the newly created low-wage positions in the manufacturing and service sectors. This represents a markedly different portrait of poverty than the one painted for over twenty years by research on the urban underclass. To that end, more recent analyses have sought to emphasize the effects of these transformations on the concentration of poverty process. In doing so, they have examined poverty concentration within a much wider racial context. For example, while 25 highlighting the relevance of compositional and redistributive forces in the production of concentrated poverty, Strait (2006) asserted that levels of poverty concentration among not only Blacks, but Whites, Latinos, and Asians should be assessed. Meanwhile, Sessoms and Wolch (2008) emphasized the increasing levels of differentiation within concentrated poverty neighborhoods. Their sample was characterized by the presence of Blacks, as well as large Latino and Asian immigrant populations (both young people and older immigrants reunited with families). Many of these residents were employed in the growing number of low-skill, low-wage, non-unionized jobs necessary to support burgeoning nondurable manufacturing, transportation, and services industries linked to global trade and local-serving retail and consumer-services sectors. Despite differences in race and educational attainment, many of these residents work full-time, but are unable to obtain enough income to rise above the poverty threshold. Such profiles highlight the presence of an emerging working poor population and question the contemporary relevance of previous studies which linked poverty concentration to neighborhood unemployment rates among other related factors (Ricketts and Sawhill 1988, Jargowsky and Bane 1991). Findings indicated that although these types of communities are ‘burdened’ by low homeownership rates, crowded housing, and high rental costs, they are not necessarily characterized by social pathologies or specific economic problems associated with poor Blacks stigmatized by the underclass debate. In demonstrating that “…poverty is not a monolithic phenomenon” (p.83), this research articulates the need for forthcoming depictions of poverty concentration to be flexible and more nuanced in order to minimize the possibility of misrepresentation. 26 Changing Geographies of Poverty Concentration in the U.S. The primary drivers of poverty concentration have also served as a fertile topic for substantive scholarly deliberation. However, Wilson’s seminal work also provided the impetus for research which sought to analyze and provide explanations for the geography of poverty concentration. Situated at the nation-state level of scale, this research privileged the urban as the default area of analysis. Again, much of this work has been conducted by sociologists. Geographers, however, have been largely absent from the discourse on concentrated poverty, as well as that of the related urban underclass, with notable exceptions (see Hughes 1989, Kodras 1997, Cooke 1999, Gilbert 1997). Much of this silence can be attributed to the discipline’s reluctance to engage in issues that pertain to race (see The Professional Geographer Vol. 54, No.1) as well as the lingering effects of the Environmental Determinism movement, which it espoused during the early portion of the 20 th century (see Peet 1985). However, despite this lack of assertiveness, it is within this particular strand of research that geographers appear to have found their niche. The majority of their work has underscored the mediating effect of place and place-specific processes in the manifestation of concentrated poverty. More specifically, they have built upon the idea that the catalysts for poverty concentration are not mutually exclusive, while emphasizing the notion that such catalysts work together to produce complex relationships that vary depending on local cultural, economic, and political factors. Although not written from a geographic perspective per se, research by Frey and Fielding (1995) exemplifies the notion of the multifaceted, yet spatially diverse nature of 27 urban poverty concentration. These researchers argued that, “Changes over the 1980s in the concentration of poverty in cities varied widely across metropolitan areas, depending on the volume and destinations of immigrants and internal migrant streams and on differential changes in the income levels of city and suburban residents” (p. 29). These findings highlight the dual importance of immigration and inter-community dynamics, in addition to differences in metropolitan inequality. Later, geographer Janet Kodras (1997) demonstrated the ways in which poverty is commonly visualized as a set of statistical incidents, rather than an “…experience and a generative process” which varies spatially (p. 79). Utilizing data from the U.S. Census, she mapped county-level poverty rates and presented five brief case studies of geographic variation - Detroit, Michigan, Silicon Valley, Eastern Kentucky, the Mississippi Delta, and the Dakota Badlands. While these findings confirm that poverty is experienced differently in different places, it further illustrates the relationship between economic, cultural, and political transformations and, more importantly, their geographic nature. Building on these findings, geographer Thomas Cooke (1999) asserted that places, and their geographically specific characteristics (such as race, class, and gender), serve as mediators of broader processes, such as structural economic changes and processes of residential segregation. Utilizing census data, he analyzed concentrated poverty tracts within US metro-areas and classified them based on their racial and class composition. Each of the four clusters demonstrated varying poverty rates and associated characteristics. Cooke’s findings confirmed that the causes of concentrated urban poverty are dependent upon both local and regional forces, rather than broader social and 28 economic forces situated at nation-state level of scale or individual-level behavioral factors alone, and that race, as well as class matter to our understanding of urban poverty concentration. Similar sentiments have been expressed in more recent research. Focusing on the Atlanta metro-area, Strait (2001) utilized census data, as well as indices of segregation, to examine variations in levels of poverty concentration. Findings revealed that: (1) Changes in the region’s composition of the poor and non-poor were responsible for decreased levels of poverty exposure, underscoring the effect of metropolitan-wide economies in the concentration of urban poverty and the sentiments expressed by Jargowsky (1997); (2) The spatial redistribution of population in Atlanta increased both African American and White exposure levels to poverty, emphasizing the impact of class-specific migration and the assertions of Wilson (1987); and (3) Although the isolation/exposure indices indicated high levels of racial segregation, decreases in poverty isolation and exposure were the result of increasing levels of racial integration. While these findings highlight the influence of both race and class in the formation of racial clusters, it also emphasizes that, despite compositional changes, redistributive forces greatly impacted the residential well-being of the poor. Research on the geography of concentrated poverty has demonstrated a focus on the Rustbelt/Snowbelt areas of the Midwestern and Northeastern United States, as well as urban areas. However, this tendency has recently been called into question. Given general increases in the West, recent investigations have focused on the Los Angeles metro-area (Strait 2006, Sessoms and Wolch 2008). The geographic setting of Los 29 Angles, thus, represents a significant departure from those areas, such as Chicago, Detroit, Cleveland, and Milwaukee that have been represented in ‘traditional’ research. However, characterized by globalization, racial/ethnic diversity, as well as extreme levels of social and economic fragmentation, Los Angeles represents the “signal case of the American urban future” (Strait 2006, p. 73) and, therefore, serves as an ideal locale in which to analyze emerging conditions of poverty concentration, as well as burgeoning conditions of economic polarization, and associated catalysts. Such changes in the topography of concentrated poverty underscore the need in forthcoming studies for a renewed emphasis on the vital role of place and place-specific processes, as well as the mediating role played by local-level cultural, political and economic factors. While the work of scholars writing from various social science perspectives has aided in our overall understanding of the poverty concentration process, the fact remains that concentrated poverty is, if nothing else, a spatial phenomenon (Glasemier 2002) with tangible social effects that are often experienced in different ways. Therefore, a geographic perspective is warranted and allows the persistence of poverty concentration to be examined through the lenses of place and scale. To that end, geographers in particular, stand to play a key role in analyzing and articulating the various patterns and forms of poverty segregation and economic polarization in general. For example, although poverty concentration increased in southern California during the 1990s, research by Joassart-Marcelli et al. (2005) revealed that cities within the region also experienced different levels and types of segregation - including unevenness, clustering, and isolation – that changed significantly over time. In particular, 30 cities where poverty had been high and increasing often maintained a high level of clustering and unevenness, but experienced higher levels of concentration and clustering in 2000. In contrast, wealthier cities typically experienced a rise in unevenness and clustering, as small pockets of the poverty population emerged in the midst of high- income neighborhoods. Similarly, while criticisms of the federal poverty threshold are legion (Citro and Michael 1995, Madden 1996, Joassart-Marcelli and Wagle 2005), the most salient could very well be its inability to consider regional variations in cost of living expenses. For this reason, place-based comparisons of both poverty and ‘concentration’ are difficult to carry out. In order to address this shortcoming and, more importantly, guide flexible policies that are better able to assist residents, recent geographic research on poverty concentration has adopted alternative poverty thresholds that are sensitive to the increased costs associated with housing, transportation, utilities, groceries, and miscellaneous goods and services (Sessoms and Wolch 2008). This increased threshold, thus, captures those individuals whose income would otherwise render them on the margin or slightly above the poverty line - and, therefore, not poor - to be included in the poverty population. These examples underscore both the need for and importance of geographic research on poverty concentration, as such efforts will not only help assess the efficacy of existing theories, but also assist in the development of new, explanatory theories capable of providing more accurate depictions of concentrated poverty neighborhoods. 31 Measuring and Assessing Concentrated Urban Poverty In addition to providing commentary on spatial nature of poverty segregation, additional research has attempted to quantify formations of concentrated poverty in various geographic locations. To do so, scholars developed a sundry of measures to assess the extent and degree to which poverty has become concentrated. The measurement of concentrated poverty has commonly relied on the census tract as the primary unit of analysis. With total populations often fluctuating between 3,000 and 6,000, these areal units often serve as proxies for neighborhoods. However, from the inception of research on concentrated poverty, scholars have utilized a 40 percent benchmark which defines ‘extreme poverty’ tracts as those in which forty percent or more of the population lives below the federal poverty threshold. Despite its strong reliance on the federal poverty threshold and its arbitrary nature, this particular threshold remains the standard measure of poverty concentration (see Mincy, Sawhill and Wolf 1990; Massey and Eggers 1990; Jargowsky and Bane 1991; Jargowsky and Yang 2006). The forty percent benchmark was originally developed by the U.S. Census Bureau. Beginning in 1970, small area data and percentage-based thresholds based on income were made available for the purpose of categorizing impoverished neighborhoods. Although poverty rates of 20 and 30 percent were constructed in order to provide some degree of flexibility, areas in which 40 percent of the population lived below the poverty line became synonymous with ‘extreme poverty’. The fact that these thresholds were originally developed by the U.S. Census Bureau is significant. For many years, the decennial census has served as the primary source of comprehensive data at 32 various geographic scales and is, therefore, commonly relied upon by researchers. Moreover, given that this type of data was unavailable prior to 1970 scholars took full advantage of its potential to guide groundbreaking contributions (Danzinger and Gottschalk 1987). During the 1980s, this particular method of measurement became increasingly prominent and intricately tied to the urban underclass debate, as researchers became interested in examining the poorest of the poor and began to employ it exclusively in their analyses of behavioral deviance and dysfunction believed to be most prevalent within urban neighborhoods (Glasgow 1980; Auletta 1982; McLanahan et al. 1986; Van Haistma 1989; Jencks 1989; Ricketts 1989; Murray 1990). The most notable of these studies was conducted by Ricketts and Sawhill (1988), who based underclass existence on the geographic clustering of specific dysfunctional behaviors and asserted that “…extreme poverty areas can reasonably be used as a proxy for concentrations of social problems” (322). Thus, socially deviant behavior became linked with the 40 percent threshold. This particular methodology drew criticism (Hughes 1989; Jargowsky 1994) and, eventually, research on the underclass became mired in controversy (see Lehman 1986), as liberal scholars asserted that it was linked to the flawed “culture of poverty” thesis (Harrington 1962; Lewis 1966; Ricketts 1992). Additionally, scholars argued that the underclass terminology was a “…racial codeword that subtly hides anti-Black and anti-Hispanic feelings” (Gans 1990, 273). In response, researchers gradually turned their focus toward the urban nature of poverty concentration. Nevertheless, the 40 percent threshold gained ascendancy in urban poverty research. 33 Wilson (1987) was the first to employ the 40 percent criterion in his empirical analysis of poverty concentration within Chicago’s urban neighborhoods during the 1970s. In confirming these findings, scholars (Danzinger and Gottschalk 1987; Jargowsky and Bane 1991) endorsed the use of the 40 percent threshold to denote poverty concentration within urban areas. Later, these areas were also characterized by the presence of blight and decay, including deteriorated housing, abandoned structures with broken windows, discarded automobiles, and loiterers (Jargowsky 1997). Thus, concentrated poverty neighborhoods, already defined by economic deprivation and deviant behaviors, commanded attention based on their physical conditions, while the spatial nature of poverty was ignored (Massey and Denton 1990; Greene 1991). Although it continues to be employed in various analyses of poverty concentration (Orfield 1997; Cooke 1999; Goetz 2000; Mulherin 2000), scholars have developed and tested alternative measures and techniques (such as those detailed by Massey and Denton 1990; Greene 1991; Lee and Culhane 1998; Plewe and Bagchi-Sen 2001; and Sanchez-Jankowski 1999) designed to assess levels of poverty segregation. In the following paragraphs, I discuss these alternative approaches, as well as potential implications of their use. Building on the forty percent threshold, researchers have measured the spatial organization of concentrated poverty through the deployment of segregation indices. These statistical measures assess varying degrees and patterns of segregation within various units of spatial analysis. Although various indices exist, below, I briefly summarize the ways in which the most commonly used have been deployed. 34 Particularly in terms of assessing levels of poverty segregation, the Concentration Index has been utilized in tandem with the 40 percent criterion to measure the ratio of poor people residing in extreme poverty neighborhoods (Massey and Denton 1988, Coulton et al 1996). Coulton et al. (1996) assert that this measure is “most directly related to the absolute neighborhood circumstances of the poor or affluent, because it reveals how likely they are to live at one extreme or the other” (p. 194). The use of this particular index, however, requires a definition of extreme poverty. As discussed earlier, such definitions tend to be arbitrary, and may apply to specific times and places. This creates a major drawback to its use. One of the most commonly used indices is the Index of Dissimilarity (Tauber and Tauber 1965, Massey and Denton 1988, Abramson, Tobin and VanderGoot, 1995, Coulton et al, 1996). This particular index informs us of what percentage of a given population would have to relocate in order for their distribution to be evenly dispersed across spatial units of analysis (census tracts, etc). While relatively easy to comprehend, this particular measure has received criticism, as well. Coulton et al. (1996) asserted that while this index accurately measures separation, it does not accurately measure extremes. Thus, it is not sensitive to such phenomena as income polarization. In addition, Ethington (2000) has voiced two disadvantages regarding this measure, citing its insensitivity to relative population sizes, and the fact that it can only be used to measure differences between two groups. The latter remains a significant barrier to its use in measuring evenness within places that demonstrate extreme levels of racial diversity. 35 Meanwhile, the Isolation and Exposure Indices are asymmetric measures of intergroup interaction (Lieberson 1981, Massey and Eggers 1990). The Isolation Index calculates the probability that a poor individual is isolated from more affluent individuals, while the Exposure Index measures the degree to which these populations will come into contact with each other. Unlike the Dissimilarity Index, these particular measures are sensitive to both proportions and relative population sizes of the groups being researched (Ethington 2000). Methods of concentrated poverty measurement have been diverse in purpose, geographic scale, and statistical technique. The forty percent threshold, however, evokes notions of geographic spaces marked by the presence of dilapidation and disinvestment, as well as impoverished African American residents engaged in dysfunctional behavior. However, recent research has demonstrated that this is deeply misleading, while highlighting this particular measure’s inability to provide a suitable representation of the emerging landscape of poverty concentration (Sessoms and Wolch 2008). Therefore, despite its long-standing prominence, new methods of measurement are in order, as our continued reliance upon this particular strategy may result in the most detrimental effects of concentrated poverty going unnoticed as well as the misdirection of policies that might improve the plight of the urban poor. Such measures must be sensitive to recent changes in the spatial distribution of poverty concentration, which are largely due to the impacts of globalization, state devolution, and fiscal federalism. Additionally, the inadequacies embedded within current poverty measures suggest that, used alone, such measures depict only a portion of the specific politics of place or 36 everyday lived experience within concentrated poverty neighborhoods. In this way, they represent a hands-off approaches to poverty measurement based upon simple assumptions, rather than nuanced empirical research. Such false portrayals often lead to the formation of negative perceptions (such as the urban underclass) that are long lasting and difficult to overcome. Alternative Measures of Concentrated Urban Poverty While the use of traditional methodologies is pervasive throughout much of the concentrated poverty literature, alternative measures - both quantitative and qualitative in nature - have been deployed. The development and usage of these measures further emphasizes the inability of traditional methods depict the increasingly complex manifestations and spatial distributions of concentrated poverty and, in turn, provides insight into the level of sophistication and intricacy that may be required. Emphasizing the salience of spatial contiguity in concentrated poverty measurement, Greene (1991) argued that conventional measures lacked the ability to distinguish between dispersed and clustered poverty concentrations, resulting in the treatment of concentrated poverty tracts as if they “are independent and self-contained settlements” (p. 240). Utilizing the standard radius to calculate the distribution of concentrated poverty tracts around their mean centers, Greene’s analysis revealed two types of concentrated poverty tracts in U.S. cities - nucleated extreme poverty tract clusters (older concentrated poverty tracts surrounded by those that were recently formed) and dispersed settlements (older concentrated poverty tracts coupled with those that were newly formed in outlying areas). Based on these findings, he concluded that, 37 “Areal growth of large poverty settlements in cities does, indeed, provide a necessary, but not a sufficient condition for the existence of an underclass, as suggested by Wilson (1987)”. Meanwhile, Lee and Culhane (1998) emphasized the inadequacy of poverty concentration measures that were insensitive to spatial interaction across areal units and highlighted the importance of contiguous distributions across adjacent areal units. These researchers asserted that, “a high degree of clustering does not always represent a high degree of contiguity” (p. 328). Their findings revealed the existence of isolated enclaves, which are characterized by high levels of concentration and separateness, as opposed to spatial contiguity alone. These analyses articulate the idea that concentrated poverty tracts vary in terms of their formation and spatial distribution, that adjacent tracts play a role, and that these variations can, in some cases, have complex social ramifications. Meanwhile, Plewe and Bagchi-Sen (2001) proposed the use of (population) Weighted and Partially Weighted Ternary Histograms. While these histograms identify and describe segregation patterns, examine the interaction between different variables, and possibly, visualize change over time, they experience difficulty in explaining the presence and effect(s) of neighborhood clustering, limiting them to identification and descriptive uses, rather than explanation. Finally, Sanchez-Jankowski (1999) raised fundamental questions about the wisdom of and reliance on quantitative measures alone. Rather, he utilized qualitative methods to investigate the specific way(s) that structural forces impact everyday life. His five-year ethnography within inner-city neighborhoods of Detroit, Los Angeles, and New 38 York revealed that the exodus of those with higher economic standing played a greater role in generating large concentrations of poor people than did inter-community dynamics, as argued by Wilson (1987). Moreover, findings from Los Angeles and New York, in particular, illustrated the impact of immigrant populations seeking low-rent housing or the establishment of ethnic enclaves, and their tendency to occupy areas adjacent to impoverished or working-class African Americans. The presence of such enclaves suggests that growth in poor African American neighborhoods did not occur in an unabated fashion, and speaks to the significant effects that immigration can impose upon more common conceptualizations of concentrated poverty. Such research demonstrates that, while the original catalysts for concentrated poverty were racial segregation and community unemployment, respectively, the rigid race-class assertions made by Wilson (1987) and Massey and Denton (1993) underestimate the effects of internal community dynamics and neighborhood push-pull factors. This study follows an extensive line of research, highlighting the perceived behavioral patterns of the urban poor. Indeed, this constitutes another strand of research that was rejuvenated by the work of Wilson (1987). The alleged presence of social pathologies, including violent crime, drug abuse, out-of-wedlock births, low educational attainment, and unemployment, has been well documented by conservative researchers interested in contesting liberal social policies aimed at assisting this particular population (Moynihan 1965, Lewis 1966, Murray 1984). While these assertions are not the focus of this essay, the perceived behavioral tendencies of residents in impoverished neighborhoods, as well as the responses of residents in the middle and upper stratum may 39 begin to illustrate the presence of a mutually supportive relationship between concentrated urban poverty and concentrated affluence. From Poverty Concentration to Economic Polarization In light of its predominant focus on the poor, their spatial distribution, and perceived behavioral tendencies, urban scholarship has rarely discussed the notion of affluence concentration. Therefore, little is known about this particular stratum. While concentrated poverty possesses a tendency to attract attention due to perceived by- products of social pathologies, concentrated affluence carries with it a patina of strength, fortitude and social well-being that implies all is right in the world and no research is actually needed (Shaw 1997). This, in some ways, is understandable given such long- standing notions as the ‘American Dream’, which demonstrate the reverence that affluence has been afforded in the United States. However, when viewed in tandem with poverty concentration, the negative aspects associated with this particular phenomenon become more evident. Chief among these is the unequal distribution of resources, such as quality of housing, employment opportunities, schools, as well as amenities and municipal services. Some have focused on this topic of affluence concentration exclusively (Shaw 1997, St. John 2002). However, the majority of the research focusing on this phenomenon has analyzed it in relationship to concentrated poverty within the largest U.S. metropolitan areas (Massey and Eggers 1990, Massey 1996, Coulton et al. 1996). The first analysis of concentrated affluence, conducted by Massey and Eggers (1993), revealed that, during the 1970s, this particular phenomenon increased at a rate that was 40 far greater than that of concentrated poverty. Additional research has supported these findings, emphasizing global economic restructuring as the primary catalyst for increasing levels of economic polarization, while advancing the notion of a mutually supportive relationship between concentrated poverty and concentrated affluence (Massey 1996). However, research has refuted this notion and, instead, argued that the two phenomena are unrelated (Coulton et al.1996). In light of new developments in the spatial distribution of concentrated poverty, numerous questions regarding the affluent remain which warrant further consideration. In particular, as concentrated poverty becomes increasingly suburbanized, what are the behavioral responses of the affluent? During this time-period, did affluent households seek to isolate themselves from crime, decreasing property values, and an increasing poverty population, comprised of Blacks, Latinos, and other residents of color, including recently arriving immigrants? Such behavior often leads to a disproportionate share of resources, such as infrastructure spending, general economic growth, and employment opportunities within upper-income suburbs and exurban areas. These areas are often able to shirk their fiscal responsibilities to provide affordable housing and other services from which lower- income residents might benefit. Moreover, as housing becomes exclusionary and property taxes increase, social concerns diminish. How might these responses impact poverty policy? Although foundational and centered on affluence segregation, these and related questions may remain critical to the development of a greater understanding of emerging conditions of poverty concentration and economic polarization in general. 41 Conclusion and Suggestions for the Study of the New Concentrated Poverty ‘Traditional’ research concerning poverty concentration in the United States has provided a wealth of insight regarding its root causes, spatial distribution, and methods of assessment. However, much of this work is outdated and, therefore, is in need of revision. Analyses of the root causes of poverty concentration have focused on the individual prominence of class-based out-migration and historical, institutional racism, as well as their physical and social ramifications. Meanwhile, literature centered on spatial distribution has attempted to assess outcomes at and within various geographic scales, with the vast majority privileging urban areas as the primary locus. Finally, changes in the nature of concentrated poverty suggest that traditional methods of poverty concentration measurement may be unable to capture the social and physical characteristics associated with emerging concentrated poverty landscapes. What does the assessment of these interrelated aspects suggest with respect to future research? In what follows, I propose five areas that warrant closer scrutiny by those concerned with understanding this phenomenon. In doing so, I offer a new agenda for the study of poverty concentration. Conclusions and Suggestions for the Study of the New Concentrated Poverty Poverty Concentration and Globalization With some notable exceptions (Massey 1996, Castells 2000) social scientists and urban poverty scholars have focused on agents and institutions located at the nation-state level of scale in their explanations of poverty concentration. However, the increasingly complex nature of concentrated poverty suggests that causes go well-beyond those 42 operating at the level of the nation-state, requiring an investigation of the social and political-economic reordering that is occurring on a global scale. To that end, future research on should acknowledge the influence of global economic, cultural, and political transformations, thus highlighting the relationships between neoliberal welfare statism, globalization, and poverty concentration. One specific example might involve an analysis of the impacts of such transformations upon specific industrial sectors that are currently restructuring. The fact that this restructuring process is most evident within particular locales with distinct labor market characteristics may further demonstrate their role as catalysts as these places become major areas of attraction for the burgeoning working poor population predominantly comprised of Latino and Asian immigrants and, inherently, increases in the size and number of such areas of concentration. Spatial Measures of Poverty Concentration This review has advanced the notion that poverty manifests itself in multiple ways, depending on the various geographically-specific cultural, political, and economic forces at play. Traditional measures of segregation have been employed to characterize poverty conditions in monocentric regions, where poverty populations are relegated to the older, urban core. However, recent research suggests that multiple dimensions of segregation (Massey and Denton 1988) must be considered when attempting to illustrate the spatial distribution of poverty across a given region, particularly if that region is characterized by polycentric urban form (Joassart-Marcelli et al.2005). Traditional measures may, therefore, tell only part of the story as both inner-ring and outlying 43 suburban areas now contain enclaves of concentrated poverty. To that end, future research should aim to demonstrate the changing nature of poverty through the use of more developed spatial methods including GIS and other visualization techniques. One example might analyze the effects of poverty on inner-ring suburban neighborhoods that are adjacent to one another. This research would diverge from traditional studies of poverty segregation, which commonly rely on the census tract level of analysis due its relative approximation to neighborhood size and would, instead, consider the plight of poor people residing in municipal jurisdictions and counties within a metropolitan region. In view of welfare reform and devolution, these localities bear an increasing share of the social politico-administrative or fiscal responsibility associated with concentrated poverty, such as housing, welfare, health care and community policing. (Marcelli, Musso, and Wolch, 2005). Thus, the consideration of larger centers of poverty whose influence span beyond the geographic boundaries of a single census tract would advance our comprehension of emerging trends in the geographic mobility and behavior of concentrated poverty. Concentrated Poverty and Metropolitan Form Additional research might also look to establish linkages between studies of metropolitan form and concentrated poverty. Previous studies focused on metropolitan form, and the related urban sprawl/smart growth debate have been concerned with land use issues, such as brownfields redevelopment and the preservation of green space and farmland. However, this body of research should also consider the issue of poverty concentration and, more specifically, its mitigation. 44 For example, recent research has discussed the need for smart growth initiatives to be comprehensive in nature, asserting that social equity remains one of the main objectives and is central to the land use debate (Knaap 2002b). To that end, policies such as Maryland’s Live Near Your Work and Job Creation Tax Credit Programs focus on the revitalization of designated areas through increased home ownership and employment opportunities of residents. The goal of these initiatives is to mitigate urban blight and decay by improving the quality of life in the neighborhood, while at the same time restrict urban land consumption at the metropolitan fringe. These policies have been in existence for only a short while, but it will soon be time to assess their ability to achieve these dual goals (Gearin 2004). Research will be critical to understand if the perceived economic benefits associated with edge city development, can be sufficiently offset by smart growth policies that make such development more expensive while simultaneously promoting economic development, employment, and home-ownership in older urban areas to reshape metropolitan dynamics. If so, will this dynamic actually change the fortunes of the urban poor or simply generate a chain migration of poor people to less desirable places within the metropolis or beyond? Concentrated Affluence Given the vast canon of research has been devoted to poverty concentration, research on inequality has become one-sided. Meanwhile, affluence concentration represents an emerging area of scholarship. Research has demonstrated that, as a result of concentrated urban poverty, the suburbanization of homeowners has increased, as 45 more affluent residents flee to the suburban areas and, in turn, such flight leads to the social and spatial isolation of central city residents. This particular process has been furthered by numerous factors including the difficulties associated with brownfield/infill development and the suburban orientation of home-developer marketing. Future research, however, should emphasize the ways and extent to which interrelationships exist between poverty concentration and affluence concentration, focusing not only on those factors that perpetuate the already well-documented flight of the middle-class and affluent from impoverished neighborhoods, but also those factors that reinforce and, thereby, maintain conditions of segregation along class lines. One explanatory framework that could be usefully explored and tested empirically involves the investigation of the various attitudes and preferences exhibited by the affluent. For example, do fears regarding class and racial difference, crime, and other perceived behavioral tendencies associated with the inner-city play a role in the affluence concentration process, despite the fact that inner-city stereotypes may no longer characterize many areas of concentrated poverty? If so, where do they come from and what continues to drive them (e.g., local media reports driven by crime reporting, long- standing fears of people of color, including immigrants)? Moreover, what do “NIMBY” attitudes regarding the development of affordable housing, the enactment of exclusionary zoning ordinances, and a bias in favor of home rule that results in an unwillingness of the affluent to tax themselves for the betterment of their region tell us about this particular population and their desires to remain separate from the rest of urban society? 46 Increasing levels of globalization, with its concomitant political, economic, and cultural reordering, and neoliberal policies are complex and continue to result in extreme levels of geographic unevenness, exacerbating existing conditions of inequality. As a result, the face of both poverty and affluence continue to change. For example, research has revealed an increase in the levels of concentrated poverty within inner-ring suburban areas (Orfield 1997, Lucy and Phillips 2001, Jargowsky 2003). Has urban renaissance, including gentrified inner-city developments, gated enclaves, and New Urbanist urban villages - a non-traditional form of concentrated affluence - forced the poor out to inner ring suburbs? As this process of differentiation continues, traditional methods of measurement should be enhanced, and in some cases revised, in order to depict a more realistic portrait of these phenomena. Additionally, broadening our knowledge and understanding of the existing inter-relationships between the development and maintenance of privatized public spaces such as gated communities and impoverished urban areas may serve as the first step in the advancement of policies aimed at alleviating these conditions. 47 CHAPTER 2  FROM URBAN SEGREGATION TO ECONOMIC POLARIZATION:  TRENDS IN THE SPATIAL DISTRIBUTION OF POVERTY AND AFFLUENCE  CONCENTRATION IN THE UNITED STATES, 1990‐2000  Chapter Two Introduction The recent expansion of concentrated poverty into suburban areas represents the next chapter in the discourse surrounding income segregation in the United States. Historically, urban geographic studies of inequality have been one-sided, focusing on urban neighborhoods of the East Coast and Midwest, African Americans with perceived social pathologies (ex: high school drop-outs, unemployment, welfare recipients, etc.) and the general social ramifications commonly associated with their existence. Often relying upon a 40 percent threshold to denote ‘underclass areas’ marked by social dysfunction and physical dilapidation, this substantial canon of research has guided conventional thought regarding poverty, urban neighborhoods and residents, as well as poverty policy for the past twenty-five years. Meanwhile, in light of this predominant focus, the notion of affluence concentration has rarely been discussed. In recent years, however, scholars have called such conventional notions into question, suggesting that much of what we knew about both ‘poverty’ and ‘concentration’ no longer hold true (Jargowsky 2003, Kingsley and Petit 2003, Joassart- Marcelli et al. 2005, Jargowsky and Yang 2006, Strait 2006, Sessoms and Wolch 2008). Focusing on the dramatic changes in its spatial distribution, a sharp decrease in the number of underclass areas in the US, and the inadequacies of standard measures, these research efforts are provocative as they challenge such long-standing notions as the urban 48 underclass and ‘extreme poverty’ neighborhoods, and inherent assumptions about their character. To that end, they have the potential to re-shape public perception, future research, and - perhaps most importantly - the nation’s urban and regional policy debates. During the 1990s, concentrated poverty decreased considerably throughout metropolitan areas of the Midwestern and Southern regions of the United States, while increasing in the West. But perhaps the most significant modification was the suburbanization of concentrated poverty. Although previously thought of as relatively homogenous jurisdictions, during this same time-period, suburban areas became more heterogeneous, as varying levels of income and diversity accompanied population growth (Lucy and Phillips 2001). This trend was not experienced evenly, however, as some inner-ring suburbs appeared to be suffering from characteristics commonly associated with inner cities, while other suburbs continued to flourish. To that end - and given the dearth of analyses focused on concentrated affluence - numerous questions remain regarding the suburbanization of concentrated poverty both in terms of pattern of process, as well as the effect of concentrated poverty on levels of affluence segregation. During the same time-period that concentrated poverty increased within inner-suburban areas of various metropolitan regions, did levels of affluence become more concentrated? If so, which regions experienced the greatest increases/declines? What particular traits characterize these regions - high levels of immigration, changes in levels of manufacturing and services, changes in overall population levels, increasing rates of unemployment, etc.? Finally, to what degree are concentrated poverty and concentrated affluence correlated? 49 Such questions are pertinent for several reasons. First, they illustrate that the changing landscape of poverty concentration carries implications for not only urban areas - as advanced by the ‘traditional’ literature - but entire metropolitan regions as well. Additionally, while the social and economic effects of concentrated poverty have been well-documented, a systematic analysis of suburban poverty concentration and its relationship to patterns of affluence concentration has yet to be conducted. While the notion of an interdependent relationship between concentrated poverty and concentrated affluence is not new (Massey and Eggers 1993, Coulton et al. 1996, Massey 1996), these investigations do rely upon the most recent census data and, therefore, were unable to empirically analyze the impact(s) of the increasing globalization of the US economy that occurred during the 1990s, or how the suburbanization of poverty greatly influenced geographical patterns of affluence. In particular, attendant modifications in the economic, social, and demographic composition within several US city-regions - including the deindustrialization and reindustrialization of key sectors, as well the rise of the service sector and concomitant international labor migration flows - have significantly altered metropolitan labor markets, contributing not only to severe poverty, but income polarization in general. Given such transformations, during the 1990s, the suburbanization of concentrated poverty may have exacerbated existing tendencies of the affluent to segregate themselves from an increasingly diversified poverty population. To that end, an investigation of trends in the concentration of both poverty and affluence is warranted. 50 This chapter is organized as follows. First, I review previous research on poverty concentration, including historical conceptualizations as well as more recent analyses, which highlight startling changes in the topography of poverty segregation. Given these transformations, several revisions in conventional thinking are in order. Additionally, I review research on affluence concentration in the United States. These studies, although few in number, demonstrate diverging opinions on the relationship between poverty and affluence concentration. Next, I discuss the multifaceted methodological approach and specific data employed in this analysis. Following, I discuss general trends in poverty and affluence concentration within the 50 largest Metropolitan Statistical Areas of the United States between 1990 and 2000 and present the results of the statistical models employed. Finally, I discuss policy implications and offer suggestions for future research. The Changing Landscape of Poverty Concentration Conducted in the Rustbelt/Snowbelt areas of the Midwest and Northeast, early work on poverty concentration was multi-faceted and revolved around the tenuous relationship between race and class. While this substantial body of research tended to confirm a dramatic increase in concentrated urban poverty during the 1970s and 1980s and ‘concentration’, characterized by simultaneous increases in the number of poor people residing in poor neighborhoods, it also portrayed African American neighborhoods as the primary geographic locus within which these conditions occurred. Poverty scholars, however, expressed diverging ideas regarding the central catalysts involved, including deindustrialization and the attendant loss of manufacturing jobs, a history of racism in residential housing markets, and metropolitan inequalities associated 51 with general economic change (Wilson 1987, Massey and Denton 1993, Segrue 1997; Jargowsky 1997). Despite the provocative nature of these debates, the causes of poverty concentration were not mutually exclusive. Instead, the lack of local employment opportunities, combined with the exodus of upwardly mobile African Americans to suburban communities as racial restrictions in residential housing markets eased, resulted in deepening intrametropolitan disparities, economic and social disinvestment in central cities, and blight, decay and concentrated poverty in many older urban neighborhoods. Moreover, the strategic location of public housing within such areas worked to exacerbate levels of poverty concentration among low-income African-Americans (Goetz 2001). The 1990s, however, saw the emergence of several factors which combined to combat the effects of institutional racism, as well as levels of concentrated poverty throughout the United States. A bolstered U.S. economy, reductions in unemployment, the expansion of the Earned Income Tax Credit (EITC), and a number of federal initiatives - the Hope VI, Moving to Opportunity (MTO), and Portfolio Reengineering programs - were implemented with the goal of mitigating both the concentration of public housing and poverty within urban neighborhoods (Goetz 2000, 2003; Jargowsky and Yang 2006). Indeed, recent research has revealed that during this time-period, the face of poverty was significantly altered, as poor areas became differentiated. In stark contrast to its dramatic increase during the 1970s and 1980s, concentrated poverty decreased notably in urban areas of the Midwest and Northeast, while increasing significantly within inner- 52 suburban areas and, in particular, the West (Jargowsky 2003). In light of these findings, more recent research has expanded the discourse on poverty concentration, breaking from ‘traditional’ studies in the areas of conceptualization, geographic scale and focus, and measurement. Jargowsky and Yang’s (2006) investigation of the contemporary ‘state of the underclass 3 ’ revealed that “fewer neighborhoods now resemble the depressing descriptions of the inner city that were commonplace in journalistic and scholarly accounts of previous years” (p. 67). These findings demonstrate that the changes in concentrated poverty neighborhoods are two-fold. Not only have such neighborhoods decreased in number, but they are not necessarily disproportionately home to residents with dysfunctional behaviors or social ills either. Meanwhile, research by Joassart- Marcelli et al. (2005) illustrated the diverse and increasingly complex nature of the emerging landscape of poverty segregation. Focused on the southern California region, this research asserted that concentration is but one aspect of segregation, and that additional facets, including evenness, clustering, as well as isolation and exposure, matter to our understanding of this particular phenomenon. Again, diverging from historical research on concentrated poverty, Strait (2006) emphasized the need to consider all racial groups in forthcoming analyses of poverty concentration. The call for more inclusive depictions of the social context of poverty concentration represents a fundamental and extremely salient change in the discourse surrounding poverty concentration, which has focused primarily on African Americans. 3 As defined by Ricketts and Sawhill (1988) 53 Finally, as discussed later in this dissertation, tradition poverty concentration metrics, such as the 40 percent threshold for defining extreme poverty or concentrated poverty neighborhoods, may not be appropriate given the increasingly variegated landscape of metropolitan poverty. The geographic setting of southern California and, in particular, Los Angeles represents another significant departure from historical research, which focused on the Midwest and East Coast. However, characterized by globalization, racial/ethnic diversity, as well as extreme levels of social and economic fragmentation, it represents the “signal case of the American urban future” (Strait 2006, p. 73) and, therefore, serves as an ideal locale in which to analyze burgeoning conditions of economic polarization, as well as associated catalysts. Conceptualizing Affluence Concentration Analyses of income-based segregation concur that poverty and affluence have become increasingly concentrated since the 1970s (Massey and Eggers 1993, Jargowsky 1996, Fischer 2003, Lee and Marlay 2007). However, in sharp contrast to the extensive canon of research devoted to poverty concentration, little research has focused on affluence concentration, let alone as its catalysts, spatial distribution, and social ramifications. Several reasons in particular explain this paucity. First, the existence and further perpetuation of long-standing notions such as the ‘American Dream’ demonstrate the reverence that wealth and fiscal integrity have been afforded in the United States. Along these lines, affluence and affluence concentration in particular carry with them 54 notions of economic stability, social well-being, and general success and good fortune, which imply that all is right in the world and no research is actually needed (Shaw 1997). Moreover, from an empirical standpoint, analyzing affluence concentration has been and remains an arduous task, due to the lack of data available. Unlike poverty, there are no thresholds for affluence provided by the U.S. Census, nor does a federally defined benchmark for affluence exist. To that end, previous research has often relied upon several quantitative techniques in order to derive a suitable definition, including the use of family-income designations (e.g. multiplying the median household income for a family of four by a given multiplier - 2, 3, 4, etc.) and the utilization of poverty threshold multipliers (e.g. income levels that are equal to 300%, 400%, 500%, etc. of the poverty threshold) to estimate levels of affluence. Therefore, depictions of affluence have, in reality, amounted to nothing more than best estimations, while accurate portrayals of the affluent and their places of residence have remained elusive. Finally, research on affluence concentration and, in particular, its role in creating and maintaining conditions of inequality have been constrained by the common doctrine that individuals are responsible for their own socioeconomic circumstances. To that end, affluence as well as its recompenses are earned and, therefore, justified. When viewed in tandem with poverty concentration, however, the negative aspects associated with affluence concentration become more evident. Chief among these is the unequal distribution of resources, such as the quality of housing, employment opportunities, schools, as well as amenities and municipal services. Although affluent areas are often depicted as homogeneous, idyllic spaces of social cohesion and 55 functionality (Jackson 1985), recent changes in the spatial distribution of concentrated poverty and its suburbanization in particular may have led such areas to experience significant shifts in their economic and demographic compositions. Therefore, suburbs and exurbs are deserving of our attention as they have arguably become the geographic locales most impacted by burgeoning conditions of economic polarization. Although limited in number, previous analyses of concentrated affluence have centered on the largest U.S. metropolitan areas and demonstrated two broad themes, including (1) an emphasis on the relevance and long-standing nature of this particular phenomenon, as well as its relationship to poverty concentration (Massey and Eggers 1993, Massey 1996, Coulton et al 1996), and (2) changes in the geography (i.e. regional dimensions) of affluence concentration (Shaw 1997, St. John 2002, Lee and Marlay 2007). While the vast majority of these studies have been conducted by sociologists, geographers have made noteworthy contributions as well. Although their foci vary, these analyses have relied upon various measurement strategies to provide insight regarding the catalysts for affluence concentration, while expressing diverging opinions on the presence of a mutually supportive relationship between it and poverty concentration. In the paragraphs that follow, I review these studies and - in view of recent changes in the spatial distribution of concentrated poverty - emphasize the pressing need to revise discussions of inequality such that they become more inclusive and take into consideration the relevance of affluence concentration, its detrimental effects, and its role in both the creation and maintenance of such conditions. 56 The first analysis of concentrated affluence was conducted by sociologists Douglas Massey and Mitchell Eggers (1993), who boldly posited that the spatial concentration of affluence was greater and more dispersed than the concentration of poverty during the 1970s. More specifically, they argued that [t]he continued suburbanization of the middle class during the 1970’s combined with the growth of new business, industrial, and commercial zones outside of central cities, may have increased segregation by income and given rise to a spatial concentration of affluence, yielding an urban spatial structure increasingly divided along class lines” (p. 300). These researchers concluded that (1) increasing levels of not only poverty, but economic polarization were common within many of the nation’s largest metropolitan areas, such as Chicago, Los Angeles, Detroit and Philadelphia; (2) increases in the incomes of affluent families occurred, particularly within the Sunbelt region (Houston, Phoenix, Tampa, etc.), where energy production was the primary driver of the local economy and; (3) a substantial decrease in income within the New York metro-area, where lower middle class and poor populations increased significantly, and the number of affluent and upper middle class families decreased. These findings are particularly insightful considering that they were presented in the midst of the urban underclass debate, during which poverty concentration, as well as its race and class-based catalysts represented the sole foci of research on income inequality. To that end, they demonstrate that both affluence concentration and broader conditions of economic polarization are not new phenomena, but instead have been steadily increasing for over thirty years. Finally, and although sociological in nature, these findings also demonstrate that - much like poverty concentration - levels of 57 affluence concentration vary depending on local economic, cultural, and political factors (e.g. energy production in the Sunbelt, immigration in New York) - thus emphasizing its spatial nature. Building on this work, Massey (1996) warned that polarized spatial concentrations would bring about the dawning of a “…new ecology of inequality” (p. 410), characterized by detrimental effects such as the exacerbation of urban social dilemmas, including unemployment, crime, drug abuse and violence, motivating the affluent to continue their outward migration, and perpetuating increased levels of sprawl and suburbanization. In particular, this non-empirical work emphasized both the role and varied effects of globalization and attendant economic restructuring - often characterized by computer-based production, the expansion of globalized economic networks, and the fractured nature of consumer markets - in the production of economic polarization. This work and its corresponding assertions are provocative as well. In detailing some of the specific catalysts associated with economic polarization and, perhaps more importantly its negative outcomes, it provided a way to understand the process through which poverty and affluence concentration work in unison to exacerbate conditions of inequality. In doing so, this work legitimized the study of affluence concentration, while challenging the prevailing sentiment that the systematic migration of the affluent from the poor (e.g. suburbanization) represents the natural progression for individuals and families that are upwardly mobile. Instead, this work conveyed the notion that this process may actually be problematic, as the same process that leads to the creation and maintenance of 58 affluence concentration, intensifies the factors that work to produce and reinforce poverty concentration. Meanwhile, a multifaceted effort by geographers Coulton et al. (1996) investigated spatial patterns of poverty and affluence concentration and considered the roles of race and city/suburban advantage as catalysts, as well as levels of interdependence within the 100 largest metro-areas of the U.S. Their analysis revealed that: (1) the greatest separation between the poor and affluent occurred within metro- areas that were also characterized by high levels of racial/ethnic segregation; (2) cities with lower levels of racial/ethnic segregation were characterized by lower levels of poverty concentration and varying levels of affluence concentration; and (3) metro-areas characterized by high levels of affluence concentration demonstrated low levels of racial/ethnic segregation, but varying levels of economic segregation within racial/ethnic groups. This particular study provided further insight into the catalysts for affluence concentration, including the limited residential choices of racial/ethnic minorities, as well as the construction of homogeneously expensive housing developments, and the suburbanization of jobs and concomitant out-migration of middle and upper-class residents. Perhaps more importantly, however, and in contrast to the assertions of Massey (1996), they asserted that only a small number of cities demonstrated extreme levels of both poverty and affluence concentration, and that no evidence of an interdependent relationship existed. 59 While the notion that poverty concentration is strongly correlated with racial/ethnic segregation is congruent with traditional research (ex: African Americans in urban neighborhoods per Wilson 1987, Massey and Denton 1993), it should be no surprise that similar conditions hold true for affluence concentration, given that its existence is likewise strongly correlated with wealthy Whites living in suburban/exurban areas. However, while the relationship between varying levels of affluence concentration within racially homogenous areas is expected, its relationship to varying levels of in- group economic segregation may be the result of a combination of factors. These might include relaxed housing restrictions and affirmative action policies have led to increased levels of upward mobility among some historically oppressed minority groups (ex: the emergence of the Black Middle Class). Additionally, research has revealed that some immigrant groups (namely wealthy Asians) have been able to utilize their transnational capital to relocate to suburban areas of the United States (Li 1999, 2000). In this way, they differ from other immigrant populations, who often settle within urban areas upon arriving in the United States. Building upon these studies, additional research has focused on the geography of affluence concentration. In addition to providing greater insight regarding potential catalysts, these analyses demonstrate that - much like poverty concentration - conventional wisdom regarding the spatial distribution of concentrated affluence no longer holds true. Research by geographer Wendy Shaw (1997) further depicted affluence concentration as a phenomenon that possesses its own unique geography. Focusing at the 60 county level, her analysis confirmed that, while the affluent in the United States are predominantly located within metropolitan areas, only a handful of such areas are home to spatial concentrations of affluence. With the exception of a large region in the Northeast (Megalopolis), these metro-areas, for the most part, demonstrated geographic diversity (as they were dispersed throughout the U.S). To that end, she argued that spatial concentrations of affluence are derived from the combination of available economic opportunities within metropolitan areas, but their presence within specific counties demonstrates that personal choices made by affluent individuals to segregate themselves from the working-class and high-densities also play a prominent role. Although focused on the various strategies and associated complexities involved with the measurement of affluence, research by Lee and Marlay (2007) emphasized both the geographic dispersal of affluent neighborhoods, as well as their concentration within suburbs of a small number of larger U.S. metro-areas. In doing so, they confirmed the findings of Shaw (1997). Finally, in another study more focused solely on affluence concentration, St. John (2002), hypothesized that increased levels of concentrated affluence should be present in large metro-areas where the employment base reflects economic restructuring associated with global finance. Examining levels of affluence concentration within the largest U.S. metropolitan areas, as well as variations among African Americans and Whites, his findings revealed that the specific economic characteristics of metro-areas played a greater role in determining the presence and levels of affluence concentration than income inequality. Moreover, from a regional perspective, metro-areas of the Northeast 61 displayed lower levels of concentrated affluence due largely to the lack of economically homogenous dwelling areas. In contrast, metro-areas in the Midwest and South demonstrated higher rates of concentrated affluence than the West. Lastly, while racial residential segregation was highlighted as a factor in the rates of concentrated affluence for both African Americans and Whites, the strongest predictor was mean household income. While this research reinforces the role of globalization and its role in promoting geographic unevenness as a primary catalyst in the concentration of affluence, similar to Shaw (1997), it also stands in contrast to previous conceptualizations of affluence concentration by emphasizing significant changes in its spatial distribution. In summary, despite its common characterization as the polar opposite of poverty concentration, previous analyses of affluence concentration demonstrate that these phenomena may share important similarities. Although measurement strategies and geographic scales have varied, scholars have tended to implicate globalization and attendant economic restructuring as primary catalysts for both the increasing complexity and changing spatial distribution of poverty concentration. Meanwhile, the same catalysts have induced changes in the spatial distribution of affluence concentration, which is no longer confined to the Northeast, but has instead become geographically dispersed throughout the U.S., albeit in a small number of metro-areas. Such factors as historical racial segregation and continued white privilege in the residential housing market, the suburbanization of employment opportunities, and inherent metropolitan income inequality have exacerbated this condition resulting in increasing levels of severe geographic unevenness. In chronicling both the historical as well as the more recent 62 conceptualizations of poverty and affluence concentration, the notable transition that poverty concentration has undergone over the past twenty five years is made evident. Once a phenomenon that was largely implicated in hampering the social development and life chances urban Blacks while threatening the property values and well-established social order of suburban Whites, concentrated poverty has morphed into a regional phenomenon that - given its recent outward expansion - may stand to directly impact Whites in suburban/exurban areas by forcing them to retreat further into gated communities and other common interest districts. Data and Methodology The methodology utilized in this analysis is multifaceted and relies upon Geolytics software to attain normalized census tract data from the 1990 and 2000 Census of Population and Housing, as well as spatial indices of segregation to investigate trends in the suburbanization of concentrated poverty and concentrated affluence. Additionally, STATA statistical software was utilized to construct statistical models to better explain the interplay between those variables responsible for the varying economic trajectories of the selected regions. First, the 50 largest Metropolitan Statistical Areas of the US are selected based on their 1990 population levels. The metro-scale has been utilized in similar analyses of both poverty and affluence concentration and is sufficient to provide both regional diversity and robust statistical findings. Next, I investigate whether or not, during the 1990s, the suburbanization of concentrated poverty within these metro-areas was paralleled by increasing levels of affluence concentration. The acquisition of normalized data is, 63 therefore, critical to this aspect of the analysis, as it allows for data comparisons to be made over time. For example, it can be assumed that as metro-areas increase in size, geographic boundaries change (new census tracts are added) in order to accommodate population growth or shifts. In response, normalized data allow for changes that have occurred over time by adjusting and weighting such data to account for such geographic changes. Consistent with previous studies, this research utilizes the 40 percent threshold to define ‘concentration’ (the ratio of poor people residing in extreme poverty census tracts) for both 1990 and 2000. Additionally, due to the longstanding debate surrounding the inadequacy of the official poverty threshold 4 , which is unable to distinguish between regional variations in poverty associated with costs of living differentials (especially housing costs), this research relies upon an alternative threshold based on 150 percent of the official poverty benchmark to provide a more accurate picture of the poverty population throughout the U.S. The application of this alternative threshold is warranted given inflation as well as the increased cost of living incurred by residents within a number of larger metro-areas throughout the US such as New York, Chicago, San Francisco, Los Angeles, and San Diego. While those associated with transportation, utilities, groceries, and miscellaneous goods and services often play a role, often the most salient of these is extraordinarily high housing costs (see American Chamber of Commerce Research Association 2004). 4 see Orchansky 1978; Levitan and Shapiro 1987; O’Hare et al. 1990; Ruggles 1990, 1991; Schwarz and Volgy 1992; Fisher 1992, 1992; Citro and Michael 1995; Joassart-Marcelli and Wagle 2005 64 Utilizing this strategy, the original poverty threshold (often referred to as 100 percent of poverty) is increased by 50 percent. This increased threshold, thus, captures those individuals whose income would otherwise render them on the margin or slightly above the poverty line - and, therefore “not poor” - and allows them to be included in the poverty population. For example, if the official poverty threshold (100 percent) in 1999 for an individual was $8,500, the adjusted threshold (150 percent) would be $12,750. This follows the practice of other researchers, as well as federal and state program guidelines (Joassart-Marcelli and Wagle 2005; Joassart-Marcelli, Musso and Wolch, 2005; Montgomery et al. 1996; U.S. Department of Education 2006; Emergency Home Energy Crisis Assistance for the Elderly Program 2006; Partners for a Prosperous Athens 2006; Northern Illinois University Regional Development Institute 2006). Additionally, the investigation of trends in the suburbanization of concentrated poverty requires a definition of suburbs (or census tracts that lie within suburbs). To that end, this research borrows from Joassart-Marcelli et al. (2005) and defines suburbs as those tracts in which the proportion of the housing stock was built after 1960 above the regional average. The application of this formula to the selected 50 metro-areas allows for the identification of concentrated poverty tracts in 1990 that were located within suburbs. Once suburban concentrated poverty tracts are delineated, the concentration index was employed to provide tract-level rates of concentrated poverty for the year 2000. Together, these calculations allow for the analysis of general increases/decreases in the rates of suburban concentrated poverty between 1990 and 2000. Additionally, tract- 65 level rates were aggregated to the MSA level so that regional comparisons could be made. Next, given the absence of a suitable definition, I define affluent households as those with income levels that are five times the poverty rate or more for a family of four in 1989 (per 1990 Census data) and 1999 (per 2000 Census data), yielding cutoff levels of income above which households are considered affluent for the years 1990 ($63,370) and 2000 ($85,145), respectively. The US Census provides household income data by categories only (for ex: $10,000 - $14,999), making it impossible to attain the exact number of households per tract. To that end, this analysis employs the technique utilized by Strait (2002) in order to calculate the total number of affluent households in each tract within each of the selected MSAs. For example, the 2000 cutoff level of $85,145 falls within the category of $75,000 - $99,999. The linear interpolation assumes that households are distributed evenly on the income continuum. Therefore, given the $25,000 range in that particular category, there should be (99,999 – 85,145)/ 25,000 or 59% of the households in that category have income levels above $85,145. To this number I also add the households in the remaining higher income categories ($100K-124,999K, $125K- 149,999K, $150K-199,999K, and $200K+) in order to obtain an estimate of the total number of affluent households. Again, to denote ‘concentration’, the 40 percent threshold was utilized. Those census tracts in which 40 percent of households had income levels greater than the specified cutoff levels, therefore, constituted neighborhoods of concentrated affluence in 1990 and 2000. Similar to the analysis of poverty concentration, tract-levels of affluence 66 concentration levels were then aggregated to the MSA level to allow for regional comparisons. Following, three matrices were constructed (Figures 2.1 – 2.3) in order to better depict the regional changes in levels of poverty concentration, affluence concentration, and changes in both during the 1990s. In the matrices, each metro-area was grouped into one of four quadrants based upon their 2000 concentrated poverty/concentrated affluence rate (and whether it was above or below the US median) and direction of rate change (growth or decline) and the direction of rate change for both concentrated poverty/concentrated affluence that occurred between 1990 and 2000. Thus, each quadrant represents a different economic condition and economic trajectory: I. Below average (low) and decreasing rate of concentrated poverty (Figure 2.1), concentrated affluence (Figure 2.2), or the change in both (Figure 2.3); II. Above average (high) but decreasing rate of concentrated poverty, concentrated affluence, or the change in both; III. Above average (high) and increasing rate of concentrated poverty, concentrated affluence, or the change in both; and IV. Below average (low) but increasing rate of concentrated poverty, concentrated affluence, or the change in both. 67 68 69 70 Finally, to identify and better understand those factors that have contributed to recent trends as well as regional variations in poverty concentration and suburban poverty concentration within the 50 largest Metropolitan Statistical Areas of the United States, as well as their relationship to affluence concentration, I utilize data from the 1990 and 2000 U.S. Census of Population and Housing and STATA statistical software to construct cross-sectional multivariate regression models. These models analyze the change in poverty concentration and suburban poverty concentration levels between 1990 and 2000 against various demographic, economic, and labor market characteristics of the selected Metropolitan Statistical Areas. The regression models take the following forms: ΔC i = α + β D i + γ E i + δ L i + ε In this particular instance, ΔC i measures the changes in urban or suburban poverty concentration in tract I, α is the constant term, β, γ, δ are vectors of coefficients, D, E, and L are vectors of demographic, economic, and labor market variables, and ε is the error term. Table 2.1a and Table 2.1b on the following page lists the independent variables and data sources. 71 Table 2.1a: Two Stage Least Squares Regression Analysis - Variables and Descriptions Abbreviation Dependent Variables Measurement Data Source % Concentrated Poverty Percentage of Concentrated Poverty Percent of poor population in MSA living in extreme poverty neighborhoods Census of Population and Housing 1990 and 2000, STF3 % Suburban Concentrated Poverty Percentage of Suburban Concentrated Poverty Percent of poor population in MSA living in extreme poverty neighborhoods in suburbs Census of Population and Housing 1990 and 2000, STF3 Abbreviation Independent Variables Measurement Data Source % Black Percentage of Blacks Percent of the MSA population - Black Census of Population and Housing 1990 and 2000, STF3 % Latino Percentage of Latinos Percent of the MSA population - Latinos Census of Population and Housing 1990 and 2000, STF3 % Asian Percentage of Asians Percent of the MSA population - Asian % Other Percentage of Other Percent of the MSA population - Some other race alone, Native Hawaiian, American Indian, Two or more races Census of Population and Housing 1990 and 2000, STF3 % Foreign Born Percentage of Foreign Born Population Percent of the MSA population born outside of the US Census of Population and Housing 1990 and 2000, STF3 % Manufacturing Percentage Employed in Manufacturing Percent of the MSA population - M/F 16 yrs and older in the labor force - that is employed in Manufacturing Census of Population and Housing 1990 and 2000, STF3 % Services Percentage Employed in Services Percent of the MSA population - M/F 16 yrs and older in the labor force - that is employed in Service occupations Census of Population and Housing 1990 and 2000, STF3 % Unemployment Percentage of Unemployed Percent of the MSA population - M/F 16 yrs and older in the labor force - that is unemployed Census of Population and Housing 1990 and 2000, STF3 Abbreviation Independent Variable Measurement Data Source % Home Ownership Percentage of Home Owners Percent of the MSA population residing in owner- occupied dwellings Census of Population and Housing 1990 and 2000, STF3 % Poverty Percentage of Poor Residents Percent of the MSA population living below the of the poverty line (150%) Census of Population and Housing 1990 and 2000, STF3 Total Population (Log) Total MSA Population Total number of people within selected MSAs Census of Population and Housing 1990 and 2000, STF3 % Concentrated Affluence Percentage of Affluent Households Percent of affluent households located in affluent census tracts (aggregated to MSA level) Census of Population and Housing 1990 and 2000, STF3 West Regional Dummy Variable MSAs within the Western area of the US Census of Population and Housing 1990 and 2000, STF3 South Regional Dummy Variable MSAs within the Southern area of the US Census of Population and Housing 1990 and 2000, STF3 Midwest Regional Dummy Variable MSAs within the Midwestern area of the US Census of Population and Housing 1990 and 2000, STF3 % FB 10 Yrs Percentage of Foreign Born Percent of population who was born outside of the US and arrived in the US within the previous ten years Census of Population and Housing 1990 and 2000, STF3 % FB 10-20 Yrs Percentage of Foreign Born Percent of population who was born outside of the US and arrived in the US between ten and twenty years ago Census of Population and Housing 1990 and 2000, STF3 % FB 20+ Yrs Percentage of Foreign Born Percent of population who was born outside of the US and arrived in the US twenty years ago or more Census of Population and Housing 1990 and 2000, STF3 Predicted Conc. Affl. Predicted Value of Concentrated Affluence The predicted value of the regression equation containing the problematic causal variable (dependent) and exogenous instrumental variables (independent) Census of Population and Housing 1990 and 2000, STF3 TABLE 2.1a: REGRESSION VARIABLES AND DESCRIPTIONS 72 Table 2.1b: Two Stage Least Squares Regression Analysis - Instrumental Variables and Descriptions (Affluence Cleansing) Abbreviation Independent Variable Measurement Data Source 3+ VEH Percentage of Housing units with 3 or More Vehicles Available Percentage of owned and rented housing units with 3 or more vehicles available Census of Population and Housing 1990 and 2000, STF3 1865 Percent Age 18-65 Percentage of males and females age 18-65 Census of Population and Housing 1990 and 2000, STF3 EMP Percent Employed in Managerial, Professional, and Technical Occupations Employed persons 16 years and older employed in Managerial, Professional, and Technical Occupations Census of Population and Housing 1990 and 2000, STF3 GRPR Percent with Graduate and Professional Degrees Percentage of Population 25 years and older with Graduate and Professional Degrees Census of Population and Housing 1990 and 2000, STF3 IDNR Percent Receiving Interest, Rent, and Dividends Percentage of Households with supplementary income from Interest, Rent, and Dividends Census of Population and Housing 1990 and 2000, STF3 MARR Percent Married Percentage of Married-Couple Families Census of Population and Housing 1990 and 2000, STF3 MHV Median Housing Value Median Value of Single-Family Homes Census of Population and Housing 1990 and 2000, STF3 MINC Median Income Median Household Income Census of Population and Housing 1990 and 2000, STF3 TABLE 2.1b: REGRESSION VARIABLES AND DESCRIPTIONS: Affluence Cleansing 73 More specifically, given the complex nature of the relationship between poverty and affluence concentration, this research utilizes a Two-Stage Least Squares Regression (2SLS). This particular method of analysis is commonly utilized to extend regression models in which the assumption of recursivity – common to Ordinary Least Squares (OLS) regressions - stands to be violated. Here, the disturbance term of the dependent variable is assumed to be correlated with the cause(s) of the independent variable(s). In response, in the first stage of the regression analysis, new endogenous variables are created to substitute for the original ones. Then, in the second stage, the standard OLS regression analysis is computed using the newly created variables. In this case, many of the independent variables utilized in the base model (Percent Unemployment, Percent Homeownership, Percent Poverty, etc.) could be highly correlated with Concentrated Affluence (another independent variable) as well as Concentrated Poverty (the dependent variable). This indirect causal relationship severely hinders the ability to discern the true relationship between the two variables. Therefore, the variable Concentrated Affluence is treated as a problematic causal variable and is utilized as the dependent variable in the initial stage of the regression analysis. Also included in this stage are instrumental variables. These variables are exogenous and have a direct or indirect relationship to the dependent variable Concentrated Affluence, but no direct causal path to the dependent variable in the base model, Concentrated Poverty. The instrumental variables utilized, as well as their data sources, are also listed Table 2.1. The resulting predicted value of this regression equation then serves to generate values for the new independent variable (Predicted 74 Concentrated Affluence), replacing the problematic causal variable (Concentrated Affluence) in the second stage (OLS model) of the regression analysis. Finally, to better articulate the specific effect(s) that both place and immigration have on the dependent variable, each of the OLS Concentrated Poverty and Suburban Concentrated Poverty models for both 1990 and 2000 contain five iterations. The first contains the basic regression model (including race, socio-economic, employment, and population variables), while the second builds upon the basic model by articulating the effects of regional dummy variables. The final three iterations build on the first two by illustrating the effects of three immigration cohorts (immigrants that arrived within the previous ten years, immigrants that arrived between ten and twenty years ago, and immigrants that arrived more than twenty years ago). In the models, the log of the variable Total Population is employed so that the resulting coefficients represent the effect of a percent change in population, rather than a numerical change. Finally, once correlation matrices were reviewed for evidence of multicollinearity, independent variables in the models with p-values of less than 0.2 were removed so that those with parsimonious p-values might increase in significance. Exploring Regional Trends in Poverty and Affluence Concentration in the US, 1990-2000 In this section, I present findings from the analysis of poverty and affluence concentration within the selected Metropolitan Statistical Areas. First, the selected MSAs were divided into quadrants based on their geographic locations - Northeast/Midwest, Southeast, Northwest, and West/Southwest – so that regional trends could be observed. In 75 particular, I report on levels of concentration as well as rate changes. These results are listed in Table 2.2. Following the presentation of intrametropolitan trends, I utilize the economic polarization matrix to characterize metro-areas based upon the changes in their concentrated poverty and concentrated affluence rates during the 1990s. 76 Table 2.2 – Poverty and Affluence Concentration Rates and Rate Changes for the 50 Largest Metropolitan Statistical Areas, 1990 and 2000 NORTHEAST/MIDWEST CPOV90 CPOV00 %CH CAFF90 CAFF00 %CH New York, NY 0.35 0.37 2.0% 0.40 0.45 5.0% Chicago, IL 0.35 0.29 -6.0% 0.28 0.36 8.0% Washington D.C. 0.19 0.17 -2.0% 0.46 0.49 3.0% Philadelphia, PA 0.33 0.34 1.0% 0.26 0.33 7.0% Boston, MA 0.16 0.15 -1.0% 0.27 0.35 8.0% Detroit, MI 0.44 0.35 -9.0% 0.27 0.34 7.0% Cleveland, OH 0.37 0.33 -4.0% 0.17 0.19 2.0% Minneapolis, MN 0.20 0.17 -3.0% 0.20 0.34 14.0% St. Louis, MO 0.32 0.25 -7.0% 0.18 0.25 7.0% Pittsburgh, PA 0.20 0.16 -4.0% 0.15 0.14 -1.0% Cincinnati, OH 0.27 0.23 -4.0% 0.17 0.21 4.0% Milwaukee, WI 0.46 0.40 -6.0% 0.17 0.24 7.0% Kansas City, MO 0.27 0.20 -7.0% 0.18 0.29 11.0% Indianapolis, IN 0.25 0.18 -7.0% 0.15 0.25 10.0% Hartford, CT 0.24 0.29 5.0% 0.33 0.32 -1.0% Buffalo, NY 0.36 0.34 -2.0% 0.08 0.10 2.0% Providence, RI 0.16 0.31 15.0% 0.06 0.09 3.0% Rochester, NY 0.24 0.29 5.0% 0.17 0.17 0.0% Oklahoma City, OK 0.25 0.26 1.0% 0.07 0.10 3.0% Dayton, OH 0.31 0.20 -11.0% 0.09 0.10 1.0% Grand Rapids, MI 0.27 0.16 -11.0% 0.09 0.13 4.0% Albany, NY 0.13 0.21 8.0% 0.12 0.08 -4.0% SOUTHEAST Dallas, TX 0.21 0.28 7.0% 0.27 0.37 10.0% Houston, TX 0.38 0.36 -2.0% 0.29 0.36 7.0% Miami, FL 0.33 0.34 1.0% 0.14 0.24 10.0% Atlanta, GA 0.23 0.17 -6.0% 0.26 0.37 11.0% Tampa, FL 0.19 0.15 -4.0% 0.03 0.13 10.0% Norfolk, VA 0.22 0.21 -1.0% 0.06 0.11 5.0% San Antonio, TX 0.57 0.40 -17.0% 0.14 0.23 9.0% New Orleans, LA 0.52 0.43 -9.0% 0.09 0.13 4.0% Orlando, FL 0.14 0.13 -1.0% 0.11 0.19 8.0% Charlotte, NC 0.15 0.11 -4.0% 0.13 0.30 17.0% Greensboro, NC 0.13 0.16 3.0% 0.11 0.12 1.0% 77 Table 2.2 (Continued) SOUTHEAST (Continued) CPOV90 CPOV00 %CH CAFF90 CAFF00 %CH Memphis, TN 0.52 0.42 -10.0% 0.24 0.26 2.0% Nashville, TN 0.20 0.14 -6.0% 0.18 0.25 7.0% Louisville, KY 0.32 0.22 -10.0% 0.15 0.21 6.0% Jacksonville, FL 0.22 0.15 -7.0% 0.07 0.31 24.0% Richmond, VA 0.25 0.24 -1.0% 0.16 0.27 11.0% West Palm Beach, FL 0.22 0.22 0.0% 0.27 0.29 2.0% Raleigh-Durham- Charlotte, NC 0.15 0.12 -3.0% 0.16 0.27 11.0% SOUTHWEST/WEST Los Angeles, CA 0.36 0.43 7.0% 0.37 0.37 0.0% San Francisco, CA 0.15 0.12 -3.0% 0.41 0.56 15.0% San Diego, CA 0.25 0.30 5.0% 0.28 0.32 4.0% Phoenix, AZ 0.34 0.33 -1.0% 0.21 0.29 8.0% Sacramento, CA 0.24 0.29 5.0% 0.10 0.22 12.0% Salt Lake City, UT 0.13 0.11 -2.0% 0.14 0.22 8.0% Las Vegas, NV 0.19 0.21 2.0% 0.04 0.11 7.0% Denver, CO 0.23 0.19 -4.0% 0.22 0.40 18.0% NORTHWEST Seattle, WA 0.09 0.06 -3.0% 0.15 0.22 7.0% Portland, OR 0.08 0.09 1.0% 0.06 0.15 9.0% Northeast/Midwest This particular grouping of 22 metropolitan areas contains many of the cities that have been the subjects of historical literature on concentrated urban poverty, including Chicago, Detroit, Philadelphia, New York, and Boston. Consistent with the assertions of Jargowsky (2003) and Kingsley and Petit (2003), the vast majority of these areas (15) experienced decreases in their rates of concentrated poverty during the 1990s. In particular, those experiencing the greatest decreases were Dayton, Ohio and Grand 78 Rapids, Michigan (-11%), Detroit, Michigan (-9%), and Indianapolis, Indiana, Kansas City, Missouri, and St. Louis, Missouri (-7%). Meanwhile, in contrast to the general trend of decreasing poverty concentration in this particular region, a small number of metro areas (7) demonstrated increases in their rates of concentrated poverty. In particular, Providence, Rhode Island, demonstrated an increase of 15% - the greatest in the entire sample of metro areas. Additionally, notable increases were present in Albany, New York (8%), as well as Hartford, Connecticut and Rochester, New York (5%). In stark contrast to the general trend of decreasing poverty concentration, affluence concentration was more prevalent and even more pronounced within metro areas of the Northeast and Midwest. In particular, 19 of the 22 metro areas experienced increases. The most notable increases were present in Minneapolis (14%), Kansas City and Indianapolis (11%), Boston and Chicago (8%), and Philadelphia, Detroit, St. Louis, and Milwaukee (7%). Meanwhile, although few in number (3), some metro areas experienced decreasing rates of affluence concentration, including Albany (-4%), as well as Hartford and Pittsburgh (-1%). Southeast The aforementioned trend continued in the Southeast region, where both decreases in concentrated poverty and increases in concentrated affluence were even more pronounced. Of the eighteen metropolitan areas that comprised this particular grouping, fourteen demonstrated decreases in concentrated poverty during the 1990s. Moreover, these decreases were greater (by percentage) than those in the 79 Northeast/Midwest region. Those experiencing significant decreases in poverty concentration were San Antonio (17%) – which was the largest decrease in the entire sample of metro areas, Memphis and Louisville (10%), and New Orleans (9%). Three metro-areas, however, demonstrated increases in their rates of concentrated poverty, including Dallas (7%), Greensboro (3%), and Miami (1%). Also within this geographic grouping, rates of concentrated affluence were significantly greater than those in the Northeast/Midwest, as all of the 18 metro-areas experienced increases. Those experiencing the most notable increases included Jacksonville (24%), Charlotte (17%), Richmond, Raleigh-Durham-Chapel Hill and Atlanta (11%), and Dallas, Tampa, and Miami (10%). Southwest/West Again, consistent with the findings of Jargowsky (2003), levels of concentrated poverty increased significantly in the West. Of the eight metro-areas that comprised this particular grouping, half demonstrated increases in their levels of concentrated poverty during the 1990s. These included Los Angeles (7%), San Diego (5%), Sacramento (5%), and Las Vegas (2%). Meanwhile, the remaining metro-areas demonstrated decreases in their rates of concentrated poverty, including Denver (4%), San Francisco (3%), Salt Lake City (2%), and Phoenix (1%). Increases in the levels of concentrated affluence were once again notable and occurred within 7 of the 8 metro-areas. Surprisingly, Los Angeles was the only metro- area that demonstrated no change in its level of concentrated affluence. Denver, Colorado demonstrated the greatest increase (18%), followed by San Francisco, 80 California demonstrated the second largest increase in this particular grouping (15%), but the highest level of affluence concentration in the entire sample of MSAs (.56). Meanwhile, Sacramento, California demonstrated the third largest increase (12%). Northwest This particular grouping consisted of only two metro-areas - Seattle, Washington and Portland, Oregon. Generally speaking, these areas demonstrated some of the lowest levels of poverty concentration in the entire sample. In Seattle, concentrated poverty decreased slightly (3%), while in Portland, it increased slightly (1%). Meanwhile, levels of concentrated affluence increased within both metro-areas – 7% and 9%, respectively. Characterizing Regional Trends in Poverty and Affluence Concentration in the US, 1990-2000 The concentrated poverty quadrant diagram (Figure 2.1) articulates that, during the 1990s, concentrated poverty decreased significantly across the country. In particular, of the 50 MSAs selected, only 12 witnessed increases in their levels of poverty concentration. While some MSAs in the South demonstrated extreme declines in their levels of poverty concentration (New Orleans, Memphis, San Antonio), a number of the larger, Midwestern cities of the Rustbelt experienced decreases as well (Chicago, Detroit, Cleveland, Milwaukee, and Buffalo). This is noteworthy because these same areas served as archetypes for the vast canon of historical research surrounding this phenomenon during the 1980s. Meanwhile, the quadrant containing MSAs with low and declining rates of poverty concentration contained the largest grouping of the entire sample. While these MSAs demonstrated the least amount of variation in their 2000 concentrated poverty 81 rates, they demonstrated a great deal of regional variation, as areas of the South (Atlanta, Jacksonville, Nashville, Tampa, and Charlotte and Raleigh-Durham-Chapel Hill), smaller areas of the Midwest (Pittsburgh, Dayton, Grand Rapids, Kansas City, and Indianapolis), East Coast (Washington D.C. and Boston), and the West (Denver and Seattle) were all represented. In contrast, only four MSAs demonstrated low, but increasing rates of poverty concentration – the fewest in the entire sample. In addition to varying population sizes, these areas (Las Vegas, Albany, Greensboro, and Portland) demonstrated a high degree of geographic variation as well. Finally, the grouping characterized by high and increasing rates of poverty concentration contained some of the most populous (Los Angeles, New York, and Miami) as well as some of the least populous (West Palm Beach and Hartford) of the sample. San Diego and Dallas were also present within this particular grouping. However, once again, in addition to variations in size, they also demonstrated a high level of geographic variation. This particular diagram highlights a number of trends that are critical to understanding the changing nature of poverty concentration in the US. In particular, it illustrates that, during the 1990s, the vast majority of the selected MSAs (38) witnessed decreases in their rates of poverty concentration. In particular, these decreases occurred within MSAs located in the Midwest, which has long been regarded as its traditional geographic epicenter. Second, despite the aforementioned decreases, the diagram illustrates that extreme levels of geographic dispersion have emerged, as nearly half of the selected MSAs (22) had concentrated poverty rates that were above the national 82 median. Lastly, the model illustrates that concentrated poverty increased within areas that we might not typically think of as being nodes of inequality, such as Hartford, Portland, Albany, Dallas, and Oklahoma City. The concentrated affluence quadrant diagram (Figure 2.2) demonstrated that substantial increases within this particular phenomenon occurred during the same time- period. In fact, all but five of the selected MSAs experienced increases. Two of these in particular -Hartford and Albany - were amongst the grouping of MSAs that experienced increasing rates of poverty concentration. Of those MSAs that had high rates of affluence concentration and experienced increases, the vast majority were larger (New York, Washington D.C., San Francisco, Chicago, Boston, Philadelphia). Surprisingly, Los Angeles had a concentrated affluence rate that was well above the median, but demonstrated no increase, and Miami was slightly below the median. Meanwhile, less populous MSAs had lower, but increasing rates of affluence concentration. Generally speaking, these MSAs were divided into two clusters, with smaller areas demonstrating lower affluence concentration rates (Norfolk, Greensboro, Dayton, Buffalo, Las Vegas, Providence, Oklahoma City, Portland, New Orleans, and Tampa) and slightly larger areas demonstrating rates that were slightly below the median as well as increases (Cincinnati, Cleveland, Milwaukee, Seattle, Salt Lake City, Sacramento, San Antonio, Louisville, and Orlando). This diagram articulates that - with the exception of some anomalies - both higher rates and greater increases in affluence concentration were associated with the most populous MSAs. 83 Finally, the economic polarization quadrant diagram (Figure 2.3) depicts changes in the rates of both concentrated poverty and concentrated affluence that occurred during the 1990s for the 50 largest Metropolitan Statistical Areas. In particular, it demonstrates that while levels of concentrated affluence decreased in a small number of the selected MSAs (3), they increased in almost all (45) of them. Meanwhile, two of the selected MSAs demonstrated no change in concentrated affluence but increasing levels of concentrated poverty (Los Angeles and Rochester). Of the three MSAs with decreasing levels of concentrated affluence, including Pittsburgh, Pennsylvania, Albany, New York, and Hartford, Connecticut, Albany and Hartford also demonstrated increasing levels of poverty concentration. However, it should be noted that these metro-areas represent smaller locales with populations that would, therefore, be sensitive small population changes due to immigration, out- migration, etc. Of those metro-areas demonstrating increases in their levels of affluence concentration, most (30) also demonstrated decreasing levels of poverty concentration. This particular subset was regionally diverse, including several of the older, industrial cities upon which many of the historical studies of concentrated poverty were based, such as Chicago, Detroit, Cleveland, Buffalo, and Milwaukee. Other Midwestern metropolitan areas that fell into this grouping included Minneapolis, Indianapolis, Cincinnati, Grand Rapids, Dayton, and Kansas City. Additionally, however, a number of Southern metro- areas such as Memphis, New Orleans, Charlotte, Raleigh-Durham-Chapel Hill, Louisville, Atlanta, and Jacksonville, which had the greatest increase in affluence 84 concentration, were represented. These findings indicate that while the majority of the selected MSAs can be characterized by poverty concentration, they can also be characterized by affluence concentration as well. Understanding Poverty Concentration and Suburban Poverty Concentration in the US, 1990-2000 The first stage of the 2SLS model for 1990 and 2000, in which the problematic variable Concentrated Affluence was screened by instrumental variables, yielded R- squared values of .7324 (1990) and .8588 (2000). These values are sufficiently robust and demonstrate that these particular variables adequately account for the variance in the original Concentrated Affluence variable. Therefore, they are suitable for predicting the (new) exogenous values of Concentrated Affluence. These values were, then, inserted into the OLS model in the place of the original Concentrated Affluence variable. In the paragraphs that follow, I present the results of the 1990 and 2000 OLS models for Concentrated Poverty and Suburban Concentrated Poverty and discuss their implications. Poverty Concentration 1990-2000 Table 2.3 depicts the 1990 and 2000 poverty concentration models. The 1990 Base model for poverty concentration within the 50 largest MSAs revealed that Percent Black (p=.005), Percent Other (p= -.024), and Percent Unemployment (.000) were significant variables. Therefore, in this particular iteration, poverty concentration was higher within MSAs with increasing populations of both unemployed residents and Black residents. These areas also contained decreasing percentages of residents categorized as Percent Others (these individuals may have been either bi-racial or multi-racial and, 85 therefore, were not included in one of the fifteen single racial categories listed on the census form). In the second iteration, the addition of the regional dummy variables considerably increased the overall strength of the model from .7154 to .8240, while also increasing the significance level of Percent Black (p=.000) and Percent Other (p= -.018). While Percent Unemployment remained significant (p=.000), Total Population (p= -.060), Percent Manufacturing, and Percent Asian were significant at the 0.1 level – all with negative relationships with the dependent variable. Meanwhile, two of the regional dummy variables, South (p= -.022) and Midwest (p=.008), were significant as well. The aforementioned changes to the model brought about by the addition of these particular variables demonstrate the extensive role of place-specific economic, demographic, and political factors in shaping conditions of poverty concentration across the selected MSAs. The model articulates that poverty concentration was greater within MSAs characterized by larger shares of Unemployed residents and Black residents. These MSAs were also characterized by small population size relative to the average in the sample, and lower shares of Asian population and workers employed in manufacturing. In addition to these more general characteristics, the regional dummy variables indicate that compared to the Northeast, the Midwest had greater levels of poverty concentration. Meanwhile, levels of poverty concentration in the South were lower. Finally, in the third iteration, the Percent Foreign Born variable was, replaced by the three immigrant cohort variables – immigrants that arrived in the US within the last ten years (Fb910), immigrants that arrived between ten and twenty years ago (Fb91020 86 Yrs), and immigrants that arrived more than twenty years ago (Fb920). By nature, these variables are highly correlated with each other. Therefore, to minimize the chance of multi-collinearity, each was inserted into the model separately. In addition to reducing chances of multicollinearity, this technique also allows for the analysis of each immigrant cohort’s unique relationship with the Concentrated Poverty, as well as the independent variables included in the model. The addition of the variable Fb910 yielded an R-squared of .7918. In this particular model, Percent Black (p=.000), Percent Unemployed (p=.001), and Midwest (p=.001) were all significant. Meanwhile, Percent Other (p= -.036) and Fb910 (p= -.009) were significant, and negatively correlated with Poverty Concentration. This indicates that Poverty Concentration was greater within areas that had larger populations of Unemployed residents and Black residents, but that more of the Percent Other population (some sizable share of which is Latino) and recent immigrants were negatively associated with poverty concentration. Similar to the previous model variant, poverty concentration was higher within MSAs located in the Midwest (compared to the Northeast). Concentrated affluence was not significant (p=.573). Next, the variable Fb91020 yielded a slightly lower R-squared of .7824. Again, Percent Black (p=.000), Percent Unemployed (p=.000), and Midwest (p=.001) were significant. Additionally, Fb91020 (p= -.019) was significant (although less significant than Fb910) and negatively correlated with Poverty Concentration. Here, again, Concentrated Poverty was greater in those MSAs with larger shares of Unemployed residents and Black residents, and more pronounced within the Midwest (compared to the 87 Northeast); the share of immigrants arriving 10-20 years prior was associated with lower levels of concentrated poverty. The predicted value of concentrated affluence was negatively correlated with concentrated poverty and was less significant than in the previous iteration (p= -.816). Finally, inserting Fb920 into the model yielded an R-squared of .7469. Similar to the previous iterations, Percent Black (p=.000), Percent Unemployed (p=.000), and Midwest (p=.000) were all significant, while Fb920 (p= -.174) was negatively correlated with poverty concentration but not significant. This particular model articulates, once again, that concentrated poverty was greater in MSAs that had increasing levels of Unemployed residents and Black residents, and that (once again) such conditions were greater within MSAs located in the Midwest (compared to the Northeast). Again, the predicted value of concentrated affluence was negatively correlated with concentrated poverty, but still insignificant (although slightly less so) (p= -.263). The results of the base and regional dummy models demonstrate the linkage between Blacks, joblessness, and poverty concentration and are congruent with the dominant conceptualizations of poverty concentration expressed during the 1980s and 1990s (Wilson 1987, Massey and Denton 1990, Jargowsky 1997). While the models clearly confirm the conditions that have served as the foundation for the vast canon of research on the Urban Underclass, they also demonstrate that - during this particular time-period - concentrated affluence was not a significant factor in the process driving poverty concentration. In particular, the predicted value of concentrated affluence was never significant in the models. In fact, it actually decreased in significance from .337 in 88 the base iteration to .723 in the regional dummy variable iteration and was negatively correlated with the dependent variable in two of the three immigrant iterations. Meanwhile, the immigration iterations themselves echoed the same sentiments. In all three iterations, Percent Black, Percent Unemployment, and Midwest were significant. Recent and mid-term immigrant variables (Fb910 and Fb1020) were significant (-.009 and -.019 respectively), although the long-term immigrant variable was not. All three cohort variables were negatively correlated with the dependent variable, meaning that Concentrated Poverty was more likely to be greater within those MSAs that had lower levels of recently arriving or relatively established immigrants, and had nothing to do with the presence of well-established immigrants. Finally, within these iterations, Concentrated Affluence was never a significant factor. Table 2.3a: Final Regression Results - Concentrated Poverty, 1990 !""# !"#$ %$&'()"* +,--. /"0'"1*$# 2--'&0"3() $%&'%!#%()* $%&'%!#+,#%()* $%&'%,#-%()* 4($56 78929:92 4($56 78929:92 4($56 78929:92 4($56 78929:92 4($56 78929:92 ./01%23)4356/ !"#$%#&'(&%)*+",%'&- !"#$%#&'(&%)*+",%'&- !"#$%#&'(&%)*+",%'&- 7891%23)4356/* .*/0($1 234556784 23225 .*/0($1 2357529:; 23222 .*/0($1 23:;7577: ;6;;; 235255<99 ;6;;; 235:<5;96 ;6;;; .*=(>#" ? .*=(>#" ? .*=(>#" ? ? ? .*@AB(# ? .*@AB(# C23886:759 2362: .*@AB(# ? ? ? .*D&E%' C4239658 232;: .*D&E%' C;93:9475 23269 .*D&E%' C;5326<6: 23248 ? ? .*F"'%BG#*/"'# C238<22597 23226 .*F"'%BG#*/"'# ? .*F"'%BG#*/"'# H H H H H H .*I(#JK($&J'B#G ? .*I(#JK($&J'B#G C23;5;:289 23625 .*I(#JK($&J'B#G ? C23;6;:<49 23698 ? .*L%',B$%A ? .*L%',B$%A ? .*L%',B$%A ? ? ? .*M#%NO0"-N%#& 643::6:; 23222 .*M#%NO0"-N%#& 6;3:8424 23222 .*M#%NO0"-N%#& 6;389994 ;6;;; 6;327:9 ;6;;; 6237:475 ;6;;; .*P"N%*DQ#%'EABO ? .*P"N%*DQ#%'EABO ? .*P"N%*DQ#%'EABO ? ? ? .*+",%'&- ? .*+",%'&- ? .*+",%'&- ? ? ? R"&(0*+"OJ0(>"#*S="GT ? R"&(0*+"OJ0(>"#*S="GT C232467;79 23282 R"&(0*+"OJ0(>"#*S="GT ? ? ? +'%)B$&%)*!"#$3*@U3 236;78<2: 2344< +'%)B$&%)*!"#$3*@U3 232528467 23<;4 +'%)B$&%)*!"#$3*@U3 232894886 235<4 C232;9264 23968 C236;5:62; 23;84 V%A& H V%A& ? V%A& ? ? ? L"J&E H L"J&E C232827;6< 232;; L"J&E ? ? ? IB)Q%A& H IB)Q%A& 2328:8;7 23229 IB)Q%A& 232<;265 ;6;;< 23299294: ;6;;; 232977289 ;6;;; .*F/*62*W'A H .*F/*62*W'A H .*F/*62*W'A C23797:845 23227 H H H H .*F/*62C;2*W'A H .*F/*62C;2*W'A H .*F/*62C;2*W'A H H C6397:9:5 23267 H H .*F/*;2X*W'A H .*F/*;2X*W'A H .*F/*;2X*W'A H H H H C23<;87;5: 236<: : , #1;!<= #1>,=# #1;"!> #1;>,= #1;=?" @ <# <# <# <# <# %$=> ?'&)'@A"):9/"0'"1*$# !*,$> B0$)=#9')94()A$):0":$=9CD,$)A$ 89 Table 2.3b: Final Regression Results - Concentrated Poverty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hile each of the iterations of the 2000 model demonstrated lower R-squared values than their 1990 counterparts, they possessed a greater number of significant variables. This indicates that while less overall variance in concentrated poverty could be predicted by the 2000 independent variables, more factors were involved in explaining that variance. This suggests in that poverty concentration became increasingly complex during the 1990s. The 2000 Base Model demonstrated an R-squared of .6027 and indicates that Percent Manufacturing (p=.002), Percent Poverty (p=.005), Percent Unemployment (p=.010), and Percent Services (p=.022) were all significant. Meanwhile, Percent Asians (p= -.012) and Percent Homeownership (p= -.009) were significant, as well, and negatively related to Poverty Concentration. Percent Foreign Born was marginally significant (p=0.099). This iteration reveals that Poverty Concentration was higher in MSAs that were characterized by higher rates of residents employed in Manufacturing and Service sectors, but also increasing levels of Unemployment and Poverty. Areas with higher shares of Asian population and homeowners had lower concentrated poverty. However, the most salient finding from this particular iteration is that the Predicted Value of Concentrated Affluence is significant (p=.000) – an outcome that did not characterize any of the 1990 models. The addition of regional dummy variables increased the overall strength of the model from .6027 to .6645. In particular, these variables boosted the significance of Percent Black and Percent Poverty (p=.000), while reducing the importance of homeownership, service, and manufacturing employment, unemployment, and Asian 91 population. Once again, the Predicted Value of Concentrated Affluence was significant (.025), but less so than in the previous iteration. The regional dummy variables West (p= -.021) and South (p= -.000) were significant, they were negatively correlated with Poverty Concentration. This iteration reveals that Concentrated Poverty was higher in those MSAs with increasing shares of Blacks and greater levels of Poverty, but also increasing levels of Concentrated Affluence. On average, these conditions were less prominent within MSAs located in the Western and Southern United States (compared to the Northeast). Finally, in the third iteration, the variable Percent Foreign Born was again replaced by the three immigrant cohort variables (this time from the year 2000) – immigrants that arrived in the US within the last ten years (Fb010), immigrants that arrived between ten and twenty years ago (Fb01020 Yrs), and immigrants that arrived more than twenty years ago (Fb020). Again, each was inserted into the model separately in order to minimize the chances of multicollinearity and better understand its unique relationship with the poverty concentration. The addition of the variable Fb010 yielded an R-squared of .6455. This was lower than that of the previous iteration (.6645) and was significantly lower than that of its 1990 counterpart (.7915). Again, however, unlike the 1990 model, a greater number of significant variables were present. Here, Percent Manufacturing (p=.045), Percent Unemployment (p=.003), and Percent Poverty (p=.001) were significant. Meanwhile, Asian (p= -.024) and Homeownership (p= -.009) were significant, but negatively correlated with Poverty Concentration. In particular, Fb010 was significant, and 92 negatively correlated with Concentrated Poverty (p= -.045), as well. Meanwhile, the predicted value of Concentrated Affluence was once again significant (p=.001). This particular iteration indicates that Poverty Concentration was higher in those MSAs with greater numbers of residents employed in Manufacturing, higher levels of Unemployment, and greater levels of Poverty, but also greater levels Affluence Concentration. These MSAs also had smaller percentages of Asians, homeowners, and newly arriving immigrants. Next, the variable Fb01020 was inserted into the model. The R-squared was slightly less than the previous iteration (.6111) and much lower than its 1990 counterpart (.7824). Here, Unemployment (p=.008) and Poverty (p=.000) were significant. Meanwhile, two of the regional dummy variables – West (p= -.001) and South (p= -.000) – were significant, and negatively correlated with Concentrated Poverty. Again, the predicted value of Concentrated Affluence was slightly less significant than in the previous iteration (p=.006). Moreover, similar to Fb010 in the previous iteration, Fb01020 was negatively correlated with Concentrated Poverty. However, in this case, it was not significant (p=-.124). This indicates that Poverty Concentration was higher in those MSAs that possessed higher levels of Unemployment and overall Poverty, but also greater levels of Affluence Concentration (although slightly less than those with immigrants that had arrived more recently). Additionally, it articulates that MSAs located within the West or South had lower levels of Poverty Concentration (compared to the Northeast). 93 Finally, the variable Fb020 was inserted into the model. The R-squared was .6845 – the highest of all of the 2000 immigration iterations. Here also, for the first time in this set of iterations, race played a factor, as Percent Black was positively correlated with Concentrated Poverty (p=.000), as was Poverty (p=.000). Meanwhile, similar to the previous iteration, two of the dummy variables - West (p=.035) and South (p=.000) - were significant and, negatively correlated with Concentrated Poverty. The predicted value of Concentrated Affluence was once again significant (p=.034) – although less significant than the two previous iterations. Fb020 was not significant (p=.532). These results suggest that Concentrated Poverty was higher in those MSAs with higher shares of Blacks and poor residents, but also increasing levels of Concentrated Affluence. Similar to the previous iteration, it also suggests that MSAs located within the West or South had lower levels of Poverty Concentration (compared to the Northeast). The iterations of the 1990 Concentrated Poverty model confirm the conditions that served as the basis for historical conceptualizations (Wilson 1987, Massey and Denton 1993, Jargowsky 1997). However, the 2000 model presents us with a much different narrative, demonstrating the salient demographic, geographic, and economic shifts that occurred within the landscape of poverty concentration during the 1990s. First, Blacks - once the focal point of concentrated poverty research - no longer appeared to play a prominent role in the poverty concentration process. Instead, and perhaps more interestingly, the iterations articulate the emergence of Asians as related to lower levels of concentrated poverty. 94 Second, these particular iterations shed light on recent fluctuations in the spatial distribution of poverty concentration. During the 1980s, this phenomenon was most acute in the Midwest (with respect to the Northeast). However, during the 1990s, this particular region was no longer the epicenter for poverty concentration. This demonstrates that the vast majority of historical work on poverty concentration, which was based on the Rustbelt area of the Midwest and the East Coast, may have served as adequate foundations in prior periods, but are no longer as relevant. These findings emphasize the pertinence of developing much wider lenses - both spatially and racially - through which to analyze poverty concentration (Strait 2006). Meanwhile, poverty and unemployment - also long-standing tenets of historical conceptualizations - remain significant factors in the nation’s poverty concentration story. However, unlike during the 1980s, when Blacks were disproportionately affected by the emergence of deindustrialization and the concomitant loss of manufacturing positions, the iterations of the 2000 model reveal that this combination of variables can no longer be implicated in the poverty concentration process. This also emphasizes that historical conceptualizations are in need of revision. Instead, the 2000 model reveals that, while unemployment remained a significant contributor, Blacks were not as centrally involved. Additionally, it suggests that different waves of immigrants appear to play different roles in the poverty concentration process. For example, MSAs with more recent immigrants tended to have lower levels of concentrated poverty. This finding is particularly salient as it stands in contrast to long-standing theories regarding immigrant settlement patterns and urban development, which have emphasized that recently- 95 arriving immigrants often enter the US mired in poverty and work toward assimilation and improved socioeconomic status (Park et al 1925). For the purposes of this research, however, the most salient finding from the models is the dramatic increase in the role of Concentrated Affluence in the poverty concentration process. Throughout the iterations of the 1990 model, this particular variable was not significant at all. However, in the 2000 model, it was significant across all model specifications. These results confirm the hypothesis that the affluent increasingly sought to isolate themselves from poor people over the 1990s (Blakely and Snyder 1997). Overall, the 2000 Concentrated Poverty models confirm the presence of a strong, interdependent relationship between affluence concentration and poverty concentration. To that end, the one-sided nature of urban geographic and social science literature in general, which has historically focused its attention solely upon poverty concentration, is also in need of revision. Instead, affluence concentration should be taken more seriously, as it represents a new lens through which to view inequality. Suburban Poverty Concentration, 1990-2000 Table 2.4 depicts the results of the 1990 and 2000 Suburban Concentrated Poverty models. These models contain the same independent variables that were utilized in the Concentrated Poverty models. However, Suburban Concentrated Poverty serves as the dependent variable. The 1990 Base model had an R-squared of .5703 and only two of the independent variables were significant - Percent Unemployment (p=.000) and Percent Black (p=.002). 96 Thus, Suburban Poverty Concentration was higher in those MSAs that had greater shares of Black residents and higher Unemployment rates. Percent Foreign Born and the Predicted Value of Concentrated Affluence were negatively correlated with the dependent variable but these variables were not significant. In the second iteration, the regional dummy variables were added. However, none of these were significant or met the 0.2 threshold and were, therefore, removed from the iteration. This rendered the model identical to the previous iteration. Next, the three immigrant iterations were run. All three iterations (Fb910, Fb920, and Fb91020) yielded similar results, despite slight deviations in their R-squared values (.5480, .5409, .5640, respectively). In each of the iterations, it was revealed that Suburban Concentrated Poverty was greater in MSAs with greater shares of Blacks and higher rates of Unemployment. Of note, within these iterations, neither the Predicted Value of Concentrated Affluence nor any of the immigrant cohort variables played a significant role. The Base, Regional Dummy, and Immigrant iterations of the 1990 Suburban Concentrated Poverty model mirror those of the 1990 Concentrated Poverty model (with much lower R-squared values). In doing so, they reaffirm that, during the 1980s, regardless of its spatial location, poverty concentration stemmed largely from the effects of joblessness and large populations of Blacks. Meanwhile, similar to the 2000 Concentrated Poverty model, the 2000 Suburban Concentrated Poverty model articulated the increasing levels of complexity that became associated with poverty concentration during the 1990s. 97 Table 2.4a: Final Regression Results - Suburban Concentrated Poverty, 1990 !""# !"#$ %$&'()"* +,--. /"0'"1*$# 2--'&0"3() $%&'%!#%()* $%&'%!#+,#%()* $%&'%,#-%()* 4($56 78929:92 4($56 78929:92 4($56 78929:92 4($56 78929:92 4($56 78929:92 ./01%23)4356/ !"#"$#%&'()&*+',)-.$/0 !"#"$#%&'()&*+',)-.$/0 !"#"$#%&'()&*+',)-.$/0 7891%23)4356/* 1'23%*4 5+56789:; 5+55; 1'23%*4 5+56789:; 5+55; 1'23%*4 5+56755; ;6;;< 5+575<7<= ;6;;= 5+56;=85< ;6;;> 1'>%?&) @ 1'>%?&) @ 1'>%?&) @ @ @ 1'ABC%& @ 1'ABC%& @ 1'ABC%& @ @ @ 1'D/E.$ @ 1'D/E.$ @ 1'D/E.$ @ @ @ 1'F)$.CG&'2)$& H5+5855:5I 5+989 1'F)$.CG&'2)$& H5+5855:5I 5+989 1'F)$.CG&'2)$& J J J J J J 1'K%&"L%*/"$C&G @ 1'K%&"L%*/"$C&G @ 1'K%&"L%*/"$C&G @ @ @ 1'!.$-C*.B @ 1'!.$-C*.B @ 1'!.$-C*.B @ @ @ 1'M&.NO3)0N.&/ 9+8<:I;; 5+555 1'M&.NO3)0N.&/ 9+8<:I;; 5+555 1'M&.NO3)0N.&/ 9+6<I<:8 ;6;;; 9+8:I;6 ;6;;; 9+7;<6<9 ;6;;; 1'P)N.'DQ&.$EBCO @ 1'P)N.'DQ&.$EBCO @ 1'P)N.'DQ&.$EBCO @ @ @ 1',)-.$/0 @ 1',)-.$/0 @ 1',)-.$/0 @ @ @ R)/%3',)O"3%?)&'S>)GT 5+55<I9=I 5+96< R)/%3',)O"3%?)&'S>)GT 5+55<I9=I 5+96< R)/%3',)O"3%?)&'S>)GT @ @ @ ,$.UC*/.U'()&*+'AV+ H5+5;978;= 5+<5; ,$.UC*/.U'()&*+'AV+ H5+5;978;= 5+<5; ,$.UC*/.U'()&*+'AV+ 5+555=I86 5+::5 H5+556<5:: 5+6:= 5+555=699 5+:77 W.B/ J ?$#: @ W.B/ @ @ @ !)"/E J @(,:A @ !)"/E @ @ @ KCUQ.B/ J B'CD$#: @ KCUQ.B/ @ @ @ 1'F2'95'X$B J 1'F2'95'X$B J E9F!9=;9G0# H5+56:=6=; 5+=<; J J J J 1'F2'95H;5'X$B J 1'F2'95H;5'X$B J E9F!9=;H<;9G0# J J H5+56=<<7 5+875 J J 1'F2';5Y'X$B J 1'F2';5Y'X$B J E9F!9<;I9G0# J J J J H5+97I56: 5+998 : , #1;<#= : , #1;<#= #1;>?# #1;>#" #1;@># A ;# A ;# ;# ;# ;# %$C9J @'&)'KL"):9/"0'"1*$# !*,$J M0$)C#9')94()L69NO,$)L$ 98 Table 2.4b: Final Regression Results - Suburban Concentrated Poverty, 2000 !""" !"#$ %$&'()"* +,--. /"0'"1*$# 2--'&0"3() #$%&$'"$()* #$%&$'"+!"$()* #$%&$!",$()* 4($56 78929:92 4($56 78929:92 4($56 78929:92 4($56 78929:92 4($56 78929:92 -./.01.02$34)5467. !"#"$#%&'()&*+',)-.$/0 !"#"$#%&'()&*+',)-.$/0 !"#"$#%&'()&*+',)-.$/0 801./.01.02$34)5467.* 1'23%*4 5 1'23%*4 5 6+67897:8 6+986 1'23%*4 6+6;:<798 6+9<9 5 6+6;<<8<; 6+99: 1'=%>&) 5 1'=%>&) 5 5 1'=%>&) 5 5 5 1'?@A%& B6+99<67C8 6+6D7 1'?@A%& 5 B6+97<779C 6+99< 1'?@A%& B6+97:8E87 6+97: 5 B6+9:78D9D 6+68C 1'F/G.$ 5 1'F/G.$ 5 6+7;C:;;9 6+96; 1'F/G.$ 6+77EE8;D 6+99C 5 6+7;EE;<< 6+6E8 1'H)$.AI&'2)$& 5 1'H)$.AI&'2)$& 5 5 1'H)$.AI&'2)$& J J J J J J 1'K%&"L%*/"$A&I 6+997:E;< ;6;;< 1'K%&"L%*/"$A&I 6+6:E<89D 6+99; 6+6CE7:;; 6+6<: 1'K%&"L%*/"$A&I 6+6CCEE78 6+688 5 6+6<68:9< ;6;=> 1'!.$-A*.@ 6+7CE<:6: ;6;?; 1'!.$-A*.@ 5 5 1'!.$-A*.@ 5 5 5 1'M&.NO3)0N.&/ 6+C;8D6<: ;6;;= 1'M&.NO3)0N.&/ 6+CC7C6;< ;6;;@ 6+:876;E9 ;6;<< 1'M&.NO3)0N.&/ 6+:;86C8< ;6;A= 6+C<<;<;D ;6;;@ 6+:6977:< ;6;=A 1'P)N.'FQ&.$G@AO B6+6EEC;<: ;6;<@ 1'P)N.'FQ&.$G@AO B6+6C67<:; 6+97; B6+6<;D76: 6+68: 1'P)N.'FQ&.$G@AO B6+6<9<;97 6+6EE 5 B6+6<98D:E 6+6E: 1',)-.$/0 9+6ED66; ;6;;; 1',)-.$/0 9+<;8889 ;6;;; 9+D<6<< ;6;;; 1',)-.$/0 9+D97ED7 ;6;;; 9+<8C;9: ;6;;; 9+<<EE8E ;6;;; R)/%3',)O"3%>)&'S=)IT 5 R)/%3',)O"3%>)&'S=)IT 5 5 R)/%3',)O"3%>)&'S=)IT 5 5 5 ,$.UA*/.U'()&*+'?V+ 6+6E7CCDD ;6;;; ,$.UA*/.U'()&*+'?V+ 6+6DDC;E< ;6;;; 6+6E:C<DE ;6;;; ,$.UA*/.U'()&*+'?V+ 6+68:<87 ;6;;B 6+6866DD: ;6;;; 6+68<D9<E ;6;;; W.@/ J J C$#: B6+66E;EE8 ;6;@? B6+66DE<:: 6+99E W.@/ B6+668:::< 6+968 B6+66EEE8; ;6;@A B6+66D99<8 6+9D6 !)"/G J J D(,:E B6+696C9;; ;6;;? B6+69;E<6< ;6;;A !)"/G B6+69C677C ;6;;B B6+69;6DE ;6;;< B6+69:79:8 ;6;;@ KAUQ.@/ J J F'GH$#: 5 5 KAUQ.@/ 5 5 5 1'H2'96'X$@ J J 1'H2'96'X$@ J J I9J!9<;9K0# 6+6:6D787 6+<6C J J J J 1'H2'96B76'X$@ J J 1'H2'96B76'X$@ J J I9J!9<;L@;9K0# J J 6+69:<9<7 6+8<E J J 1'H2'76Y'X$@ J J 1'H2'76Y'X$@ J J I9J!9@;M9K0# J J J J 6+6<ED6C8 6+;<< 9 ! ":;'!< 9 ! ":;="= ;6N?A< 9 ! ":;>?@ ;6?OO= ;6N?>@ A B" A B" =; A B" B" B" %$GP D'&)'QR"):9/"0'"1*$# !*,$P S0$)G#9')94()R$):0":$G9TU,$)R$ 99 100 First, the iterations of the 2000 Suburban Concentrated Poverty model yielded R- squared values that were much higher than that of the 1990 iterations and displayed a greater number of independent variables that were significant. This indicates that a greater proportion of the overall variance in suburban poverty concentration was predicted by the 2000 independent variables. This was the exact opposite of the 1990 and 2000 Concentrated Poverty models, in which less of the overall variance in the dependent variable was explained, but a greater number of the independent variables were significant. The Base model generated an R-squared of .7129. Moreover, Percent Manufacturing (p=.001), Percent Unemployment (p=.005), and Percent Poverty (p=.000) were all significant. Additionally, Percent Services (p=.060) and Percent Asian were significant at the 0.1 level, as well. Meanwhile, Percent Homeownership (p=-.012) was negatively correlated with Suburban Concentrated Poverty. Therefore, Suburban Poverty Concentration was greater in those MSAs with larger shares of residents employed in Manufacturing and Services, and higher levels of Unemployment and Poverty. These same areas were characterized by lower rates of homeownership. Also of note, the Predicted Value of Concentrated Affluence (p=.000) was significant for the first time. The addition of the Regional Dummy Variables yielded a higher R-squared value of .7631. Here, Percent Poverty (p=.000) and Percent Unemployment (p=.011) remained significant. Additionally, the regional dummy variable for the South was negatively related with and significant (p= -.003). Finally, Percent Manufacturing (p= .064) was marginally significant, as was Percent Other and Percent Homeowners. Suburban 101 Concentrated Poverty was, thus, higher in MSAs that were characterized by greater shares of people employed in manufacturing, but also increasing levels of poverty and unemployment. Additionally, selected MSAs that were located in the South had lower levels of suburban poverty concentration (compared to the Northeast). Again, the Predicted Value of Concentrated Affluence (p=.000) was significant. Finally, the immigrant iterations were run. The first iteration containing Fb010 yielded an R-squared of .7648. Here, Percent Unemployment (p=.035) and Percent Poverty (p=.000) were significant, and Percent Manufacturing and Homeownership were marginally significant (p=0.088 and -0.099 respectively). Additionally the Predicted Value of Concentrated Affluence was again significant (p=.004). Negatively correlated with Suburban Concentrated Poverty, South (p= -.004) was, again, significant, while West was marginally significant (p=0.108). Finally, Fb010 (p= .605) was positively related to the dependent variable, but not significant. Therefore, this particular iteration suggests that Suburban Concentrated Poverty was higher in those MSAs with higher rates of unemployment and poverty, but also increasing rates of affluence concentration. Meanwhile, Suburban Poverty Concentration was lower in the South and West (compared to the Northeast). Next, the iteration containing Fb01020 yielded a slightly lower R-squared of .6995. Similar to the previous iteration, it was positively correlated with the dependent variable, but not significant (p=.869). Once again, Percent Unemployment (p=.002) and Percent Poverty (.000) were significant, while two of the Regional Dummy Variables - West (p= -.023) and South (p= -.001) - were significant, and negatively related to the 102 dependent variable. Again, the Predicted Value of Concentrated Affluence (p=.000) was significant. These findings mirror those already highlighted – that Suburban Concentrated Poverty was higher in those MSAs characterized by higher unemployment and poverty rates, but also higher rates of affluence concentration. And, rates of Suburban Poverty Concentration were lower within MSAs located in the South and West (compared to the Northeast). Finally, the iteration containing Fb020 yielded an R-squared of .7682, which was the highest of all the immigrant iterations. Here, Percent Manufacturing (p=.058), Percent Unemployment (p=.053), and Percent Poverty (p=.000) were all significant. Additionally, Percent Asian and Percent Other, as well as Homeownership, were marginally significant - Meanwhile, the Regional Dummy Variable South (p= -.002) was significant, and again negatively correlated with the dependent variable. The Predicted Value of Concentrated Affluence (p=.000) was, again, significant. Fb020 (p=.366) was positively correlated with the dependent variable, but not significant (although it was the most significant of the immigration variables). Despite the fact that none of the immigration variables were significant within either the 1990 or 2000 models, they remain important in shaping our understanding of regional economic and race-related trends in poverty and affluence concentration. The 2000 model demonstrates that Suburban Concentrated Poverty was higher in those MSAs characterized by higher rates of employment in Manufacturing, but also higher rates of unemployment and poverty. Moreover, MSAs located in the South 103 demonstrated lower levels of Suburban Poverty Concentration (compared to the Northeast). Additionally, these iterations demonstrate the stark changes that occurred within the landscape of poverty concentration during the 1990s. In particular, while Unemployment levels remained a significant factor, Poverty played a primary role as well. Additionally, in contrast to the long-standing conceptualizations that fueled the Urban Underclass debate, the iterations of the 2000 model fail to articulate a relationship between Suburban Concentrated Poverty and Blacks (or any racial group for that matter). However, immigrants appear to play an important role. Unlike the 1990 iterations, all three of the immigrant cohort variables were positive, but not significant. This demonstrates that, although they did not play a prominent role, immigrants – whether newly arriving, relatively established, or well-established – are in some way involved in the suburbanization of concentrated poverty process. In particular, well-established immigrants (Fb01020) were the most significant of the three cohorts in the model. This, however, is what we would expect to occur, given that they would be most likely to be living in suburban areas after being in the US for twenty or more years. Moreover, the models illustrate changes in regional variation that occurred during the decade. In the 1990 model, none of the regional dummy variables played a role within any of the iterations. However, the 2000 model revealed that rates of Suburban Concentrated Poverty were higher in the Northeast than in the South and West regions and the Midwest, which was not significant in the model, was neither ahead or behind the Northeast with respect to the suburbanization of concentrated poverty. 104 Finally, and perhaps most importantly, Concentrated Affluence emerged as a prominent contributor to explaining levels of Suburban Poverty Concentration during the 1990s. Per the 1990 model variant, during the 1980s, this particular variable was not significant. However, in the 2000 models, it was significant in each variant. The model findings highlight two points in particular. First, although rooted in the same catalysts that were largely responsible for poverty concentration within urban areas in the 1980s, during the 1990s, suburban poverty concentration was not related to one racial group in particular. Instead, it linked to economic drivers, such as unemployment and overall poverty. Second, results reinforce the results of the Poverty Concentration models in demonstrating the growing role of Concentrated Affluence during the 1990s. While research on poverty concentration and the Urban Underclass has dominated the discourse on inequality for the past 25 years, affluence concentration and economic polarization, in general, may very well represent the discourse on inequality for the new millennium. In 1990, poverty concentration was higher in the Midwest and lower in the South in MSAs with higher shares of Black population, unemployment rates, and lower percentages of recent and medium-term immigrant populations. This suggests that concentrated poverty was driven by long-standing dynamics of racial and class segregation, associated with deindustrialization, and particularly pronounced in the Midwest compared to other areas and less evident in rapidly growing Western and Southern regions. MSAs with higher shares of Asians and rates of homeownership also had lower levels of concentrated poverty. And concentrated affluence did not seem to be 105 shaping patterns of poverty concentration. By 2000, this picture had changed. Concentrated poverty was higher in MSAs with lower rates of employment and especially manufacturing employment, higher shares of Black and poor populations, and lower presence of immigrant groups. It was also lower in the West and South. Concentrated affluence also played a role, with MSAs with higher levels of concentrated affluence being characterized by higher levels of concentrated poverty. Suburban concentrated poverty patterns have a roughly similar explanation, being higher in MSAs with higher unemployment rates, larger shares of Black population, and lower shares of immigrant population. MSAs in the West and South had lower levels of suburban concentrated poverty. Concentrated affluence was not a driver. By 2000, however, it was clear that the role of race had declined, and that MSAs with higher shares of employment in manufacturing and services, and higher rates of unemployment and poverty, lower rates of homeownership, lower shares of immigrant population, and higher rates of concentrated affluence were more apt to have higher rates of suburban poverty concentration. Rates were lower in the South and West regions, the locus of rapid economic growth during the 1990s. Thus, suburban concentrated poverty was linked to geographic region, the nature of the job base, overall socio-economic status, immigration dynamics, and efforts of affluent people to separate themselves from the poor. Chapter Two Conclusion For nearly three decades, poverty scholars and social scientists, in general, have focused on conceptualizing concentrated poverty, as well as its urban geography, its ties to the Black Urban Underclass populations, and social consequences. However, by 106 ignoring the concentration of affluence, the specific catalysts involved, and the process by which it occurs, our understanding of inequality has been rendered incomplete. In an attempt to address this lacunae, this research breaks from tradition and attempts to advance the discourse on inequality by demonstrating that poverty concentration - while critical - is but one aspect of the dilemma surrounding inequality. Although few in number, subsequent analyses of affluence concentration have addressed its geography and assessed its relationship to concentrated poverty, while effectively demonstrating that, in many ways, affluence concentration and poverty concentration are similar in several important respects. Yet none of these studies have empirically demonstrated the strong correlation that exists between these phenomena. To that end, our understanding of the ways that poverty and affluence concentration work together, and thus our understanding of inequality, remains incomplete. Based upon the multifaceted empirical analysis conducted, affluence concentration increased significantly within 45 of the nation’s 50 largest MSAs during the 1990s. This demonstrates that many MSAs previously characterized by the presence of concentrated poverty, can now be characterized by the presence of concentrated affluence. Moreover, these findings are reinforced by the regression models constructed, which articulate the presence of an increasingly strong correlation between affluence concentration and poverty concentration during the same time-period. Thus, an interdependent relationship exists between these two phenomena. Therefore, while the recent changes in the spatial distribution of concentrated poverty are important, the 107 widespread augmentation of wealth is also worthy of attention, as it signals the need for a fundamental shift in the way(s) that inequality is defined and conceptualized. Per the 2000 model, within some regions, affluent households may seek to isolate themselves from crime, decreasing property values, and an increasing poverty population, comprised of Blacks, Latinos, and other residents of color, including recently arriving immigrants. However, this type of behavior often leads to a disproportionate share of resources - infrastructure spending, general economic growth, and employment opportunities - within upper-income suburbs and exurban areas. Meanwhile, as these spaces become privatized and the power of homeowner’s associations increase, the ability to shirk fiscal responsibilities to provide affordable housing and other services from which lower-income residents might benefit can be ignored rather easily. Moreover, social concerns often diminish as housing becomes exclusionary and property taxes increase. This and related scenarios clearly signifies the need for stronger inclusionary housing policies, housing tax bonds, and regional governance to ensure that critical resources - housing, education, employment, municipal services, green space and economic opportunities throughout entire metropolitan areas are distributed in an equitable fashion. 108 CHAPTER 3  THE CHANGING FACE OF CONCENTRATED POVERTY  The Changing Landscape of Concentrated Poverty Jargowsky (2003) found that, during the 1990s, concentrated poverty decreased significantly throughout metropolitan areas in the Midwestern and Southern regions of the United States, while increasing within inner-suburban areas and, in particular, the West. Such findings suggest that the face of poverty is undergoing dramatic changes, as poor areas are becoming increasingly differentiated. More importantly, they raise questions as to whether conventional methods of measurement may be unable to adequately depict the complex landscape of poverty, particularly in ‘globalizing’ cities such as Los Angeles, Chicago, New York. What researchers have taken to constitute as ‘concentration’ has been based on a 40 percent benchmark, which defines ‘extreme poverty’ census tracts (neighborhoods) as those in which 40 percent or more of the population is living below the federal poverty threshold. Criticisms of the federal poverty threshold are legion (Citro and Michael 1995; Madden 1996; Joassart-Marcelli and Wagle 2002), the most salient being its inability to distinguish between the needs of different family types or consider regional variations in cost of living expenses. But perhaps more troubling is that, despite the fact that the 40 percent benchmark has become the standard for defining concentration among urban poverty researchers, neither the environmental nor behavioral criteria behind this measure have been substantiated. Given recent changes in the topography of poverty, 109 traditional notions of ‘extreme poverty’ neighborhoods as well as inherent assumptions about their character may no longer apply. Based upon research conducted in the southern California metropolitan region, this paper interrogates the meaning of ‘concentrated poverty’ and proposes to address the following research questions: Do selected places characterized as “extreme poverty neighborhoods” match traditional ideas advanced through the literature employing the 40 percent measure? More specifically, how do the physical environments of these places and social profiles of the residents compare with those commonly associated with traditional conceptualizations of “extreme poverty neighborhoods”? Lastly, from a policy perspective, if this 40 percent measure turns out to be unable to adequately characterize the complex landscape of poverty concentration, will its continued use shape our assumptions – and, more importantly, the nation’s urban policy debates – in inappropriate ways? This chapter is organized as follows. First, numerous studies that employ the 40 percent threshold are reviewed. I demonstrate that through the use of this measure, urban areas as well as those residing there have been inaccurately and, thus, unjustly stigmatized by notions of physical deterioration and perceived social pathologies. Next, following a brief depiction of poverty conditions in southern California, I describe the methodology employed by this analysis. Following, I present general information regarding the municipalities selected, and characterize the ‘extreme poverty’ neighborhoods where research was conducted. Additionally, I discuss the results of the two-fold analysis utilized, which reveals that the 40 percent threshold measure is 110 arbitrary and unable to provide an accurate portrayal of poverty in the region. Finally, in Section VI, policy implications are discussed and areas for further research are suggested. The Origins and Usage of 40 Percent Threshold Research focused on urban poverty concentration in the metropolitan United States highlights the problems associated with poverty measurement and demonstrates that a consistent measure has yet to be agreed upon. A more detailed investigation of methodologies, however, reveals that the 40 percent threshold remains the most widely used measure of poverty concentration, although the origins of this particular threshold criterion have gone largely unexamined. In addition, despite its arbitrary nature (as recognized by Mincy, Sawhill and Wolf 1990; Massey and Eggers 1990; Jargowsky and Bane 1991 and others) and an absence of empirical evidence, scholars have utilized this particular benchmark not only to measure poverty concentration levels within large cities, but also to identify “underclass areas” characterized by the presence of dysfunctional social behaviors, and declining physical infrastructures. In this section, we review several of these studies, as well as criticisms, with the goal of providing both a historical perspective of the 40 percent threshold, as well as a demonstration of its broad usage in analyzing poverty conditions across various geographic areas. The concept of employing percentage-based thresholds to identify impoverished neighborhoods was originally developed by the U.S. Census Bureau (1970) “…in order to provide a statistical index based on income only and to utilize the small area data on poverty status which were available in 1970 for the first time in a decennial census” (p. VIII). Designations for tracts with poverty rates of 30 and 40 percent were also 111 constructed in order to provide some degree of flexibility. Over time, areas in which 40 percent of the population lived below the poverty line became synonymous with “extreme poverty”. The fact that they were originally developed by the U.S. Census Bureau assists in explaining why such thresholds, and in particular the 40 percent variant, have become the primary means of analyzing poverty conditions. For many decades, the decennial census has served as the primary source of comprehensive data at various geographic scales. Therefore, data supplied by the census bureau is commonly believed to be the most accurate and is, therefore, commonly relied upon by researchers. In addition, this particular type of data (at the census tract level and stratified by thresholds) was unavailable prior to 1969 (Danzinger and Gottschalk 1987). Therefore, poverty scholars and social science researchers took full advantage of this “new” data, and its potential to guide groundbreaking contributions. Finally, the 40 percent threshold gained significant prominence during the 1980s, as researchers became interested in examining the “poorest of the poor” and began to employ the threshold exclusively. Ultimately, this particular method of poverty measurement became intimately tied to the debate regarding the “urban underclass”. While poverty rates fell during the 1960s in part as a result of the War on Poverty, they rose slightly in the 1970s. During the 1980s, however, they increased dramatically, drawing the attention of both mainstream journalists and academics who immediately began speculating about the causes, geographic location, and potential effects of this 112 phenomenon. Although the term underclass was first employed as a term to denote conditions of unemployment (Myrdal 1944), during the 1980s, poverty scholars began to utilize the term to denote conditions of extreme poverty resulting from behavioral deviance. The vast majority of this research focused on Blacks and Hispanics in the rustbelt/snowbelt areas of the Midwest and East Coast. (see Clark and Nathan 1982; Nathan 1987; Wilson 1987). Initially, scholars analyzed the underclass from three different perspectives: (1) the length of time that they remained impoverished (persistent poverty); (2) the specific type of household in which they lived and its perceived dysfunctions (behavioral characteristics); and (3) the type of community in which they lived (geographic areas) (Nathan 1987). Over time, however, scholars turned their attention toward the dysfunctional behaviors believed to be most prevalent within urban neighborhoods (Glasgow 1980; Auletta 1982; McLanahan et al. 1986; Van Haistma 1989; Jencks 1989; Ricketts 1989; Murray 1990). The most notable of these studies was conducted by Ricketts and Sawhill (1988), who based underclass existence on the geographic clustering of specific dysfunctional behaviors. These included dropping out of high school, being unemployed, receiving welfare, and living in a female-headed household. Along these lines, they defined an “underclass area” as one in which the proportion of such behaviors was significantly greater (by one standard deviation) than the mean for the entire United States population and asserted that “…extreme poverty areas can reasonably be used as a proxy for concentrations of social problems” (322). Although this methodology drew 113 criticism (Hughes 1989; Jargowsky 1994), socially deviant behavior became linked with the 40 percent threshold. Eventually, research on the underclass became mired in controversy (see Lehman 1986), as it was linked to the “culture of poverty” thesis (Harrington 1962; Lewis 1966), which asserted that poverty was generational and impossible to escape (Ricketts 1992). Additionally, scholars argued that the underclass terminology was a “racial codeword that subtly hides anti-Black and anti-Hispanic feelings” (Gans 1990, 273). In response, researchers turned their focus toward the urban nature of poverty concentration. Similar to research focused on underclass behaviors, however, the 40 percent threshold was once again employed. The 40 percent threshold was first utilized to demonstrate dramatic increases in poverty concentration within Chicago’s urban neighborhoods during the 1970’s (Wilson 1987). Scholars confirmed these findings (Danzinger and Gottschalk 1987; Jargowsky and Bane 1991) – and in doing so endorsed the use of the 40 percent threshold exclusively to denote poverty concentration and focus on impoverished urban residents throughout the nation. Later, these areas were also characterized by the presence of blight and decay, including deteriorated housing, abandoned structures with broken windows, discarded automobiles, and loiterers (Jargowsky 1997). Thus, concentrated poverty neighborhoods, already defined by economic deprivation and deviant behaviors, commanded attention based on their physical conditions, while the spatial nature of poverty was ignored (Massey and Denton 1990; Greene 1991). 114 However, despite these criticisms and the development of alternative measures sensitive to the spatial nature of poverty, the 40 percent threshold continues to be employed in both quantitative and qualitative studies as a means of analyzing various aspects of poverty concentration (Orfield 1997; Cooke 1999; Sanchez-Jankowski 1999; Goetz 2000; Mulherin 2000). While much of this research has focused on urban neighborhoods of the Midwest and East Coast, patterns of poverty concentration in metropolitan regions appear to have shifted significantly during the 1990s. Changes in the West, and particularly southern California, have been notable (Jargowsky 2003). Thus, our particular geographic focus is warranted. Moreover, given recent dynamics of globalization, state devolution, and fiscal federalism, we contend that the 40 percent threshold may not provide a suitable representation of the region’s poverty conditions. Thus, in what follows, we provide an empirical analysis of the region’s poverty landscapes and their implications for the continued use of this measure in poverty research. Empirical Focus and Methodological Approach The southern California region is an appropriate area in which to examine the changing face of poverty, due to recent economic, social, and demographic transformations, as well as the area’s polycentric spatial form. Similar to other areas of the United States, during the 1970s and 1980s, the region experienced significant modifications in its economic structure due to increasing globalization of the economy, attendant deindustrialization and reindustrialization of key sectors, and the rise of the service sector (Soja and Scott 1996; Dear, Schokman and Hise 1996; Wolch, Pastor, 115 Joassart-Marcelli and Dreier, forthcoming). Unlike other areas of the nation, however, the region also experienced a significant increase in the production of non-durable and craft-based goods including furniture and textiles. These structural transformations have significantly altered metropolitan labor markets, as positions traditionally occupied by the middle-class, were replaced by low- wage, non-unionized jobs and high-skill, high-wage positions, contributing to severe income polarization, particularly in Los Angeles County (Wolch et al. 2004). Meanwhile, a globalizing economy has rendered southern California a major destination for international labor migration flows. The region’s burgeoning levels of poverty and inequality are characterized by a rapidly growing working-poor population. Largely comprised of Latinos and recent immigrants of other national origins, these individuals occupy many of the newly created low-wage positions in the manufacturing and service sectors. Changes in the region’s economic, social, and demographic composition have, in turn, guided changes in its physical landscape, including residential patterns and the formation of new clusters of economic activity. For example, more affluent, predominantly white residents have gradually relocated to outlying suburban and exurban areas. The majority of the region’s economic activity has suburbanized in a similar fashion, leaving older urban areas with an increasing share of low-wage jobs. Meanwhile, lower-income, predominantly minority residents often remain concentrated within older inner-city and inner-suburban areas and continue to suffer from spatial, as well as skills “mismatches” (Pastor and Marcelli 2000). 116 This study utilizes field-based methods and data from the 2000 Census to explore the social and physical conditions found in areas historically identified as “high poverty” or “extreme poverty” neighborhoods. We examine the relevance of the 40 percent criterion, focusing on both the census tract and city scale of analysis in recognition that suburbs as well as inner cities increasingly share the impacts of concentrated poverty. First, 30 of Los Angeles County’s inner-ring suburbs were selected for analysis. Many of these have high poverty rates, but are located outside of the county’s central city (Los Angeles), and are therefore useful for testing the implications of utilizing the 40 percent threshold. We then calculated the Concentration Index (a segregation index used to measure the ratio of poor people that reside in extreme poverty areas) to provide concentrated poverty rates for the years 1990 and 2000 and to illustrate changing patterns of concentrated poverty during the 1990s. Each city was grouped into one of four quadrants based on their 2000 concentrated poverty rate and the growth/decline in rate change that occurred between 1990 and 2000 (Figure 3.1). One city was selected from each quadrant for in-depth comparative analysis - Monterey Park, Cudahy, Long Beach, and Baldwin Park - to ensure a solid cross-section of inner-suburban areas in various economic conditions and experiencing different economic trajectories. Next, census tracts within each city with concentrated poverty rates greater than 40 percent were identified (16 in total). Unlike traditional studies of neighborhood poverty, we adopted an alternative poverty threshold based on 150 percent of the official benchmark. While the debate surrounding the inadequacy of the official poverty index 117 has been well-publicized 5 our usage of this alternative threshold is warranted given the increased cost of living incurred by southern California residents - the most salient being housing costs. (ACCRA 2004). Further, this particular threshold has been adopted by researchers to analyze conditions of inequality associated with metropolitan growth in Los Angeles (Southern California Studies Center 2001), as well as the general effects of race and poverty (Montgomery et al. 1996). However, in order to compare findings with those of others, we also report on the share of households in our selected tracts that fall below the 100 percent of the official poverty threshold (Table 3.1). 5 As defined by Ricketts and Sawhill (1988) Figure 3.1:Concentrated Poverty Quadrant Analysis – Inner Suburban Municipalities, 1990-2000 Figure 3.1 – Concentrated Poverty Quadrant Analysis, 1990 - 2000 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50 0.60 1990-2000 - Decline/Growth In Concentrated Poverty 2000 Concentrated Poverty Levels - Low/High Baldwin Park Carson Compton Cudahy Downey El Monte Glendale Hawaiian Gardens Hawthorne Huntington Park Inglewood Long Beach Lynwood Montebello Monterey Park Pasadena Rosemead San Fernando South El Monte Bell Gardens Median = .33 Low/Declining High/Declining High/Increasing Low/Increasing Note: The remaining 10 cities demonstrated concentrated poverty rates of 0 in 1990 and no change in 2000 Source: 1990 & 2000 Census 118 119 Table 3.1: Comparison of Selected Tracts Using Alternative Definitions of 150% and 100% of Poverty Finally, diverging from the many studies that simply employ the 40 percent threshold, and building on previous research on poverty neighborhoods, characteristics that have been commonly associated with “high” or “extreme” poverty neighborhoods were selected and measured. We attempt to ascertain whether or not the 40 percent neighborhoods meet these criteria and, thereby validate the myriad assumptions regarding the physical conditions of ‘extreme poverty areas’, as well as behavioral deviance of residents living within such neighborhoods. The social and economic characteristics evaluated are based upon research conducted by Ricketts and Sawhill (1988). These researchers defined an “underclass” – City/Tract 150% of Poverty (Individuals) 100% of Poverty (Individuals) 100% of Poverty (Households) Baldwin Park 4047.01 40.7 26 24.7 4047.03 46.9 28 21.9 4051.02 41.8 25 23.4 Cudahy 5343.01 50.1 32 28.1 5343.02 43.3 27 26.3 5344.04 58.6 33 30.8 5344.05 53.7 32 31.8 5344.06 45.1 24 23.5 Long Beach 5752.01 65 50 42.5 5752.02 67.3 48 48.3 5764.01 71.6 49 47.3 5764.02 67.2 44 40.4 5764.03 69.8 51 45.2 Monterey Park 4817.12 42.4 24 19.5 4817.14 47.4 24 24.3 5304 46.9 35 29.3 120 and thus socially deviant – areas as any census tract with high proportions (one standard deviation above the U.S. mean) of unemployment 6 , high school drop-outs, welfare recipients, and female-headed households (Table 3.2). Table 3.2: Definition of Underclass Behaviors (Ricketts and Sawhill 1988) High School Dropouts The proportion of 16-19 year olds who are not enrolled in school and are not high school graduates. Unemployment The proportion of unemployed males 16 and older. Welfare Recipients The proportion of households receiving public assistance income. Female-Headed Households The proportion of households headed by women with children under 18. Moreover, they asserted that “extreme poverty areas can reasonably be used as a proxy for concentrations of social problems” (p. 322). Following an analysis of all U.S. tracts, the sum, mean, standard deviation, and upper threshold for high proportions of each behavioral category were calculated. Additionally, in order to provide a more detailed assessment of poverty concentration, as well as a greater comprehension of the changing topography of poor areas in the region, tract profiles (Tables 3.3 – 3.5) were constructed to highlight demographic, socio-economic, and housing characteristics within each study area. These profiles are utilized to aid in the discussion of findings. 6 see Orchansky 1978; Levitan and Shapiro 1987; O’Hare et al. 1990; Ruggles 1990, 1991; Schwarz and Volgy 1992; Fisher 1992, 1992; Citro and Michael 1995; Joassart-Marcelli and Wagle 2005 121 Table 3.3: Demographic Profile for Selected Concentrated Poverty Tracts Table 3.4: Socioeconomic Profile for Selected Concentrated Poverty Tracts Table 3.3 City Total Population % Poor %White %Black %Latino %Asian Median Age % Foreign-Born County Median 9,519,338 29.8 30.9 0.09 44.5 11.8 32 36.2 Baldwin Park 4047.01 5,786 40.7 4.2 2.2 83.3 9.6 26.7 48.4 4047.03 3,595 46.9 6 0 90.1 3.7 23.2 44.4 4051.02 4,881 41.8 7.4 1.7 75.4 13.8 28.2 55.2 Cudahy 5343.01 4,533 50.1 6.4 0 93.4 0.13 24.7 54.3 5343.02 3,927 43.3 1.4 0 94.7 2.2 22.2 54.8 5344.04 3,875 58.6 5.3 0.67 92.4 1 24.5 50.9 5344.05 4,435 53.7 5.6 0.18 93.3 0.85 23.5 51.1 5344.06 4,463 45.1 3.8 0 94.9 0 22.8 57.8 Long Beach 5752.01 5,085 65 3.8 21.4 42.5 23.6 24.9 43.6 5752.02 5,347 67.3 1.4 5.7 55.4 31 21.7 52.6 5764.01 5,066 71.6 4.7 10.2 59.6 21.6 20.2 48.4 5764.02 5,575 67.2 5.3 9 62 22.2 21.9 50.5 5764.03 6,082 69.8 7.7 14.8 53.9 19.4 22.2 46.6 Monterey Park 4817.12 5,273 42.4 3.5 0.17 21.1 70.8 35.9 70.3 4817.14 2,478 47.4 3.3 0.8 13.3 81.5 41.4 71.2 5304 3,853 46.9 4.9 2.7 76.6 13.7 33.4 33.3 Demographic Profile for Selected Concentrated Poverty Tracts City Median Household Income Median Per Capita Income % High School Graduates % Employment in Manufacturing % Employment in Retail Trade % Unemployment County Median $42,189 $20,683 18.8 14.8 10.5 8.2 Baldwin Park 4047.01 $37,847 $9,139 19.4 28 14.2 7 4047.03 $30,875 $9,622 21.7 30.2 8.9 12.1 4051.02 $33,810 $11,663 17.5 25.6 7.1 9.4 Cudahy 5343.01 $29,921 $9,482 16.5 34.7 8.5 12.7 5343.02 $34,679 $9,791 13.9 23.2 7 13.3 5344.04 $24,784 $7,746 16.9 23.7 8.8 10.7 5344.05 $24,786 $7,036 15.8 33.2 9 9.3 5344.06 $29,079 $7,689 16.2 38.9 10.3 8.4 Long Beach 5752.01 $19,388 $8,741 21.4 20.4 15.8 18.1 5752.02 $20,924 $6,000 12.1 28.6 8.7 18.6 5764.01 $18,285 $6,453 17 15.9 8 15.9 5764.02 $21,198 $6,811 15.6 16.9 15.5 23.4 5764.03 $19,122 $8,140 17.8 18.4 9.6 19.8 Monterey Park 4817.12 $26,136 $12,987 21 22.5 11.3 6.4 4817.14 $22,174 $10,074 13.8 23.5 12.3 10.3 5304 $24,630 $10,763 20.1 8.9 12.3 16.8 122 Table 3.5: Housing Profile for Selected Concentrated Poverty Tracts Similarly, the physical conditions present within each of the selected neighborhoods were observed. Adding to the negative depictions of 40 percent neighborhoods, Jargowsky (1997) concluded that they “tended to have a threatening appearance, marked by dilapidated housing, vacant units with boarded-up windows, abandoned and burned-out cars, and men ‘hanging out’ on street corners” (p. 11). These broad generalizations ignore the differentiation of poor areas and continue to perpetuate negative images, while guiding popular beliefs and policy about such areas. Further, the extremely pervasive nature of the 40 percent benchmark within urban poverty and social science research requires more detailed fieldwork, particularly within a society that is becoming increasingly “globalized”. Therefore, this represents a more useful and City % Homeowners Median Home Value Gross Rent/Income Ratio 50% or More % of Households w/4+ People County Median 50.1 $201,400 21.6 14.8 Baldwin Park 4047.01 70.6 $136,900 24.6 67.8 4047.03 40.1 $137,200 31.2 64 4051.02 50.9 $127,200 23.7 65.1 Cudahy 5343.01 14.9 $102,100 19.6 61.4 5343.02 16.8 $160,200 21.6 75.6 5344.04 22.7 $104,200 20.8 61 5344.05 11.3 $146,700 25.2 68.2 5344.06 9.5 $197,700 20.1 72.2 Long Beach 5752.01 23.3 $128,400 17.5 48.9 5752.02 20.1 $153,500 29.5 63.3 5764.01 11.1 $155,400 31.7 58.7 5764.02 17.6 $151,000 34.7 58.7 5764.03 11 $125,800 30.6 55.4 Monterey Park 4817.12 30.2 $187,500 21.2 41.3 4817.14 24 $184,500 31.6 32.4 5304 37.1 $169,700 14.2 36.8 123 informative methodology, rather than the use of arbitrary thresholds or broad generalizations. To that end, a series of investigations, including observation of the condition of the existing infrastructure, public services, and economic activity was conducted in an attempt to examine the validity of the aforementioned conclusions. Through the empirical investigation, all tracts were visited at various times of the day and night to ensure accurate observations. Additionally, city planning department staff members were interviewed in order to learn more about the specific dynamics of the study areas. 7 In the following section, the results of the two-fold analysis are presented. The Differentiation of Concentrated Poverty Neighborhoods in Los Angeles The analysis revealed that clusters of tracts in each city differed from each other in important respects, and their landscapes did not always conform to expectations of dilapidation and social dislocation as suggested by the concentrated poverty or ‘underclass’ literatures. Contrary to the assertions of Ricketts and Sawhill (1988), only two of the16 tracts had scores that were one standard deviation above the mean on all four indicators – Tracts 5343.02 (Cudahy) and 5752.01 (Long Beach) (Table 3.6). 7 As defined by Ricketts and Sawhill (1988) 124 Table 3.6: U.S. Tract Analysis of Concentrated Poverty Characteristics Cudahy’s Tract 5343.02 is characterized by a population of very young Latinos (94%) half of whom are foreign-born. While it possessed a relatively low rate of concentrated poverty (43% based on the 150 percent poverty threshold) and a relatively high per capita income level, this tract possessed an extremely low percentage of both high school graduates and residents employed in retail trade and suffered from a relatively high level of unemployment. Additionally, despite demonstrating one of the highest median home values in the entire sample, the vast majority of the residents are High Proportions 0.20 0.26 0.08 0.09 Cudahy 5343.01 0.14 0.12 0.06 0.11 5343.02 0.20 0.32 0.08 0.13 5344.04 0.18 0.20 0.05 0.16 5344.05 0.16 0.15 0.06 0.11 5344.06 0.22 0.19 0.04 0.16 Baldwin Park 4047.01 0.10 0.05 0.05 0.14 4047.03 0.11 0.23 0.06 0.12 4051.02 0.11 0.11 0.07 0.08 Long Beach 5752.01 0.24 0.28 0.08 0.19 5752.02 0.24 0.21 0.07 0.27 5764.01 0.32 0.14 0.06 0.35 5764.02 0.27 0.19 0.12 0.24 5764.03 0.34 0.18 0.11 0.34 Monterey Park 4817.12 0.08 0.12 0.03 0.14 4817.14 0.08 0.00 0.06 0.16 5304 0.19 0.07 0.12 0.16 % Female Headed Households % High School Dropouts % Unemployment % Welfare Recipients 125 renters - further complicating matters. The majority of the households (75%) are large and rent-burdened 8 . Tract 5752.01 in Long Beach paints a different picture. This tract is home to a substantial Latino population (42.5%), but contains significant percentages of Asians and Blacks, as well. The population is young, and has a lower share of immigrants than all but one other tract in our sample. Although it possesses one of the highest percentages of high school graduates, the concentrated poverty rate is much greater (67.3% based on 150 percent of the poverty threshold) and the unemployment rate is the highest in the entire sample, despite having the highest percentage of residents employed in retail trade. Nearly half of the households are large, and while the majority of them are renters, very few have high rent-to-income ratios compared to other tracts in the sample. Similarly, contrary to the findings of Jargowsky (1997), the qualitative assessment (which was supported by planners from the respective inner-suburban areas) revealed few if any dilapidated or abandoned housing structures, burned-out cars, and loiterers wandering the streets. Our sample of 40 percent neighborhoods possessed a range of urban life, including some run-down housing and streetscapes, but also enjoying well- maintained (and in some cases newly developed) housing, safe, well-paved streets, the presence of franchise commercial and retail businesses similar to those found throughout the region, as well as “mom and pop” establishments, extensive public transportation networks, and well-maintained outdoor parks and public recreation areas. 8 see Orchansky 1978; Levitan and Shapiro 1987; O’Hare et al. 1990; Ruggles 1990, 1991; Schwarz and Volgy 1992; Fisher 1992, 1992; Citro and Michael 1995; Joassart-Marcelli and Wagle 2005 126 These findings about inner suburban poverty landscapes call into question the ability to use popular opinion or the 40 percent threshold to identify ‘extreme’ poverty areas that fit stereotypical notions of the inner city ‘ghetto’ and associated behavioral pathologies believed to characterize such places. In what follows, we briefly sketch out the heterogeneous landscapes of these ‘extreme poverty’ neighborhoods. GIS maps (Figures 3.3 – 3.5) are utilized to highlight the spatial distribution of four specific variables: poverty, the relationship between race and poverty, unemployment, and immigration. Baldwin Park The Baldwin Park census tracts meeting the 40 percent threshold are home to a population largely comprised of Latinos who are relatively young and native-born. The tracts demonstrated the highest median incomes in the entire sample and relatively high per capita incomes, as well. Meanwhile, unemployment rates were relatively high with two of the three tracts (4051.02 and 4047.03) having levels greater than the county median. Finally, households are large and, despite having relatively low median home values and the highest rates of homeownership in the entire sample, it is home to a significant number of rent-burdened households. The selected tracts in Baldwin Park demonstrated a greater variety of lower- density housing than other tracts in our sample. The dwelling stock was comprised mainly of small apartments and modest single-family homes of various sizes. Most structures were well maintained and had lawns that were nicely manicured, although 127 some were unkempt. The streets were well paved and a number of development projects were in evidence, including additions to some of the homes. During our visit we observed residents of various ages enjoying themselves at the local park and several strip- malls that offered a variety of establishments, including a Blockbuster Video store, fast food restaurants, ninety-nine cent stores, laundry mats, and small “mom and pop” retail stores accessible by bus. Cudahy Less racially balanced than Baldwin Park, the selected tracts in Cudahy are dominated by younger Latinos, half of whom were immigrants. These tracts demonstrated the second-highest median household incomes and per capita incomes, as well as the highest percentages of residents employed in the manufacturing industry in the sample. Still, the tracts house the most poorly educated residents in the entire sample, greater than average unemployment rates, and the lowest rates of homeownership. Finally, household sizes are some of the largest in the sample of fourteen tracts. And despite extreme variations in median home values the area is home to a significant percentage of rent-burdened households. In Cudahy, we discovered the presence of high-density housing, including small apartments, small single-family residential structures and mobile homes – many of which had their front doors open – speaking to the perceived safety of these neighborhoods. Further, we witnessed residents, including families, walking the streets, playing in the local park and enjoying themselves at a local fair. Finally, we identified several 128 commercial, retail, and service establishments present and being frequented by neighborhood residents. These included Kaiser Permanente and Downey Bank, as well as a Super K-Mart, Big Lots, several strip-malls, and a variety of fast food restaurants that were accessible by bus. Long Beach Of the 14-tract sample, the cluster in Long Beach is the most racially diverse and disconnected from the formal labor market. In addition, the population is very young and largely foreign-born. These tracts were also the poorest of the entire sample, and fell into the ‘concentrated poverty’ category regardless of which poverty threshold (100 or 150 percent) was used. Consistent with these characteristics, the tracts possessed the lowest median household and per capita incomes, as well as the greatest percentage of unemployment in the entire sample. Finally, the area demonstrated low rates of homeownership as well as the greatest concentration of rent-burdened households in the entire sample. The selected tracts in Long Beach contained numerous single-family homes and apartment buildings. Unlike the other clusters of tracts, and consistent with its deeper poverty, this particular area suffered from declining infrastructure (poorly paved streets, sidewalk debris, and poorly lit, dirty alleys). Moreover, the economic well being of these neighborhoods is constrained, as indicated by the presence of low-end jewelry stores, and small “mom and pop” markets, ninety-nine cent stores, restaurants (fast food and sit- down), and laundro-mats. However, we did observe a well-maintained library and adjacent park that was sufficiently lit and regularly utilized by area residents. 129 Monterey Park The selected tracts in Monterey Park presented stark contrasts in race and immigrant status. Two of the tracts were largely comprised of foreign-born Asians, while the remaining tract was primarily comprised of native-born Latinos. Median ages were far higher than the county median, reflecting the fact that many younger immigrants have been united with their parents and older relatives. Although median household incomes were significantly lower, the tracts had the lowest percentage of poverty (100 percent) and the highest per capita income levels in the entire sample. Given relatively small shares of large households, this suggests a somewhat more affluent population, fewer of whom need to crowd into large households and pool income in order to make ends meet. Education and housing characteristics support this picture, as the area possessed percentages of high school graduates greater than the county median, higher homeownership rates, significantly higher median home values (by comparison to others in the sample), and lower percentages of rent-burdened households. Monterey Park’s landscape was consistent with this picture of an older, slightly more affluent area. We observed a wide variety of housing structures in close proximity, including apartment buildings on deep lots, smaller well-maintained homes, and beautiful, newly built homes. Meanwhile, some homes were in need of repair. While none of the streets were poorly maintained, some looked as if they had been recently paved. A wealth of commercial establishments existed, including restaurants, medical centers, pharmacies, small businesses (cellular phone stores and hair salons), banks (Union Pacific, Citibank, Bank of America), grocery stores, academic assistance centers, 130 and travel offices – all accessible via an expansive public transportation system that included three different types of buses. Further, we observed residents of all ages, including the elderly, walking about the area and enjoying themselves at a large, well- maintained park/public recreation center. Figure 3.2: Percent Concentrated Poverty within Selected Municipalities 131 Figure 3.3: Percent Foreign-Born Population within Selected Municipalities 132 Figure 3.4: Percent Unemployment within Selected Municipalities 133 Figure 3.5: Percent Race/Poverty within Selected Municipalities 134 135 Chapter Three Conclusion and Suggestions for Future Research Traditional methods of poverty measurement and resulting conceptualizations of impoverished neighborhoods are based upon a Midwestern/Northeastern-based model that emphasizes the misfortune of African Americans trapped in declining inner cities (Wilson 1987; Myers 2002). However, concentrated poverty is a geographic phenomenon that is dependent upon place-specific local and regional forces (Kodras 1997; Cooke 1999) as well as broader economic forces situated at the nation-state and global scales. The results of the quantitative analysis and field-based research conducted reveal robust empirical findings that illustrate the changing landscape of concentrated poverty neighborhoods, as well as their increasing differentiation (Jargowsky 2003). More specifically, findings challenge long-standing assumptions regarding the ‘urban’ nature of the concentrated poverty phenomenon as well as its ties to ‘underclass’ populations. Additionally, they challenge the use of traditional poverty measurement tools - namely the 40 percent threshold - to denote neighborhoods of ‘extreme’ poverty, concentrations of social ills, and the physical make-up of such areas. Additionally, the quantitative analysis empirically demonstrated that “40 percent” neighborhoods are not, in fact, disproportionately home to residents with dysfunctional behaviors or social ills. In doing so, we challenge the assertion of Ricketts and Sawhill (1988) that such neighborhoods “are proxies for social problems” (322). Instead, within a globalizing region such as Southern California, such neighborhoods may illustrate the 136 effects of attendant economic and demographic restructuring processes, characterized by immigrant populations (both young, and older immigrants reunited with families), and a growing number of low-skill, low-wage, nonunionized employment positions necessary to support burgeoning manufacturing and retail sectors linked to global trade and local- service industries. Not surprisingly, these types of communities share low homeownership rates, crowded housing, and high rent-to-income burdens. Finally, the extensive analysis of the selected 40 percent tracts underscores the inability of this particular measure to highlight emerging trends in the landscape of concentrated poverty. Baldwin Park and Cudahy were characterized by large immigrant Latino households, many of whom are supported by young, poorly educated individuals, trapped in low-skill, low-wage manufacturing and retail employment positions. Due to a long-standing housing crisis, such households faced significant housing burdens. Despite significantly greater levels of racial diversity (Blacks, Whites and Cambodians), and higher unemployment rates (suggesting a deeper spatial/skills mismatch and/or inability of Cambodian refugees to obtain jobs), the tracts in Long Beach demonstrate similar characteristics. Meanwhile, Monterey Park was home to an older, predominantly Asian, immigrant population, as well as an older, native-born Latino population. Despite differences in race and educational attainment, many of these residents work full-time, but are unable to obtain enough income to rise above the poverty threshold. These are all stories of working poverty that stand at odds with the picture painted for more than two decades by research using the 40 percent measure. 137 What does this analysis suggest with respect to future research? There are four areas that warrant closer scrutiny by those concerned with understanding the emerging landscape of concentrated poverty. First, the inadequacies embedded within the current quantitative methods of poverty measurement suggest that, used alone, such measures depict only a portion of the range of ‘urban life’ that exists within poverty neighborhoods. In particular, the 40 percent threshold conjures notions of geographic spaces marked by blighted and decayed structures lining barren streets and occupied by residents (typically African American) afflicted with dysfunctional behaviors. We have demonstrated that this is misleading. Moreover, it also represents a “hands-off” approach to poverty measurement based upon simple assumptions, rather than nuanced empirical research and fails to capture the specific politics of place or everyday lived experiences in such spaces. Such false portrayals often lead to the formation of negative perceptions (e.g., the ‘urban underclass’) that are long lasting and difficult to overcome. Future research should involve the use of a mixed methodology incorporating not only quantitative measures, but also qualitative techniques to substantiate research findings. Such techniques may involve ethnographies, including the use of field notes as well as interviews with community leaders and residents, structured observations and visual methods such as photography. Used in tandem with quantitative methods, such techniques may be better suited to capture and articulate the specific factors associated with newly evolving patterns of concentrated poverty. 138 Second, the term ‘urban underclass’ has been employed to describe the poorest poverty populations and, more importantly, as a racial code word (Gans 1990, Katz 1993). However, the results of this study should divert scholars’ attention from individual-level behaviors and, instead, direct it toward the presence of the underlying structural catalysts for poverty. These include shifts in the global economy, related immigration trends, and the rise in low-wage, non-unionized employment opportunities that together have resulted in a burgeoning working-poor population. Recognizing these catalysts, research should connect specific policies commonly associated with globalization and neoliberal austerity to conditions of severe geographic unevenness. While there is a growing body of literature that offers theoretical and abstract notions of various facets of global economic restructuring, including the emergence of the ‘informational’ economy (Castells 1998, 1999) and ‘global’ cities (Sassen 2001, 2002), we need to begin speaking of the explicit ways that such phenomena manifest themselves in the increasingly heterogeneous landscapes of U.S. cities. One such example might focus on the relationship between economic restructuring and employment processes at the local level. The well-publicized argument offered by Wilson (1987) emphasized that increasing levels of poverty concentration within poor neighborhoods were highly correlated with decreasing employment opportunities, as deindustrialization severely restricted the number of blue- collar/manufacturing positions available to local residents. However, our research reveals that this particular line of reasoning does not apply in the case of southern California, and, quite possibly, other ‘globalizing’ regions. Such findings emphasize the 139 need to better comprehend the ways that local labor markets interact with concentrated poverty neighborhoods. Third, while this research has utilized both place and people-based perspectives in our investigation of the selected concentrated poverty tracts, Los Angeles remains a major immigrant destination. Therefore, many of the residents for whom socio-economic characteristics were obtained were immigrants living in specific places at a specific time. However, foreign-born residents often improve their economic and housing circumstances and relocate to better neighborhoods (Myers 2002). Future research should examine the various policy implications that accompany an explicit focus on the residents of concentrated poverty neighborhoods over time. Lastly, recent research has discussed the correlation between increasing poverty levels and costs associated with the provision of municipal expenditures, such as police, fire, etc. (Pack 1998). In view of welfare reform and devolution, this emphasizes the ever-increasing burden faced by inner cities and inner-suburban areas and counties to address such indirect or ‘uncompensated’ costs (Joassart-Marcelli, Musso and Wolch, 2005). Future research, therefore, should investigate the distribution of concentrated poverty at varying spatial scales – not just the census tract. Rather, we need to understand how varying concentrated poverty landscapes impact those jurisdictions that bear either the de jure or de facto responsibility for the health, safety, and welfare of residents, as well as the impacts on entire metropolitan regions and their inner city, inner suburb, and outlying areas. 140 CHAPTER 4  How the Other Half Lives: An Analysis of Concentrated Affluence  Neighborhoods in Los Angeles County  Rethinking Affluence, Rethinking Concentration Recent research has reinvigorated interest in concentrated poverty, calling into question previous conceptualizations, patterns of spatial distribution, methods of measurement, and racial foci (Jargowsky 2003, Kingsley and Petit 2003, Joassart- Marcelli et al. 2005, Jargowsky and Yang 2006, Strait 2006, Sessoms and Wolch 2008). Given the emergence of globalization and attendant economic and demographic restructuring, these studies represent attempts to move the discipline forward in several important respects, as conventional notions regarding inequality now lag behind present- day realities. Unintentionally, they may also illuminate landscapes of concentrated affluence as well. Historically, urban studies of inequality have been one-sided, focusing solely upon poverty concentration, as well as perceived notions of social dysfunction and physical dilapidation that have often been associated with it. However, when viewed in tandem with poverty concentration, the negative aspects associated with affluence concentration become evident as well. While poverty segregation results in such negatives as decreasing tax-bases, dilapidated housing, commercial disinvestment, under- performing schools, and poor municipal services, affluence concentration often translates into an accumulation of political power, quality housing, employment opportunities that are abundant and often pay a living - if not substantial - wage, educational opportunities, and the availability of desirable amenities, such as parks, libraries, and grocery stores, as 141 well as the ability to secure vital resources, such as fire and police protection. Here I wish to argue that the notion of well-to-do residents enjoying such benefits is not problematic. However, their polarization is, as it often leads to the exclusion of those who are less fortunate and, therefore, cannot take advantage of such opportunities. Moreover, as housing becomes exclusionary and property taxes increase, social concerns diminish, and with them, the idea of creating equitable regions, characterized by affordable housing and greater levels of citizen responsibility for support of individuals set adrift by the market. The failure of researchers to recognize affluence concentration as “a dimension of power and privilege that is significant in the geographic structure of place” (Shaw 1997, p. 546) has, in turn, stunted our understanding of inequality in general, as well as our level of familiarity with the affluent, their behavior and the specific way(s) in which affluence and wealth become segregated. Given increasing levels of economic polarization that occurred within a number of regions across the U.S during the 1990s, as shown in Chapter 3, affluence concentration represents a topic that is worthy of our attention for several reasons. First, research has suggested that it plays a central role in the creation and maintenance of poverty concentration (Massey and Eggars 1990). For example, during the 1990s, poverty concentration decreased within the Midwestern and Southern areas of the US, while increasing within the Northeast and West (Jargowsky 2003, Kingsley and Petit 2003). However, just as startling was its dramatic increase within suburban areas. To that end, during this time-period, affluent households may have sought to isolate themselves in response to crime, decreasing property values, and an increasing poverty population, 142 comprised of Blacks, Latinos, and other residents of color, including recently arrived immigrants. From a policy perspective, this and related scenarios may signify the need for stronger inclusionary housing policies, housing tax bonds, and regional governance in order to ensure the equal distribution of resources - housing, education, employment, municipal services, green space - and economic opportunities throughout entire metropolitan areas. Second, given our lack of understanding of the behavioral patterns of the affluent, we know very little about affluent landscapes and in particular, their physical and social composition. Chapter 4’s analysis indicated that neighborhoods are diverse and hence poverty itself is not a monolithic phenomenon, and that conceptualizations of ‘concentration’ must be flexible and rely upon more nuanced empirical research in order to diminish the possibility of misrepresentation. Along these lines, and given the lack of research focused on these particular landscapes and populations, our assumptions - which are largely derived from anecdotal accounts and the media - regarding neighborhoods of concentrated affluence as well as local residents may very well be inaccurate. For example, such areas may demonstrate geographic differentiation and increasing population diversity given the changing nature of poverty concentration within adjacent suburban communities. To that end, conventional notions of what constitutes an upscale community may warrant modification. In an attempt to increase our overall understanding of affluence segregation and, in particular, the ways in which it is derived and maintained, this chapter’s analysis examines selected landscapes of concentrated affluence within the Los Angeles 143 metropolitan area. More specifically, it will address the following research questions: Are indicators of defensiveness and protection present within landscapes of affluence concentration? Finally, are places that are characterized as ‘affluent neighborhoods’ congruent with popular perceptions of such areas (as portrayed in affluence/ affluence concentration literature)? More specifically, how do the physical environments of these places and social profiles of their residents compare with traditional conceptualizations? I begin by reviewing bodies of literature which focus on various aspects of affluence, including its spatial distribution and its increasing concentration, as well as affluent landscapes and residential defensiveness. Following a brief discussion of the empirical context and methodological approach utilized, I present the neighborhoods selected for detailed investigation. Next, I share the results of the multifaceted analysis, which reveals that neighborhoods of affluence concentration are complex and differ in several important respects. Therefore, our perceptions of their physical landscapes and social compositions are in need of revision. Finally, I suggest areas for further research. Understanding Affluence, Concentration, and Defensiveness Despite the fact that scholars have confirmed both the long-standing concentration of affluence, as well as its increase over the past 25 years (Goldstein 1986, Kahan and McKeown 1986, Ropers 1991, Devine et al., 1992, Massey and Eggers 1993, Jargowsky 1997, Fischer 2003, Lee and Marlay 2007) little research has focused on the catalysts, spatial distribution, and social ramifications associated with this phenomenon. Two reasons in particular can be offered to explain this paucity. 144 First, from an empirical standpoint, analyzing affluence and affluence concentration has been and remains an arduous task, due to the lack of data available. Unlike poverty, there are no thresholds for affluence provided by the U.S. Census, nor does a federally defined benchmark for affluence exist. To that end, previous research has often relied upon several quantitative techniques in order to derive a suitable definition, including the use of family-income designations (e.g. multiplying the median household income for a family of four by a given multiplier - 2, 3, 4, etc.) and the utilization of poverty threshold multipliers (e.g. income levels that are equal to 300%, 400%, 500%, etc. of the poverty threshold) to estimate levels of affluence. But such measures of affluence are just approximations, because affluence itself is largely subjective and is not grounded in any notions of basic needs as are definitions of poverty. Additionally, the existence and further perpetuation of long-standing notions such as the ‘American Dream’ demonstrate the reverence that wealth and fiscal integrity have been afforded in the United States. Along these lines, the terms affluence and affluence concentration carry with them notions of economic stability, social well-being, and power, which imply that all is right in the world and no research is actually needed (Shaw 1997). Congruent with this line of thinking, research on affluence and affluence concentration, in particular, and its role in creating and maintaining conditions of inequality have been constrained by the common doctrine of ‘personal responsibility’ which promotes the idea that individuals are responsible for their own socioeconomic circumstances. Through this way of thinking, affluence - as well as its recompenses - are 145 earned and, therefore, justified. This, then, often becomes the focus, rather than the social costs that the non-affluent must bear as a result. Despite both a lack of empirical data and the pervasive nature of the aforementioned perspectives, however, the recent expansion of concentrated poverty into inner-suburban areas demonstrates that the affluent, their behavior, as well as suburbs and exurbs are indeed critical to our understanding of conditions of inequality and economic polarization, in particular. Therefore, such notions regarding this phenomenon, as well as its spatial segregation are open to question. Early research on affluence promoted broad generalizations about regional economic standing in the United States (e.g. the wealthy, industrializing North versus the impoverished, agrarian South (Smith 1972, Shaw 1997). Meanwhile, additional studies emphasized the presence of wealthy residences in the Northeast and on the West Coast (Zelinsky 1980, Wyckoff 1990, Higley 1995) and examined the differences between wealthy suburbs and impoverished inner-cities (see Shaw 1997). However, more recent analyses of affluence have focused on its increasing spatial concentration via studies of the largest metropolitan areas of the United States. In particular, these works have highlighted two broad themes including its geography (Shaw 1997, St. John 2002, Lee and Marlay 2007) and its relationship to poverty concentration (Massey and Eggers 1993, Massey 1996, Coulton et al 1996). The first analysis of affluence concentration posited that, during the 1970s, it became more concentrated and that locations of concentrated affluence neighborhoods became more dispersed than the concentration of poverty. These researchers posited that 146 conditions of economic polarization were common within many of the nation’s largest metropolitan areas, characterized by increasing levels of poverty in the New York Metro- area due to immigration and increasing levels of affluence in the Sun Belt (Houston, Phoenix, Tampa) due to the energy boom. These findings are particularly insightful and demonstrate that both affluence concentration and broader conditions of economic polarization are not new phenomena, and - much like poverty concentration - levels of affluence concentration vary depending on local economic, cultural, and political factors. Building upon this work, Massey (1996) proposed that spatial concentrations of both poverty and affluence would bring about the dawning of a “…new ecology of inequality” (p. 410), characterized by the exacerbation of urban social dilemmas (unemployment, crime, drug abuse, etc.), motivating the affluent to continue their outward migration, and perpetuating increased levels of sprawl and suburbanization. Massey’s work highlighted the varied effects of globalization and attendant economic restructuring, as well as their role in the bifurcation of the workforce. In doing so, this research hinted at not only the presence of an interdependent relationship between poverty concentration and affluence concentration, but at specific catalysts that could lead to affluence segregation. Later, geographers Coulton et al. (1996) investigated spatial patterns of poverty and affluence concentration within the largest 100 metro-areas of the U.S. In particular, their analysis explicitly emphasized the issue of race within the dialogue surrounding economic polarization, by revealing its strong correlation to levels of racial/ethnic segregation within the selected metro-areas. This particular study provided new insight 147 regarding the catalysts for affluence concentration. Chief among these were the limited residential choices of Blacks and Latinos, in explaining poverty concentration, and the construction of homogeneously expensive housing developments within suburban and exurban locales, and the suburbanization of the workforce – all of which led to the out- migration of middle and upper-class residents from urban and, more recently, inner- suburban areas. Most importantly, however, these researchers asserted that extreme levels of both poverty and affluence concentration were only present within a small number of cities and - contrary to the assertions of Massey (1996) - no evidence of an interdependent relationship existed. Additional research on affluence concentration has focused on its spatial distribution (Shaw 1997, Lee and Marlay 2007). Focusing at the county level, Shaw’s (1997) analysis revealed that the affluent were predominantly located within metropolitan areas of United States, but that only a handful resided within spatial concentrations. Additionally, with the exception of a large region in the Northeast (Megalopolis), these metro-areas were dispersed throughout the nation. To that end, she argued that spatial concentrations of affluence were derived from both the amount of economic opportunities within metropolitan areas, as well as personal choices made by affluent individuals to segregate themselves from the working-class and high-densities, given their location within certain counties. Meanwhile, in a study more focused solely on concentrated affluence, and measurement techniques in particular, research by Lee and Marlay (2007) emphasized the geographic dispersal of affluent neighborhoods, as well as their concentration within 148 suburban areas of only a small number of large U.S. metro-areas, confirming the findings of Shaw (1997). Also focused on affluence concentration alone, St. John (2002) argued that concentrated affluence was greater in larger US metro-areas where global economic restructuring was reflected in the local employment base. His findings revealed that the specific economic characteristics of metro-areas played a greater role in determining the presence and levels of affluence concentration than income inequality. From a regional perspective, this particular analysis revealed that metro-areas of the Northeast displayed lower levels of concentrated affluence due largely to the lack of economically homogenous dwelling areas. Meanwhile, metro-areas in the Midwest and South demonstrated higher rates of concentrated affluence than the West. Lastly, mean household income was the strongest predictor while racial residential segregation was highlighted as a factor in the rates of concentrated affluence for both African Americans and Whites. While this research reinforced the role of globalization in promoting geographic unevenness, similar to Shaw (1997) it stands in contrast to previous conceptualizations of affluence concentration by emphasizing significant changes in its spatial distribution, while underscoring that - much like concentrated poverty - place plays a significant role in the types and levels of affluence segregation. Despite its common characterization as the polar opposite of poverty concentration, analyses of concentrated affluence demonstrate that these phenomena share important similarities. Just as scholars have tended to implicate globalization and attendant economic restructuring as primary catalysts for both the increasing complexity and changing spatial distribution of poverty concentration, these same factors have 149 induced changes in the spatial distribution of affluence concentration, which is no longer confined to the Northeast, but has instead become geographically dispersed throughout the U.S. as shown by Chapter 3, and St. John 2002. Meanwhile, racial segregation, the suburbanization of employment opportunities, and metropolitan income inequality continue to work together resulting in increased levels of severe geographic unevenness. While the effects of these catalysts, which work at the global and nation-state levels, have been raised within urban geographic and globalization literatures, studies of affluence segregation have also emphasized that such concentrations are developed in-part through the actions of wealthy residents themselves via out-migration from less desirable population areas and zones of higher-densities, and maintained through various acts of residential defensiveness. Such actions include those made by wealthy individuals - the gating of single-family dwellings, subscription to private security patrols, and reliance upon cameras and intercoms - as well as the collective actions of entire neighborhoods to oppose such ventures as the construction of affordable housing units. In response, given the suburbanization of concentrated poverty and perceived threats to property values and, perhaps more importantly, the long-standing social order of suburbanites, the various forms of residential defensiveness may have changed or become more evident. While urban geographic literature has largely ignored the issue of affluence segregation from an empirical perspective, cultural geographers and others have explored the topic of landscape from a theoretical perspective. This work conveys the idea that affluent landscapes are complex, as are the actions of residents who work to maintain 150 their exclusive nature. Moreover, it emphasizes that all landscapes, including those of affluence, are tangible places in which the development and maintenance of local social identities and construction of community values occurs (Lowenthal 1991, Cosgrove 1993, Rose 1995). Over time, affluent communities inhabited by like-minded residents control and govern processes of ingress and egress. As Duncan and Duncan (2004) have asserted that Members of certain types of small, affluent, and relatively homogeneous communities are able to mobilize enough economic and cultural capital to create landscapes that have the power to incorporate and assimilate some identities while excluding or erasing others. (25) Others have placed a considerable amount of emphasis on affluent landscapes as positional goods (Higley 1995, Ley 1993, 1995, Pratt 1981, Wyckoff 1990). These accounts echo Duncan (1973), who commented that the privileged regularly work to decouple status from class, as landscapes become possessions for the wealthy and powerful to control. Through this particular viewpoint, affluent landscapes have been considered important products, particularly within the United States’ Capitalist economy, which privileges material possessions as well as their aesthetic quality, and considers them proxies for personal identities (Harvey 1989, Duncan and Duncan 2004). Finally, affluent landscapes have been viewed as both a psychological and social refuge, given the more recent economic and demographic fluctuations which have accompanied globalization (Harvey 1989, Giddens 1991, Smith 1996). Particularly in the post-911 era, they often serve as zones of stability and perceived safety within which the idea of community might be rediscovered, family values might be reaffirmed, and a familiar way of life might be once again realized. This retreat toward institutions 151 traditionally considered foundational (the family, community schools, and community organizations) has been termed localism as well as “the reactionary politics of an aestheticized spatiality” (Harvey 1989, p. 292). Although it remains arguable whether or not such behavior is malicious in nature, this particular viewpoint offers additional insight into the behaviors and possible rationale of wealthy residents, who - in their attempts to retreat and align themselves with more comfortable and familiar surroundings - also insulate themselves from much of mainstream society as well as many of its harsh realities, including crime, decreasing property values and foreclosures, and poor people, particularly people of color and immigrants. In summary, geographic work on affluent landscapes stands in contrast to their conventional characterization as placid spaces beyond the urban fringe. Instead, it conveys the idea that such places are fluid, contested sites in which residents - both competing and cooperating - struggle to attain identity and status while at the same time asserting power, control, and influence on a daily basis, both on an individual and collective basis via local government action. This battle, however, is rarely apparent to the naked eye, as “…space can be made to hide the consequences from us, how relations of power and discipline are inscribed into the apparently innocent spatiality of social life” (Soja 1989, p.6). However, the role of the federal government and, in particular, federal policies focused on taxation, transportation, and housing must also be included in any discussion of residential defensiveness. In funding the development and growth of the suburbs in the 152 United States (Jackson 1985, Harvey 1989, Oliver and Shapiro 1997, Duncan and Duncan 2004), they subsequently laid the foundation for the current strategies of safeguarding and territoriality within suburban and exurban neighborhoods by providing limited access to homeownership and its many benefits. As a result, people of color and African Americans, in particular, were unable to accumulate homeowner equity, rendering them unable to participate in the process of wealth creation (Jackson 1985). Finally, it should be noted that while gates often serve as indicators of exclusive, wealthy neighborhoods and tangible signs of residential defensiveness, these barriers may not always be physical in nature. Instead, such barriers can also be clandestine in nature (Marcuse 1997). However, the analysis presented in this chapter seeks to extend this assertion further by demonstrating that the same may hold true for neighborhoods of extreme affluence – adding another layer of complexity to the conceptualizations previously discussed. In the following sections, an empirical analysis of concentrated affluence landscapes in Los Angeles is presented. Empirical Context and Methodological Approach Recent research has asserted that the LA metropolitan area is the most polarized in the nation, with less than one-third of its neighborhoods belonging to the middle-class (LA Times 2006) Comprised of the largest population of billionaires of any region in the country, it is also home to one of the nation’s largest working-poor populations, resulting in conditions of severe economic polarization and prompting researchers to comment that "the situation in L.A. is certainly at the extreme of American cities" (p. 3). In response, 153 recent research has investigated poverty concentration in the LA metro-area and southern California region, in general (Wolch et al. 2004, Joassart-Marcelli et al 2005, Strait 2007, Sessoms and Wolch 2008). However, analyses of the area’s wealth segregation have yet to surface. The seeds for the area’s existing landscape of concentrated affluence were sown during the 1970s and 1980s, when the region experienced significant fluctuations in its economic structure. Largely due to increasing globalization of the economy, attendant deindustrialization and reindustrialization of manufacturing, defense, and other employment strongholds, and well the rise of the service sector (Soja and Scott 1996, Schockman and Hise 1996, Wolch et al. 2004). At the same time, however, a significant increase in the production of non-durable and craft-based goods including furniture and textiles occurred - a phenomenon that was unique to the southern California region. As a result, the region’s various employment sectors have been significantly altered, along with its physical landscape, and social and demographic trajectories. Key in this process has been the bifurcation of the regional economy. Within local metropolitan labor markets, positions traditionally occupied by the middle class have been replaced by high-skill, high-wage positions and low-wage, non-unionized jobs (Wolch et al. 2004). Exacerbating matters, in many cases, those employed in low-wage positions, often provide services that allow the affluent to maintain, if not increase, their wealth (e.g. child care, gardening and landscaping, car washing and detailing, etc.). Meanwhile, given its geographic proximity to the Pacific Rim as well as the aforementioned global shifts, the region - long a magnet for the migration of people from 154 other areas of the US - has more recently become a major destination for international migration flows. Largely comprised of Latinos and Asians, the presence of newly arriving immigrants is often linked to burgeoning levels of poverty, signified by a growing working-poor population that often occupy low-wage positions within the manufacturing and service sectors. However, other immigrants (especially wealthy Asians) have been able to utilize their transnational capital to relocate to suburban and exurban areas of the LA region (Li 1998, 1999). These economic, social, and demographic transformations have, in many ways, served as catalysts for transformations in the physical landscape of the region including residential patterns and the formation of new clusters of economic activity. Despite the more recent suburbanization of poverty, lower-income, residents, the vast majority of whom are Black and Latino have remained concentrated within older, inner-city and inner-suburban areas, which have become home to an increasing share of low-wage jobs, and continue to suffer from spatial, as well as skills mismatches (Pastor and Marcelli 2001). Meanwhile, and again, consistent with the suburbanization of the majority of the region’s economic activity, more affluent, predominantly white residents have gradually relocated to suburban and exurban areas at or well beyond the urban fringe. Finally, unlike other large metro-areas that have allowed for and promoted development beyond the urban fringe, the area’s polycentric spatial form has exacerbated conditions of sprawl, resulting in extreme levels of unplanned development within the region’s suburbs and exurbs. It therefore, represents a suitable geographic context in which to perform detailed analysis of burgeoning levels of affluence concentration in particular. 155 This research relies upon field-based methods and data from the 1990 and 2000 Census of Population and Housing to explore both the social and physical environments within neighborhoods characterized by affluence concentration within Los Angeles County. First, all 88 municipalities in Los Angeles County were selected for analysis. Because of the paucity of established metrics for affluence, and consistent with previous investigations, this study defines affluent households as those with income levels that are six (6) times the poverty rate or more for a family of four in 1989 and 1999. This calculation yields cutoff levels of income above which households are considered affluent for the years 1990 ($76,044) and 2000 ($102,174), respectively. The US Census provides household income data by categories only (for ex: $10,000 - $14,999), making it impossible to attain the exact number of households per tract. Therefore, this analysis employs the technique utilized by Strait (2002) in order to calculate the total number of affluent households in each tract within each of the selected MSAs. For example, the 2000 cutoff level of $102,174 falls within the category of $100,000 - $124,999. The linear interpolation assumes that households are distributed evenly on the income continuum. Therefore, given the $25,000 range in that particular category, there should be (124,999 – 102,174)/ 25,000 or just over 91% of the households in that category with income levels above $102,174. To this number I also add the households in the remaining higher income categories ($125K-149,999K, $150K-199,999K, and $200K+) in order to obtain an estimate of the total number of affluent households. The forty percent threshold, which has been widely utilized in analyses of poverty concentration, is employed to determine whether or not a census tract is a concentrated 156 affluence tract. Tract levels of affluence concentration are then aggregated to the MSA level to allow for regional comparisons. Next, the Concentration Index was employed to measure the ratio of affluent households located within affluent census tracts to provide concentrated affluence rates for the years 1990 and 2000, and assess changes in levels of affluence concentration during the 1990s. Each municipality was then grouped into one of four quadrants based on their 2000 concentrated affluence rate and the growth/decline in rate change that occurred between 1990 and 2000 (Figure 4.1). One city was, then, selected from each quadrant for in-depth comparative analysis - Manhattan Beach, Santa Clarita, Diamond Bar, and La Canada Flintridge - and to ensure a solid cross-section of municipalities in various economic conditions and experiencing different economic trajectories. I. Diamond Bar exhibited a below-average and declining rate of concentrated affluence. II. La Canada Flintridge posted an above-average but declining rate of concentrated affluence. III. Manhattan Beach experienced an above-average and increasing rate of concentrated affluence. IV. Santa Clarita was below-average but saw an increased rate of concentrated affluence. Within each of the selected municipalities, tracts with concentrated affluence rates greater than forty percent were selected for detailed analysis. In total, twenty one tracts were selected. Figure 4.1: Concentrated Affluence Quadrant Analysis - Los Angeles County, 1990-2000 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 2000 Affluence Concentration Level - Low/High Percent Decline/Growth in Affluence Concentration (1990-2000) Figure 4.1 - Affluence Concentration Matrix - Los Angeles County, 1990-2000 Median = .20 Note: The remaining 47 municipalities demonstrated affluence concentration rates of 0 in 1990 and no change in 2000 Manhattan Beach Calabasas Walnut Hermosa Beach Santa Monica Inglewood Claremont Pomona Santa Clarita Cerritos Lancaster Palmdale Duarte Monrovia Diamond Bar Arcadia Whittier Burbank Long Beach West Covina Redondo Beach Rancho Palos Verdes La Canada Flintridge Westlake Village Agoura Hills San Dimas LaVerne Beverly Hills San Marino Pasadena Los Angeles San Gabriel Glendale Glendora High/Declining High/Increasing Low/Declining Low/Increasing Source: 1990 & 2000 Census Hidden Hills, Malibu, Palo Verdes Estates, Rolling Hills, Rolling Hills Estates 157 158 Research on poverty concentration has ascribed social characteristics to concentrated poverty neighborhoods by defining “underclass” – and thus socially deviant – areas as any census tract with high proportions (one standard deviation above the U.S. mean) of unemployment, high school drop-outs, welfare recipients, and female-headed households (Ricketts and Sawhill 1988). However, such linkages have yet to be developed between the concentrated affluence literature and upscale communities. Therefore, utilizing the rationale that such communities are the opposite of ‘underclass areas’, this research will utilize the inverse of those measures proposed by Ricketts and Sawhill (1988). Thus, areas of concentrated affluence will be defined as census tracts with high proportions of residents that are (1) married, (2) employed in professional, scientific, and technical services, (3) possessors of master’s, professional, or doctoral degrees, (4) recipients of interest, dividends, and net rental income. Following an analysis of all U.S. census tracts, the sum, mean, standard deviation, and upper threshold for high proportions of each behavioral category within the selected twenty-one tracts was calculated. Similarly, while the presence of “dilapidated housing, vacant units with boarded- up windows, abandoned and burned-out cars, and men hanging out on street corners” (Jargowsky 1997, p. 11) have been utilized as indicators of extreme poverty, scholars have yet to present descriptive characteristics of neighborhoods of extreme affluence. Instead, smaller spaces, such as gated communities, have served as exemplars and been used to advance notions of the physical characteristics present within affluent locales (Blakely and Snyder 1997). 159 Lastly, given the dearth of research on affluence concentration, descriptive characteristics of extreme affluence neighborhoods have rarely been offered. Instead, smaller spaces, such as gated communities, have served as exemplars and been utilized to advance notions of the physical characteristics present within affluent locales (see Blakely and Snyder 1997). However, such broad generalizations may ignore the increasing differentiation of affluence areas and over-emphasize the levels of social cohesion that exist, while under-emphasizing the social costs imposed upon those excluded. To that end, a series of characteristics were developed, including the presence of elements of: 1. Controls, such as parking regulations, homeowner’s associations, etc. 2. Aesthetics, for instance condition of housing stock, presence of manicured lawns and gardens, luxury automobiles, lawn furniture, swimming pools, and so on; 3. Privatization, exemplified by security systems, surveillance cameras, cameras, etc.; and, 4. Amenities, including upscale shopping centers, golf courses, and other commercial facilities catering to a wealthy clientele. These dimensions are displayed in Table 4.1 . Relying on these characteristics and using a strategy similar to that of Jargowsky (1997), observational field work was conducted within neighborhoods of concentrated affluence in order to better characterize these landscapes, as well as the condition of the existing infrastructure, delivery of public services, and nature of economic activity. The observations conducted within each tract were guided by an audit instrument that allowed 160 for qualitative and, in some cases, quantitative assessment of specific elements of the dimensions listed above. First, the instrument acknowledged the presence or absence of each element using categorical variables (Yes or No). Next, the frequency of each dimensional element was measured utilizing ordinal variables. Elements of each dimension were considered to be Low if their frequency was between zero and twenty-five percent (0-25%), Medium if their frequency was between twenty-six and fifty percent (26-50%), High if between fifty-one and seventy-five percent (51-75%), and Extreme if between seventy-six and one hundred percent (76-100%). Finally, levels of attractiveness for amenities were evaluated in a similar way. Amenities were considered Unattractive if they scored between zero and twenty-five (0-25%), Moderately Attractive if they scored between twenty-six and fifty (26-50%), Attractive if between fifty-one and seventy-five (51-75%), and Very Attractive if between seventy-six and one hundred (76-100%). In using the audit instrument, all tracts were visited at various times of the day and night to ensure a well- rounded picture and assessment. 161 Table 4.1: Audit Instrument for Selected Concentrated Affluence Neighborhoods CITY NAME TRACT # PRESENCE FREQUENCY ATTRACTIVENESS Y/N LOW MED HIGH EXT UNATT MOD ATT ATT V ATT (0-25%) (26-50%) (51-75%) (76-100%) (0-25%) (26-50%) (51-75%) (76-100%) CONTROL (Y/N) Homeowners Associations On-Street Parking Regulations Traffic-Calming Features (speed-bumps, signage, cross-walks) Other AESTHETICS (Y/N, Frequency) Manicured Lawns and Gardens Public Landscaping Luxury Automobiles Condition of Streets/Sidewalks Condition of Housing Stock Other PRESENCE FREQUENCY ATTRACTIVENESS Y/N LOW MED HIGH EXT UNATT MOD ATT ATT V ATT (0-25%) (26-50%) (51-75%) (76-100%) (0-25%) (26-50%) (51-75%) (76-100%) PRIV ATIZATION (Y/N, Frequency) Security Systems Private Security Patrols Cameras Intercoms Guards/Check-in Stations Perimeter Walls/Fences/Gates Noise Level AMENITIES (Y/N, #, and Level of Attractiveness) Golf Courses Tennis Courts Swimming Complexes Upscale Shopping Parks and Green Space Man-made Lakes/Reservoirs Private Schools 162 Finally, in order to provide a more detailed assessment of affluence concentration, as well as greater insight into the varying landscapes of concentrated affluence areas in the region, tract profiles (Tables 4.2-4.4) were constructed using data from the 2000 U.S. Census – Summary Tape Files 1 and 3 to highlight demographic, socio-economic, and housing characteristics within each study area. These profiles aided in the discussion of findings. 163 Table 4.2: Demographic Profile for Selected Concentrated Affluence Tracts Table 3.2 City Median Household Income Per Capita Income HH w/ Rent, Interest, and Dividends % Employed in Prof., Sci, and Tech. Fields or Management of Co's County Median $42,189 $20,683 0.24 0.07 Diamond Bar 4087.03 $95,952 $30,796 0.59 0.26 La Canada 4605.01 $112,286 $50,726 0.76 0.41 4605.02 $100,213 $41,467 0.72 0.39 4606.00 $116,152 $56,114 0.67 0.44 4607.00 $133,246 $64,737 0.67 0.53 4608.00 $136,817 $81,903 0.77 0.54 Manhattan Beach 6203.01 $102,803 $57,058 0.61 0.33 6203.02 $102,177 $82,194 0.55 0.34 6203.03 $107,706 $57,536 0.70 0.39 6204.00 $90,000 $50,302 0.62 0.36 6208.00 $102,096 $48,289 0.64 0.37 6209.01 $117,485 $71,089 0.69 0.50 6209.02 $101,606 $68,296 0.60 0.47 Santa Clarita 9108.09 $119,368 $42,272 0.58 0.21 9108.10 $94,569 $33,677 0.39 0.09 9200.32 $106,438 $31,255 0.45 0.03 9200.39 $91,032 $28,794 0.43 0.15 9200.43 $105,572 $47,911 0.42 0.26 9201.10 $96,196 $33,588 0.50 0.22 9203.14 $96,208 $35,258 0.53 0.13 9203.28 $90,644 $48,773 0.54 0.18 Socio-Economic Profile Table 4.3: Socioeconomic Profile for Selected Concentrated Affluence Tracts Table 3.3 Demographic Profile City Total Population % CAffluent %White %Black %Latino %Asian Median Age % Foreign-Born FB Race % HH w/ Married Couples % w/Grad. & Prof. Degrees County Median 9,519,338 0.20 30.9 0.09 44.5 11.8 32 36.2 0.71 0.04 Diamond Bar 4087.03 6,912 0.38 10.7 1.1 7.5 76.3 36 63.8 94.4 - Asian 0.84 0.15 La Canada 4605.01 5,560 0.70 67.1 0.4 3.2 23.0 42.6 20.2 76.3 - Asian 0.88 0.26 4605.02 4,430 0.57 70.5 0.9 3.9 20.7 40.4 17.3 72.7 - Asian 0.86 0.25 4606.00 4,320 0.63 74.3 0.0 4.9 15.9 43.0 20.7 67.0 - Asian 0.89 0.28 4607.00 5,202 0.65 73.7 0.4 5.4 17.3 42.4 18.8 66.8 - Asian 0.92 0.31 4608.00 3,112 0.64 78.5 0.9 6.2 10.8 49.0 12.2 47.6 - Asian 0.92 0.34 Manhattan Beach 6203.01 4,324 0.59 87.4 0.9 4.7 2.9 38.4 4.2 0.89 0.23 6203.02 6,022 0.52 89.8 0.5 4.1 2.8 34.9 9.4 41.0 - European 0.86 0.28 6203.03 4,303 0.62 86.9 0.4 5.0 4.1 39.1 7.6 31.7 - Asian 0.87 0.27 6204.00 5,022 0.58 81.0 0.7 5.4 10.5 40.3 12.0 45.7 - Asian 0.83 0.23 6208.00 7,271 0.46 79.2 0.3 6.6 10.8 39.1 12.9 57.7 - Asian 0.90 0.26 6209.01 2,607 0.59 91.2 0.6 2.4 2.6 40.1 7.2 41.7 - Asian 0.89 0.32 6209.02 2,879 0.55 91.3 0.1 3.8 1.1 37.3 5.9 0.85 0.33 Santa Clarita 9108.09 2,056 0.50 86.5 0.63 6.8 2.8 38.9 11.2 61.2 - Central/Latin America 0.91 0.14 9108.10 1,969 0.50 72.5 5.8 12.3 5.2 34.1 11.0 38.2 - Central/Latin America 0.96 0.07 9200.32 1,665 0.30 66.3 7.0 20.3 7.0 30.3 8.1 0.98 0.02 9200.39 1,915 0.29 79.8 2.8 9.1 4.0 37.0 7.1 0.83 0.11 9200.43 1,350 0.29 70.3 0 16.8 8.8 34.5 17.7 50.0 - Asian 0.98 0.19 9201.10 5,275 0.0 74.5 1.0 11.3 10.3 31.8 16.7 51.1 - Asian 0.92 0.16 9203.14 2,251 0.29 78.8 0.0 8.5 11.4 31.8 12.4 50.1 - Asian 0.92 0.11 9203.28 673 0.0 76.3 3.2 13.5 0 37.6 9.3 85.7 - Central/Latin America 0.83 0.14 164 165 Table 4.4: Housing Profile for Selected Concentrated Affluence Tracts Gross Rent/Income % of Households City % Homeowners Median Home Value Median Rent Asked Ratio 50% or More w/4+ People County Median 50.1 $201,400 $595 21.6 14.8 Diamond Bar 4087.03 95.4 $395,700 $0 8.1 55.1 La Canada Flintridge 4605.01 94.2 $608,600 $2000+ 9.4 37.8 4605.02 90.7 $489,600 $0 33.8 39.2 4606.00 92.0 $543,700 $0 15.1 33.9 4607.00 91.2 $797,200 $0 21.2 37.8 4608.00 94.3 $656,900 $2,000+ 0.0 16.4 Manhattan Beach 6203.01 86.2 $628,400 $2,000+ 7.7 28.6 6203.02 50.7 $745,500 $1,875 12.6 8.8 6203.03 83.8 $702,300 $1,375 6.3 23.6 6204.00 76.8 $517,800 $2,000+ 26.4 22.5 6208.00 80.9 $629,000 $1,333 6.4 29.6 6209.01 84.3 $871,200 $2,000+ 0.1 28.2 6209.02 63.6 $865,400 $1,563 16.9 14.2 Santa Clarita 9108.09 94.7 $542,500 $0 32.1 41.4 9108.10 93.3 $301,600 $0 0.0 46.8 9200.32 98.9 $296,000 $0 0.0 43.6 9200.39 92.3 $272,800 $0 0.0 46.3 9200.43 94.0 $551,500 $0 0.0 50.1 9201.10 90.5 $337,300 $1,375 15.7 44.2 9203.14 80.0 $292,700 $0 0.0 45.0 9203.28 66.0 $392,100 $1,245 27.4 26.6 Housing Profile 166 The Differentiation of Concentrated Affluence Neighborhoods in Los Angeles The investigation highlighted the complexities present within landscapes of affluence concentration within the globalizing Los Angeles metro-region. Generally speaking, clusters of tracts differed from each other in significant ways. Additionally, in some cases, variation existed within individual tracts as well. In particular, some tracts reaffirmed the common conceptualizations of affluent neighborhoods, including physical landscape and social composition, presented within much of the literature on affluent landscapes, gated communities, and other manifestations of segregated wealth. Meanwhile, other tracts stood in stark contrast. Moreover, contrary to the rationale relied upon by Ricketts and Sawhill (1988) with respect to extreme poverty neighborhoods - the inverse of which was utilized in this analysis - only two of the twenty-one tracts selected possessed scores that were high (one standard above the mean) on all four indicators - Tracts 4607.00 and 4608.00 - both of which were located in La Canada Flintridge (Table 4.5). This further emphasizes the inability of conventional measurement strategies to accurately depict emerging complexities in the physical and social characteristics present within affluent landscapes. 167 Table 4.5: U.S. Tract Analysis of Concentrated Affluence Characteristics La Canada Flintridge Thirteen miles northeast of downtown Los Angeles, La Canada Flintridge is situated in the San Gabriel Mountains and characterized by hilly terrain, the presence of low-density housing, including medium-sized homes and spacious, gated mansions, and an impressive retail strip consisting of upscale boutiques. The grouping of tracts possessed the highest rates of affluence concentration in the entire sample of tracts. The population was largely comprised of Whites and Asians in the early to late forties (the oldest residents in the entire sample). This cluster of tracts was also the most diverse and had the greatest population of foreign born residents – who were predominantly Asian. In SUM 48436.89321 8027.182884 22613.76665 4867.228661 MEAN 0.74 0.12 0.35 0.07 STDEV 0.17 0.23 0.16 0.07 U Threshold 0.91 0.35 0.51 0.14 (M+STD) Selected Tracts %Married Couples %Emp in Prof, Sci, Tech, & Mgmt %HH w Int, Rent, & Div %w Grad & Prof Degrees Diamond Bar 4087.03 0.84 0.26 0.59 0.15 La Canada Flintridge 4605.01 0.88 0.41 0.76 0.26 4605.02 0.86 0.39 0.72 0.25 4606 0.89 0.44 0.67 0.28 4607 0.92 0.53 0.67 0.31 4608 0.92 0.54 0.77 0.34 Manhattan Beach 6203.01 0.89 0.33 0.61 0.23 6203.02 0.86 0.34 0.55 0.28 6203.03 0.87 0.39 0.70 0.27 6204 0.83 0.36 0.62 0.23 6208 0.90 0.37 0.64 0.26 6209.01 0.89 0.50 0.69 0.32 6209.02 0.85 0.47 0.60 0.33 Santa Clarita 9108.09 0.91 0.21 0.58 0.14 9108.1 0.96 0.09 0.39 0.07 9200.32 0.98 0.03 0.45 0.02 9200.39 0.83 0.15 0.43 0.11 9200.43 0.98 0.26 0.42 0.19 9201.1 0.92 0.22 0.50 0.16 9203.14 0.92 0.13 0.53 0.11 9203.28 0.83 0.18 0.54 0.14 168 addition to having high rates of married couple households, the tracts were home to some of the most well educated residents in the entire sample. The selected tracts demonstrated varying levels of defensiveness, as well as palpable lines of demarcation. While no homeowner’s association was present, the sample of tracts contained the greatest number of on-street parking restrictions and traffic-calming features, such as speed bumps and signage regulating the speed limit and warning about radar. Although characterized by the highest median household income levels in the entire sample of tracts, per capita income levels were more than two (and in some cases four) times greater than the county median, but still less than those of Manhattan Beach. Levels of supplemental income were highest within these tracts, as was the percentage of residents employed in the high-wage, high-tech sector and management of companies. And while, levels of homeownership were high, median home values were slightly lower than those of Manhattan Beach. The tracts possessed the highest rental costs, and one tract (4605.02), was the most rent-burdened in the entire sample (33.8). Finally, the percentage of large households wasn’t overly large. However, as the majority of the tracts approached forty percent, it was a noticeable characteristic. In terms of aesthetics, the outer fringes of the tracts resembled small Midwestern towns more than upscale southern California neighborhoods. The housing stock consisted of smaller dwellings constructed of brick, aluminum siding, and stucco on modest-sized lots. Several (but less than 50 percent also had what appeared to be guest homes, which were positioned behind them). The streets were lined with deciduous trees that were 169 shedding their leaves, as well as evergreen trees, bushes, and shrubbery; very few palm trees were present. Meanwhile, the overall condition of the streets and sidewalks was superb. However, the streets were configured in such a way that only one side had a sidewalk. To that end, streets were not very pedestrian-friendly. All of the yards were very well-manicured and, although some luxury cars were present, less than 25 percent of the residents possessed them. Many of the cars were parked in circular driveways, but a fair number were parked on the street too. Again, topography played a significant role in guiding development and, in this case, separating both modest and upscale, spacious housing from other homes that varied in size, but possessed picturesque views of the area. A number of the homes displayed some type of Fall/Thanksgiving decoration on the front door or somewhere in the front yard. All of the lots had manicured lawns, but very few had aesthetic gardens (flowers, etc.). A large alley that was extremely clean was utilized by several people to gain access to the adjacent sports complex. Levels of privatization were moderate, as approximately 40 percent of residents had signage in their yards pertaining to security systems or private patrols. Residents appeared to feel extremely safe in this particular area of the neighborhood, as several joggers, bikers, and dog-walkers, as well as entire families were out enjoying the outdoors. This was the case throughout a number of tracts - particularly those adjacent to Verdugo Road, one of the main thoroughfares. Levels of privatization increased significantly, however, as the observation continued further inside the tract. The inner-cluster of tracts was home to much larger parcels of land which housed dwellings that were, in some cases, two to three times the 170 size of those located in the outer-area of the tract. These homes had much larger yards, with some possessing large gates and arches at the driveway entrance, fountains and elaborate trimming of shrubbery in the front yard, as well as swimming pools, tennis courts, man-made creeks on the sides and in the rear of the properties. Tangible signs of defensiveness were present, including large watch dogs. It was apparent that these dogs had been well-trained, as they remained attentive throughout the observation. Also, approximately 90 percent of the dwellings possessed large gated entries and intercoms. Additionally, roads were much narrower, limiting the amount of street parking, as well as the number of cars that could pass through. Despite the secured feel of this part of the tract, elements of nature and wildlife were present. A horse trail was present and often utilized, given the smell of manure that perforated the air. Signage also indicated that deer regularly frequented the area. Numerous squirrels were visible and the calls of numerous birds filled the air. Again, topography played a significant role, as several homes could be seen in the hills above the privatized area of the tract. The roads leading to these homes were extremely narrow. However, they circled around a large hill, giving way to dwellings of various sizes. Some of the homes were along the roadside, while others were set back from the road and couldn’t be seen. Ninety percent of the homes displayed signs (some more than one) at the base of the driveway, whether the house was in view or not. It was clear that the further up the hill, the more intense the levels of privacy became. Perhaps the most attractive attribute of this cluster of tracts the presence of several amenities that it boasted. First, the cluster houses a public botanical garden that attracts 171 thousands of people daily, as it is home to several beautiful gardens and ponds, and is a preferred location for weddings, wine tastings, and other special events. Additionally, the cluster of tracts is home to the city’s school district headquarters and houses a large complex that includes several schools and academies, as well as recreation fields and tennis courts. These amenities are very well-utilized by residents. Moreover, it was very clear that residents were very proud of the reputation of the local schools. To that end, a large banner was posted near the district headquarters informing residents and others driving on the main thoroughfare to make donations to the local schools for the betterment of various educational enrichment and arts programs. Finally, the cluster of tracts was adjacent to a shopping district that consisted of privately owned, mom and pop stores that, while not upscale per se, provided high- quality goods and services that appeared to be congruent with the socio-economic standing of the area. These included law and doctor’s offices, fitness studios and day spas, a cake bakery, multiple hair and nail salons, tile, carpet, and upholstery stores, and a computer consulting business. All stores appeared to be well-invested in the immediate community, as the windows displayed advertisements for local events and festivals. For example, one local business, a See’s Candy store, partnered with one of the local schools on a fundraising endeavor. There was also a large hospital was located on the neighborhood’s main thoroughfare approximately two blocks away. In particular, Tract 4607 possessed the second-highest rate of affluence concentration in the entire sample and yet was one of the most diverse. While it was predominantly comprised of Whites in their early forties, the tract was also home to one 172 of the largest immigrant populations in the entire sample as well (18.8). Nearly seventy percent of the tract’s immigrant population is Asian - the majority of whom arrived prior to 1980. Interestingly, the tract also benefits from the arrival of a similar percentage of Asian immigrants that could be considered newly arrived. The tract boasted a median household income that was more than three times the county median and was second highest in the entire sample. The per capita income was also more than three times the county median and was the fifth-highest in the entire sample. More than half of the tract’s residents were employed in professional, science or technology fields or were managers of companies. This was the second-highest proportion in the entire sample. Finally, the proportion of households that received supplementary income was three times the county median – which was among the highest levels in the sample. The tract is home to a substantial population of homeowners (91.2%), which was nearly double the county median, but less than several other tracts in the sample. Meanwhile, greater than one-third (37.8%) of the households are considered large (containing four or more people), which was comparable to other tracts in the same municipality, yet greater than the tracts in Manhattan Beach and less than the tracts in Diamond Bar and Santa Clarita. Finally, while none of the residents residing within this tract could be considered rent-burdened, it possessed a relatively high rent to income ratio. Less populous than Tract 4607, Tract 4608 was located in both La Canada and the City of Pasadena. This tract demonstrated a slightly lower level of affluence concentration (which was still the third-highest in the entire sample). Meanwhile, racial 173 demographics were very similar to those found in Tract 4607, except that the percentage of Whites was slightly larger and older. Additionally, the tract was home to a smaller population of Latinos and immigrants – only half of whom were Asian. The majority of these immigrants arrived before 1980. However, unlike Tract 4607, there was a sharp decline in the number of immigrants that arrived between 1990 and 2000. Very similar to Tract 4607, a large percentage of the residents (.85) are married, and slightly more than one-third possess graduate or professional degrees. Additionally, this tract possessed the highest median household income in the entire sample ($136,817), which was more than three times the county median and slightly greater than that of Tract 4607. Additionally, it boasted the second-highest level of per capita income ($81,903), which was four times the county median. This particular tract was also home to the greatest proportion of households receiving supplementary income from rent, interest, and dividends in the, and possessed the greatest percentage of residents employed in professional, scientific, and technical fields or the management of companies. Both were the greatest totals - within those particular categories - in the entire sample of tracts. With regard to housing, the tract demonstrated a homeownership rate of 94.3 as well as a median home value of $797,200, which was the highest in the sample of La Canada tracts, but comparable to other tracts in the overall sample. Meanwhile, none of the residents residing within this tract have high rent to income ratios. Finally, very few of the households in this particular tract could be considered large. 174 While the quantitative analysis of selected concentrated affluence neighborhoods revealed the need for more reliable measurement strategies, the qualitative assessment underscored that landscapes of extreme affluence are, in fact, diverse and highlighted the complexities present within landscapes of affluence concentration within the globalizing Los Angeles metro-region. In the paragraphs that follow, I briefly describe the variegated landscapes of the selected concentrated affluence neighborhoods. Diamond Bar Located in the Brea Valley in eastern Los Angeles County, Diamond Bar lies about twenty seven miles from downtown Los Angeles and possesses terrain that consists of mountains, hills, and valleys. The area is also emblematic of the demographic changes associated with the globalizing Los Angeles metro-region, as it has become a landing- point for an increasing population of upwardly mobile Asian immigrants since the 1980s. Only one tract in Diamond Bar was selected for detailed analysis (Tract 4087.03). Located in the Rowland Heights Community, which is actually considered unincorporated Los Angeles County, the tract was home to a number of hills, which played a significant role in the residential development pattern and spatial orientation of the neighborhood. The selected tract was home to varying levels of wealth, as an upscale residential community and a gated community were adjacent to each other. Given the topographic features of the area, the gated community was positioned on a hill above the upscale residential community. Access to the gated community was not granted by the attendants in the guardhouse. However, it appeared to be a much more affluent area than 175 the neighboring upscale community, considering the large, ornate gates, meticulously manicured entrance (trees, lawns, and flowers), extremely high volume of luxury automobiles that were entering and exiting the premises, and the very defensive attitude of the attendant. Still, the upscale community served as a suitable locale in which to explore and make observations. This particular tract was the most populous in the entire sample (6,912 residents), and had the second-lowest rate of affluence concentration (.38). While this rate was almost two times greater than the county median, the tract marked a decline of eleven percentage points from the 1990 rate. This tract - the only one in the entire sample that was not predominantly White – was largely comprised of relatively young, Asian immigrants. Finally, the percentage of married-couple households and individuals with graduate and professional degrees were both well-above the county median, but also amongst the lowest in the entire sample. The tract possessed the third-lowest median household income level in the entire sample, as well as the lowest per capita income level in the entire sample. Additionally, while half of the households received supplemental income, the percent employed in high-tech fields or in management were amongst the lowest in the entire sample. Intriguingly, the tract boasted the highest levels of homeownership in the entire sample, and had relatively low median home values, and, by far, the greatest percentage of large households in the entire sample. Additionally, very few households were rent-burdened. This picture is indicative of a multi-generational immigrant enclave in which homeownership is a paramount value and residents are upwardly mobile. 176 The area was aesthetically pleasing. The housing stock was extremely uniform, as all of the homes were two-stories tall, had two-car garages, and were painted an off-white color (except one that was bright yellow). They all appeared to be brand new. Meanwhile, the streets and sidewalks were very clean, with only minor cracks in the street. The vast majority of the lawns were well manicured and often accompanied by flowers and trimmed gardens. Additionally, brick pavers, and glass block columns were prevalent in 75 percent of the front yards. Approximately 95 percent of the dwellings possessed walls that were between three and four feet and extended along the side of the property, but stopped short of the front setback. Approximately 50 percent of the homes had walkway lighting, which meshed with the very well-lit streets. Types of automobiles varied a great deal within the area. Consistent with the larger households, the majority of these were minivans. However, several other makes and models were present including, Hondas, General Motors, and some luxury models (BMW, Mercedes, Lexus). These were by far the exception, however. Of note, 100 percent of the cars that entered and exited the gated community above were luxury models. Security was definitely a priority within this particular study area. Over 95% of the homes in the tract had signage indicating the presence of a security system or subscription to private security companies in the front lawn. Some had multiple signs in the yard and stickers on their garages. Many of these signs advertised different companies. This demonstrated that while residents were united in their concerns regarding the need for protection, they were not in agreement in terms of a common 177 service provider. However, no private patrols, intercoms, or cameras were evident. Again, and especially considering the security concerns, there was very little activity within the tract, in terms of automobile and pedestrian traffic, and no residents were observed walking their dogs or working in the yard. This equated to very low levels of noise (other than the automobile traffic on the main thoroughfare). Despite the low level of social interaction observed and the absence of a formal homeowner’s association, the tract demonstrated some forms of community. For example, signs were posted in the yards of a small percentage of the homes protesting the proposed development of two high-density apartment complexes in the area. Also, there were large banners attached to several telephone poles on the main thoroughfare which displayed the names of residents that are currently fighting in the wars in Iraq or Afghanistan. In terms of amenities, there were no golf courses, tennis courts, or swimming complexes present (although these may have existed within the adjacent gated community). There was a horse trail that ran under the main thoroughfare and the entrance to the gated community. But perhaps the greatest amenity was the spectacular views enjoyed by many of the residents living just below the gated community. Manhattan Beach Manhattan Beach is an upscale, beach-side municipality with crowded dwellings near the ocean and a hilly area of lower density singly-family homes, which lies immediately behind the coastal strip. The cluster of seven tracts in Manhattan Beach demonstrated low levels of residential control. No Homeowner’s Associations was noted. However, normal on-street parking regulations (consistent with weekly street 178 sweeping) were printed on signs. There were no speed bumps, or cross-walks either. Within the tracts closest to the ocean, many of the residents’ cars were parked on very narrow streets and no garages appeared to be present. This tended to give the streets a congested look while altering levels of walkability. Other tracts had streets that were much wider and allowed for not only on-street parking, but comfortable driving as well. The quality and width of streets and sidewalks varied, as some contained numerous cracks, while others were pristine. However, there were no pot-holes, but some sewers had standing water near them. The tracts were generally well-maintained. The tracts demonstrated lower rates of concentrated affluence than the cluster of tracts in La Canada, but greater rates than the selected tract in Diamond Bar. The city’s overall affluence concentration rate of .95 marked a 14 percentage point increase from 1990. The selected tracts were predominantly White, with increased percentages of Asians in two instances, and residents were in their late-thirties and early-forties. Of note, these tracts possessed the lowest percentages of foreign born residents in the entire sample. Finally, the vast majority of households contain married couples, and the percentage of well educated residents was the highest in the entire sample of tracts. The median household and per capita income levels within these tracts were the greatest in the entire sample. In addition, the tracts possessed the second highest levels of supplemental income behind La Canada. Also, at least one-third of the residents in each tract were employed in the high-wage, high tech sector or were managers of companies. Again, these levels were slightly less than those in La Canada. 179 Surprisingly, despite their high levels of high levels of education and increasing level of affluence concentration, these tracts possessed the lowest rates of homeownership. Finally, this particular set of tracts contained comparable levels of rent- burdened households and the smallest percentage of large households. Along these lines, the most interesting aspect of this particular grouping of tracts was the housing stock, which consisted primarily of single-family dwellings, as well as condominiums and some apartments near the ocean. Single-family homes varied greatly in terms of size (two-story and ranch) and construction type (siding and brick). Some were very modern and tall with large windows, while others had large balconies. These homes, although structurally different, were often side by side. In fact, up to 90 percent of the homes in some tracts appeared to be newly constructed. From the front, many of these dwellings appeared to be rather small. However, they sat on very long lots, and appeared to be quite spacious. Many of the homes – despite their varying sizes – did not have sizable front yards. In fact, even the largest homes in the entire sample of tracts, which were located closer to Hermosa Beach, had front yards that paled in comparison to the size of the actual dwelling. Instead, they had either very small amounts of grass in the front set-back or pavers only. Although a mix of cars existed, approximately 50 percent of them were luxury automobiles (BMWs, Lexus’, and Mercedes-Benz). The streets and sidewalks were in relatively good condition, as some cracks were evident. Levels of privatization here were low, as there were no private security patrols, intercoms, or guards/check-in stations, or perimeter walls, fences, or gates. Cameras may 180 have been present, but none were in plain view. Some noise, however, was present from automobile traffic and children playing in the neighborhood (sometimes after dark). Consistent with the low level of privatization, a strong sense of community was evident. Many of the residents appeared to be very friendly with each other. Residents were out and about in the tracts - working on their cars, doing minor home construction, working in their garages, talking with their neighbors in front of their homes, and a large percentage were hanging or arranging their Christmas lights. Residents also felt safe, as evidenced by the large numbers that were out walking at various times of the day and at night. Many of these were women, who were with infant children or dogs. The tracts were rich in terms of amenities, as well. In addition to the Sand Dunes Park and walking trail, the cluster of tracts is adjacent to Manhattan Village, which is a major retail shopping complex complete with stores specializing in men’s and women’s apparel, electronics, crafts, shoes, children’s, health and beauty, financial services, eateries, and a major department store – Macy’s. There were also five (5) public elementary and middle schools. The schools were quite sizeable and had large recreation areas complete with jungle gyms, basketball courts, and grass fields. It was very apparent that the residents were very proud of their local schools and actively sought to maintain their quality. Similar to La Canada, a large banner was placed upon a a fence outside of one of the middle schools, advertising a non-profit organization Additionally, the 405 freeway and Los Angeles International Airport are all in very close proximity, and the beach (which is easily the area’s greatest amenity) is in walking distance. The area was also home to an impressive mix of stores on Sepulveda Boulevard. These were very 181 diverse and included upscale establishments, such as luxury car dealerships and service centers, as well as eateries, but also low end stores such as nail salons and fast food restaurants. There were also medical and dental care centers, banks, real estate offices, and hotels (Comfort Inn and Holiday Inn Express). Meanwhile, another part of the study area contained Veteran’s Parkway (a small park with benches that served as the center of a lengthy walking trail which was being utilized by several residents, and Sand Dunes Park, which was located less than a mile away. One of the tracts selected for analysis was adjacent to the ocean, and possessed many of the same qualities. Housing was, again, diverse, not in terms of size, architectural style, and material, but in terms of type and density (single-family dwellings and condominiums). In addition to the beach, the hills present within the tract provided for spectacular views of the water and sunsets. The tract is also home to Highland Avenue, which is a main thoroughfare and home to several eateries. Therefore, noise levels were greater here, as traffic volume (cars and buses) increased significantly as afternoon progressed into evening and night. It was clear that residents felt very safe here as well. Some had their doors open while cooking outdoors on their patios, others were grilling on their balconies, women were out walking at night (some with their children), and others were walking dogs. Santa Clarita Santa Clarita lies approximately thirty miles from downtown Los Angeles and is situated within the Santa Clarita Valley. The areas is characterized by extremely hilly 182 terrain, as well as a diverse mix of housing, including large older ranches, sizeable gated mansions with large setbacks, and areas of smaller, recently built homes. Given its location, this particular study area demonstrated significant variations within its landscapes of affluence concentration. Perhaps the only feature common within the tracts under investigation was the very rugged terrain, as hills were common within each of the tracts. Consistent with the rugged terrain, the majority of the tracts possessed a distinctly rural feel, characterized by the presence of large ranches, many of which were complete with horses and stables. However, sizeable, multi-story and ranch-style mansions, as well as typical single-family dwellings were present within some of the same areas. Additionally, there were homes that appeared to have been recently built and were identical in terms of size, architectural style, construction, and color. This particular series of tracts were the least populous in the entire sample and had the second-lowest rates of affluence concentration. However, the city’s 18 percentage-point increase from 1990 demonstrates that levels of affluence segregation are rising. Additionally, these tracts were the most racially diverse in the entire sample. In particular, while the majority of the population in the study area was White, within some tracts, substantial populations of Latinos were present. Meanwhile, other tracts contained small, but significant populations of Asians. This was consistent with the second-highest rates of foreign born residents – the majority of which were Latino and Asian. Residents demonstrated a wide range of ages from early to late thirties and, while the tracts were home to the largest percentages of households with married couples, they also 183 demonstrated the lowest percentages of residents who would be considered well educated. Although the tracts possessed median household income levels that were greater than $90,000 and, in some cases, greater than $100,000, they were the second-lowest in the entire sample, as were per capita income levels. Similarly, the tracts demonstrated the lowest percentages of supplemental income and residents employed in the high-wage, high-tech sector or who were managers of companies. However, the area was home to some of the highest homeownership rates in the entire sample. Characterized by significantly large households, all but one of the tracts in this cluster had rates that were at least (41 percent). Meanwhile, although the majority had low percentages of rent-burdened households, Tract 9108.09 possessed the second- highest rate in the entire sample (32.1 percent). Along with Tract 9108.10, it possessed the highest rates of affluence concentration and was home to a sizeable population of Latino immigrants, the vast majority of whom arrived prior to 1980. Interestingly, while the majority of the immigrants in Tract 9108.09 were not citizens, all of the immigrants in Tract 9108.10 were. This could signal the existence of a large group of older, relatively established immigrants (Tract 9108.10) living in close proximity to immigrants, who are slightly younger, less-educated, and, perhaps, less-integrated into the formal labor market. The majority of the tracts within the study area contained few aspects of control. There was no evidence of a homeowner’s association, no parking regulations, and no traffic-calming features present. However, there was frequent signage on telephone poles 184 warning that all actions performed in the neighborhood were being captured on camera. No cameras were visible, however. The most significant evidence of control was that at the top of one of the hills within the tract were approximately sixty single family tract dwellings that looked exactly the same. Other tracts possessed large homes, some of which had circular driveways and large, well-manicured lawns. In these areas, primary thoroughfares contained streets that were well-maintained. However, smaller, arterial streets were also present and home to even larger homes than those that were on the primary thoroughfare. Approximately half of these homes possessed large gated entries some of which were very ornate. The lots upon which some homes sat also contained large stables with horses that were unattended. Some smaller, ranch homes existed as well. However, here, the condition of the streets deteriorated. In particular, they became much narrower and transitioned from asphalt to gravel. There were no sidewalks present within the entire tract. However, elsewhere in the tract was a small gated community, where no guards were present, but still access was not available. Intercoms and gates were frequent, while private patrols were minimally advertised. The area was extremely quiet. A second gated community (complete with guardhouse) was also present within the tract. Again, access was not provided. However, through the large perimeter gates, several large mansions with small yards were visible. In terms of aesthetics, topography often played a role. In some tracts, the size and condition of the housing stock was often smaller and less appealing at the base of a hillside and, in some cases, dilapidated with garbage strewn along the side of the street. 185 Further up the incline, the condition and size of the housing stock vastly improved. The majority of the homes were two-story and relatively new and painted a bright tan/light orange coloring. There were small roads that split from the main thoroughfare and contained additional single-family dwellings, signifying high-densities. Approximately half of the lawns in the entire study area were well-manicured, while some contained dirt patches. The condition of the sidewalks and streets were generally of high quality, although some cracks along the curbs existed. Although private security patrols and security systems were advertised in the yards of approximately one- quarter of the homes, and intercoms as well as some gates were present, the area was extremely quiet and did not give the impression that privatization was a major concern for residents. Other tracts in the study area had a distinct rural feel to them. These tracts contained no elements of control and very little aesthetic quality. However, a mixture of houses was present and sat upon lots that were quite sizeable. Some were widely built ranch-style homes, while others were taller and much larger traditional mansions. Some larger homes were arranged on a main thoroughfare in a typical fashion. However, these homes often possessed a front setback of at least 100 – 150 feet and could be viewed from the primary thoroughfare, but were behind large gates (many of which were open during the time of observation). In addition to possessing large gates, intercoms were present in front of approximately 75% of the homes. The lawns here were very well manicured. Here, amenities included a full-sized tennis court that was well-maintained 186 and attractive, as well as a sizeable, man-made lake with a fountain in the center. Few luxury automobiles were present, however. On the opposite side of the thoroughfare, were smaller, ranch style homes, as well as larger mansions that were again had a large front setback. In many cases, on this side of the street, were stables and grazing areas containing horses (many of which were unattended). Elsewhere in the tract, however, the topography changed dramatically and contained large, sprawling hills and, therefore, only a couple of smaller homes. The area was extremely quiet, except for some children that were playing on a jungle gym on the side of one of the houses and the sounds of the horses. People were very friendly and nodded or waved. Very little traffic existed. Despite its variety in terms of housing stock and topography, this cluster of tracts contained a number of quality amenities, including a large park - in which people were walking their dogs, biking, playing baseball and watching while children played on a jungle gym – and a lengthy horse trail. In addition, due to the hills that were often present, a number of the tracts provided outstanding views of the city and surrounding area, and all of the tracts had access to the 2 and 14 Freeways. Three churches (Kingdom Hall of Jehovah’s Witnesses, Church of Jesus Christ of Latter Day Saints, and a Non- evangelical place of worship) were present. Surrounded by the Angeles National Forest, Robinson Ranch, a public golf club, contained two very attractive golf courses. Finally, like other selected areas of study, this particular cluster of tracts contained a mix of retail establishments, including coffee shops and neighborhood restaurants. However, these were situated in small strip-malls. Thus, this particular cluster of tracts did not benefit 187 from the presence and revenue generated from being in close proximity to a large retail shopping area. Of note, the construction of a new sub-division down the street from Robinson Ranch indicated that this area would soon be experiencing additional growth. The most rugged tracts (9108.10 and 9200.32) were characterized by the presence of a handful of large ranches that were widely dispersed and situated on private roads (as indicated on the street sign). Some appeared to have existed for some time, while others looked to have been built relatively recently. Additionally, some commercial establishments existed as well, including a dog breeding company, small manufacturing companies, and plant nurseries. Chapter Four Conclusions and Suggestions for Future Research Utilizing a mixed-methodology and data from the 1990 and 2000 Census of Population and Housing, this research has interrogated the physical landscapes and social compositions of extreme affluent communities, as well as the behavioral tendencies of those who reside within them. In doing so, it has tested common methods of measurement, analyzed the extent to which neighborhoods of concentrated affluence meet the physical descriptions and social expectations of upscale communities set forth by academic literature, as well as the media, and the extent to which the residents seek to defend and protect their wealth by engaging in defensive strategies and tactics. Following the analysis of the 88 municipalities in Los Angeles County, I relied upon an alternative poverty threshold (150 percent), the Concentration Index, and a Concentrated Affluence Matrix to select four cities within which in-depth, comparative analyses were conducted at the census tract level. Using the inverse of the four 188 characteristics commonly utilized within concentrated poverty literature to denote ‘extreme’ poverty or ‘underclass’ areas as a guide (unemployment, high school drop- outs, welfare recipients, and female-headed households), we conducted an examination of all U.S. tracts to determine 2000 threshold values for ‘extreme’ affluence neighborhoods. Tracts in the sample of cities were screened using these variables (high proportions of residents that were married, employed in professional, scientific, and technical services, possessors of master’s, professional, or doctoral degrees, and recipients of interest, dividends, and net rental income) leading me to nineteen tracts from the four cities selected. Lastly, given the dearth of research on affluence concentration, descriptive characteristics of extreme affluence neighborhoods have rarely been offered. In response, a field-based physical landscape analysis was conducted within the selected tracts, including land use surveys, weekday/weekend street observations and assessment of neighborhood facilities. Finally, to better depict the demographic, socio-economic, and housing conditions within the selected study areas, tract profiles were constructed using data from the 2000 Census. While a substantial canon of research has focused on affluent landscapes and the associated politics of such places, little research has investigated affluence concentration, as well as the behavioral tendencies of affluent residents, particularly in light of the globalizing economy and concomitant demographic restructuring, including increases levels of poverty concentration within suburbs. Common characterizations of affluent landscapes have often conveyed notions of ‘the good life’ through such symbols as well- 189 educated, like-minded Whites, who reside in stately mansions and drive expensive, luxury automobiles. In response, this investigation, including its quantitative analysis and field-based research, produced empirical findings that deviate from the aforementioned depictions in several ways and, instead, emphasize the increasingly complex nature of affluent landscapes. In particular the selected study areas were home to varying degrees of diversity, in terms of race, age, and educational attainment. Although the majority of the tracts were largely comprised of Whites, one tract was characterized by the predominance of Asians, while others possessed substantial populations of Latinos. Both populations were consisted of immigrants – both newly arriving and more established. Additionally, percentages of residents with graduate and professional degrees varied widely. Finally, the ages of residents also varied from early thirties to approximately fifty years old. While yielding a more realistic portrait of such spaces, this also reaffirms the notion that landscapes of affluence concentration, and social profiles in particular, are becoming increasingly heterogeneous as well. Similarly, variation existed among types of wealth. While gated communities have served as the most recent manifestation of residential wealth and exclusion, these types of communities were by far the minority. Instead, forms of wealth varied - sometimes within adjacent tracts in the same municipality. The study areas did reveal more traditional forms of wealth as old money, characterized by the presence of both larger homes and mansions with large front yard setbacks on manicured lawns. However, newer enclaves of fabricated affluence were present as well, characterized by the 190 presence of smaller dwellings that were identical in architectural design, construction material, as well as color, and were built upon lots that appeared to be the exact same size. Other study areas appeared to demonstrate traces of rural well-being, characterized by the presence of rugged, hilly terrain, and medium to large dwellings and ranches complete with horse stables and sizeable front setbacks. These varied forms of wealth segregation stand in contrast to previous depictions of affluent neighborhoods and articulate the idea that conventional notions of what constitutes an upscale community warrant modification and our notions regarding their physical and social composition stand to be redefined. Finally, various forms of residential defensiveness were evident. Previous research on affluent landscapes has emphasized the reliance of wealthy residents on long- standing tactics such as restrictive covenants and exclusionary zoning, as well as the more recent influence of homeowner’s associations in order to create and maintain varying degrees of seclusion. In contrast, findings revealed the presence of more sophisticated and clandestine methods of ensuring cohesion amongst residents. In particular, strategies ranged from the posting of signage urging residents to assist in maintaining the high quality of education offered within local schools through monetary contribution in some neighborhoods, the widespread posting of stickers and yard signs advertising private security patrols and alarms in others, and the purposeful design of neighborhoods without street lights resulting in total nighttime darkness. These findings articulate that, just as the landscape of concentrated affluence has become more complex, strategies and methods designed to maintain core values - property values, the 191 provision of quality schools, the presence (or at least threat) of a strong police presence, and the provision of a safe, nighttime environment to name a few - may also follow suit. Given the increasing levels of heterogeneity present within such landscapes, notions regarding residential defensiveness should be redefined. In the paragraphs that follow, I characterize each study area and offer suggestions for future analyses. The tract in Diamond Bar was indicative of global restructuring characterized by increasing demographic changes, including the presence of large households of Asian immigrants, who were not extremely well-educated or working in the high-tech, high- wage sector. Despite being younger (on average) and relying on alternative employment patterns, reasonable amounts of wealth were present in the forms of high-levels of homeownership and supplemental income. Moreover, and perhaps in line with inherent cultural differences present within an immigrant community, the tract demonstrated low levels of social interaction, yet extreme levels of defensiveness. Thus, in many ways, the neighborhood appeared to be more of a destination, rather than a social and economically vibrant place as upscale neighborhoods are often described. Such characteristics are indicative of the ways that immigrant populations utilize their transnational capital to relocate to affluent communities of the US, rather than poor urban neighborhoods (Li 1998, 1999). They demonstrate that poverty-stricken urban and inner-suburban neighborhoods are not the only locales that are affected by the impact(s) of globalization. Meanwhile, although the tracts in La Canada fit the more traditional model of an affluent community, including well-educated residents, high levels of wealth, and employment in the high wage, high tech sector, significant differences were evident in 192 their physical and social compositions, as well as levels of residential defensiveness. Some tracts demonstrated a small town feel, complete with parks, as well as boutiques and other mom and pop stores. Here, defensive strategies revolved around the maintenance of a high-level of community cohesiveness and quality public schools. However, others demonstrated low-levels of community and a mixture of defensive strategies that were much more overt, including the prevalence of gates, watch dogs, intercoms, cameras, and the absence of street lights, making night driving without intimate knowledge of the area extremely difficult. Given the city’s economic trajectory, including a nine percentage point decrease in affluence concentration during the 1990s, high levels of immigration, and higher rent-to-income ratios, these varying levels of territoriality may be indicative of some residents’ desires to separate themselves from an increasing population of others (including immigrants who might be relatively wealthy), and other perceived detriments such as decreasing property values. Meanwhile, Manhattan Beach fits the description of an affluent community that is undergoing a lengthy demographic transition, as the area has experienced a large influx of Asian immigrants (many of whom are upwardly mobile) since the 1980s. Additionally, it is home to a significant percentage of renters (particularly in beach-side tracts) who are not starting-out, but instead appear to be content living in close proximity to the water. There, tracts fit a similar economic and demographic profile as those in La Canada, but demonstrated some significant differences. Consistent with its economic trajectory, which included a fourteen percentage-point increase the municipal rate of affluence concentration during the 1990s, the cluster boasted the greatest percentages of 193 well-educated residents, and the highest median household and per capita income levels in the entire sample, this cluster also demonstrated extremely high levels of community life. In contrast to La Canada, very few signs of overt defensiveness (gates, security signage, etc.) existed. Instead, defensiveness again revolved around the maintenance of high quality schools and community cohesiveness. However, the same cluster of tracts was also home to the lowest rates of homeownership and, inherently, the greatest number of renters (many of whom reside in rent-burdened households), as well as the smallest percentage of large households in the entire sample. Santa Clarita appeared to be experiencing a significant transformation as well. While La Canada and Manhattan Beach were well-established areas of affluence, this particular municipality gave the impression that it was in the developing stages, as evidenced by its eighteen percentage point increase during the 1990s. However, relatively low tract levels of concentration existed, as the area was characterized by the second highest rate of immigrants in the entire sample as well as low levels of residents who are well-educated. Many of these were not employed in the high wage/high tech sector, and were not managers of companies. Although known for its older, spacious ranches, the area appears to have become a magnet for individuals who are wealthy or at least earn substantial incomes and desire a quiet, rural setting complete with hills, horses, large parks, and spectacular views rather than upscale shopping. Meanwhile, other affluent individuals have chosen to reside in one of the area’s recently built gated communities. While some sections were characterized by the presence of older, run-down housing, the anticipation of future 194 growth was evident in that new housing (consisting of both smaller dwellings and much larger mansions) had either been developed or was in the process of being built in at least two of the tracts. Affluent Landscapes, Residential Behavior, and Defensiveness Given the dearth of research on wealth segregation, this study breaks new ground by illuminating the burgeoning levels of heterogeneity present within current landscapes of affluence concentration. These initial findings represent significant departures from traditional portraits of wealthy neighborhoods and, therefore, demonstrate that such depictions are in need of revision. However, this investigation and resulting vignettes of the affluent neighborhoods selected for analysis represent the initial step in understanding not only such communities, but also emerging conditions of economic polarization. However in order to better comprehend the complex catalysts which work at various geographic scales to simultaneously create and maintain affluent landscapes (as well as poverty landscapes), thus contributing to conditions of economic polarization, subsequent research should rely heavily upon surveys and interviews with city planners, homeowner’s associations, community organizations, and residents. These additional research tasks will provide much needed data regarding the general history and specific politics of place, including the rationale behind the current behaviors of the affluent, as well as the reasoning that underlies current strategies enacted to protect property values. 195 Defensiveness and the Differentiation of Wealth in Upscale Neighborhoods Previous research on affluent landscapes has emphasized the considerable lengths to which wealthy residents often work to defend their image, status, and property values. However, in this analysis , levels of defensiveness appeared to vary depending upon the type of wealth that was present. In particular, those tracts that contained relatively new housing were much more adamant about demonstrating their defensiveness through the advertisement of their affiliation with a particular private security patrol. For example, in one of the tracts in Diamond Bar as well as one in Santa Clarita, two or three security patrol signs, stickers, or both were posted on homes and garages or in front yards or at the base of driveways. Meanwhile, in those tracts that appeared to be older and more organic, residents didn’t seem to be as concerned with issues of security. For example, within a different tract in Santa Clarita, horses were left to move about freely on various properties. Additionally, in those cases where gated residences existed, they were often open. Based upon these initial findings, future research should explore the relationship between strategies and degrees of defensiveness and types of affluent communities. It could be that in some older neighborhoods of affluence, residents are less insecure about losing their possessions, due to their longer tenure with wealth or their long-standing and solid relationships with city government and providers of municipal services (for ex: police and fire departments). Therefore, they may not find it necessary to openly and aggressively advertise their means of protection. 196 In contrast, in newer enclaves of affluence, residents may be more insecure about their more recent attainment of wealth and, therefore, may be more fearful. For example, some members of Diamond Bar’s burgeoning immigrant population, most of which arrived during the 1990s, may be fearful of crime-levels or their new surroundings. Thus, they may take great pride in their new-found wealth and feel the need to protect it at all costs. 197 Conclusion  This dissertation has investigated emerging trends in the spatial distribution of concentrated poverty and concentrated affluence at the nation-state, regional, and local scales during the 1990s. Guided by the underlying hypothesis that, similar to poverty concentration, affluence concentration is becoming increasingly suburbanized, the research has drawn upon a mixed-methodology. Methods, including the quantitative exploration of census data, comparisons of spatial indices of segregation, and multivariate regression analyses in order to assess the extent to which poverty concentration and affluence concentration demonstrate an interdependent relationship. To further understand, illustrate and articulate the material and lived social realities of these landscapes, qualitative techniques, including structured observations and photography have been employed also. Previous research on concentrated poverty has emphasized the role of such catalysts as the suburbanization of employment opportunities, racial residential segregation and White privilege to explain concentrated poverty patterns. Suburbanization of concentrated poverty has also been documented, and may be related to the rise of expensive, homogenous housing developments and gated communities in the suburbs that exclude less affluent people of color, but rely on their low-wage service labor, thus attracting low income households to suburban neighborhoods. This analysis has focused on identifying and exploring the linkages between levels of affluence concentration and increasing levels of suburbanizing concentrated poverty in the United States. A geographic focus is metro-areas in which such trends were most evident, and 198 the goal is to explore the factors responsible for recent trends, and determine the degree to which cultural and physical landscapes of poverty and affluence concentration relate to common characterizations of ‘underclass neighborhoods’ and ‘upscale communities’, respectively. Previous urban studies of inequality have generally been ‘one-sided’ in nature, focusing only on poverty concentration. However, this dissertation demonstrates that affluence matters to our understanding of spatial inequality as well and, is therefore, deserving of scholarly attention. The research demonstrates the need for a more inclusive discourse which centers not only on poverty, but spatial inequality and incorporates contributions from various social science perspectives and geographers in particular. Building upon historical research and acknowledging its contributions, the chapters which comprise this dissertation contribute to urban geographic research and present emerging viewpoints regarding the conceptualization and measurement of poverty and affluence concentration, as well as their interdependent relationship. Moreover, emphasizing the influence of factors such as globalization and attendant economic and demographic restructuring processes, this research advocates for policies that are place- specific, yet flexible and, therefore, able to meet the needs of individuals as well as address the emerging landscapes of economic polarization in the United States. To that end, in the paragraphs that follow, I summarize the major findings of this dissertation and offer suggestions for future research and analysis. This research makes noteworthy contributions to the sub-field of urban geography by challenging several long-standing assumptions. First, it stands in contrast to previous 199 research by demonstrating the linkages between urban poverty concentration, emerging landscapes of suburban poverty concentration, and affluence concentration. In doing so, it signifies that spatially concentrated poverty can no longer be considered a phenomenon that is primarily urban in nature, but instead, one that has profound regional implications. Moreover, by demonstrating its relationship to concentrated affluence within US metro- areas, it confirms the existence of an interdependent relationship between the two phenomena – a notion that has been debated within previous analyses of these phenomena (see Massey 1996 and Coulton et al. 1996). Finally, this research disproves assertions set forth within previous research, linking extreme poverty neighborhoods to the so-called Urban Underclass. Instead, within the globalizing southern California region, findings highlight the existence of several different types of poverty – among workers, immigrants (documented and undocumented), welfare recipients, and homeless people – which, depending on the mix in any one neighborhood, will be reflected in the social and built environment. In short, poverty is not a monolithic phenomenon. Therefore, while previous conceptualizations of poverty ‘concentration’ presented a very limited perspective - focusing on Blacks with behaviors that were deemed dysfunctional residing in areas characterized by physical dilapidation – more accurate depictions must be flexible and nuanced in order to diminish the possibility of misrepresentation. This study also contributes to our understanding of spatially concentrated poverty — a topic that has received little attention from geographers. Traditional research concerning poverty concentration in the United States focused on its root causes, spatial 200 distribution, and methods of measurement. However, much of this work is in need of revision. Previous analyses of the root causes of poverty concentration have centered on the prominence of class-based out-migration and historical, institutional racism, as well as their physical and social ramifications. However, this dissertation emphasizes the increasingly complex nature of concentrated poverty and suggests that causes go well beyond those operating at the level of the nation-state, requiring an investigation of the social, demographic, and political-economic reordering that is occurring on a global scale. Future research should acknowledge the influence of these macro-scale transformations on local, place-specific landscapes of poverty concentration. Measuring Poverty and Affluence Concentration Historically, the measurement of concentrated poverty centered upon metro-areas of the Midwest and East Coast, and relied upon a forty percent benchmark, that defined extreme poverty census tracts (neighborhoods) as those in which forty percent or more of the population live below the federal poverty threshold. The federal poverty threshold itself remains a subject of intense scrutiny, for the outdated, 1960s formula upon which it is based, its inability to distinguish between the needs of different family types, and insensitivity to regional variations in cost of living expenses (Citro and Michael 1995, Madden 1996, Joassart-Marcelli and Wagle 2005). Meanwhile, neither the environmental nor behavioral criteria behind the 40 percent benchmark have yet to be substantiated. This dissertation argues that, given more recent changes in the landscape of poverty concentration, including significant decreases within Midwestern and Southern 201 regions of the US and increases within inner-suburban areas, traditional notions of ‘extreme’ poverty neighborhoods, as well as inherent assumptions about their character no longer apply. Moreover, these developments suggest that much of what we knew about poverty concentration, including its urban nature, spatial distribution, as well as long-standing measurement strategies, are in need of revision. The results of the regression models constructed as part of the research reveal that the catalysts for concentrated poverty (and concentrated affluence) although related - are diverse in nature. These findings, supported by field-based research within neighborhoods of poverty and affluence concentration, demonstrate that new methods of measurement are necessary in order to accurately depict and articulate emerging conditions of economic polarization. Thus, future examinations of ‘concentration’ require measurement strategies geared to varying spatial scales and geographic regions. The empirical investigation of neighborhoods of concentrated poverty and concentrated affluence highlight the inadequacies embedded within current quantitative methods of measurement and suggest that traditional measures are unable to adequately portray the social and physical characteristics associated with emerging landscapes of poverty and affluence concentration. Results suggest that, used alone, existing metrics portray only a facet of the specific politics of place or everyday lived experience within such landscapes. More specifically, the 40 percent threshold - the standard method of concentrated poverty measurement - conjures notions of geographic spaces marked by blighted and decayed structures lining barren streets and occupied by African American residents engaged in dysfunctional behavior. However, the analysis presented in this 202 dissertation demonstrates that this is deeply misleading. Moreover, it also represents a “hands-off” approach to measurement that is based upon simple assumptions, rather than nuanced empirical research. Such false portrayals often lead to the formation of negative perceptions (such as the urban underclass) that are long lasting, difficult to overcome, and shape urban policy and anti-poverty programs in profound ways. This research also contributes to our understanding of concentrated affluence and associated measurement strategies. Previous analyses of affluence concentration focused on regional comparisons and, later, metropolitan areas. Meanwhile, methods of defining affluence and affluence thresholds typically have been based simply upon levels of household income, given various data constraints. However, like concentrated poverty, affluence is a much more complex phenomenon and involves not only income levels, but wealth (e.g. home equity, supplementary income from ownership of rental property, interest and dividends received from stock ownership, etc.) as well. With this in mind, this dissertation argues that future research should derive a more robust metric for assessing levels of concentrated affluence by incorporating both of these components into one measure. For example, concentrated affluence areas may be defined as block groups containing individuals and households that (1) earn more than $200,000 dollars in annual household income, (2) receive additional income from financial investments in the form of interest and dividends, as well as rental property, and (as home equity is often considered to be the most common form of personal wealth), (3) possess property with 203 values exceeding $500,000 dollars. Such a strategy would be better suited to address the increasing levels of complexity associated with this phenomenon. Despite their shortcomings, reliable measures of poverty and affluence concentration are essential to our ability to characterize burgeoning levels of economic polarization and make accurate comparisons across regions. That said, any measure should be both derived and utilized very carefully. In response to this challenge, this dissertation advocates for utilization of quantitative criteria that are ground-truthed using field-based, qualitative techniques. Such techniques may involve interviews, structured observations or visual methods such as photography and geographic information systems. Taking Affluence Concentration Seriously Urban geographic research has rarely concerned itself with the affluent and their spatial concentration. Therefore, our assumptions regarding neighborhoods of concentrated affluence, as well as the behaviors of wealthy residents - largely derived from anecdotal accounts and the media – may be misguided, if not, inaccurate. However, the recent expansion of concentrated poverty into inner-suburban areas, as well as the housing choice and mobility responses of the wealthy, demonstrates that the affluent and their behavior, as well as suburbs and exurbs are indeed critical to our understanding of conditions of inequality and economic polarization, in particular. Just as concentrated urban poverty and the urban underclass debate represented the dominant narrative within urban research of the 1980s and 1990s, burgeoning levels of spatially concentrated wealth should represent the principal storyline of the new 204 millennium. The multifaceted empirical analysis presented in this dissertation show that - during the 1990s - affluence concentration increased significantly within 45 of the nation’s 50 largest MSAs. Therefore, many of the MSAs previously characterized by the presence of concentrated poverty within the traditional poverty literature can now be characterized by the presence of concentrated affluence. Moreover, these findings are reinforced by the regression models constructed, which emphasize the presence of an increasingly strong correlation between affluence concentration and poverty concentration during the same time-period. Thus, this research advances the notion that an interdependent relationship exists between these two phenomena. Therefore, while the recent changes in the spatial distribution of concentrated poverty are important, the widespread augmentation of wealth is also worthy of attention, as it signals the need for a fundamental shift in the way(s) that inequality is defined and conceptualized. Finally, this research highlights the complexities present within concentrated affluence neighborhoods. In contrast to common depictions of such spaces as serene environments inhabited by residents who are White, well educated, and own luxury automobiles. Findings presented a picture that deviates in several ways. Within the selected study areas, some racial diversity existed, with one area was characterized by the predominance of Asian residents, who possessed the highest rate of homeownership despite being younger (on average) and less-educated, with many residents being recently arriving immigrants. This area was also characterized by much larger households than other concentrated affluence neighborhoods. While yielding a more realistic portrait of 205 such spaces, this also reaffirms the notion that - like neighborhoods of concentrated poverty - landscapes of affluence concentration are becoming increasingly heterogeneous as well. Similarly, the presence of various types of wealth was also revealed. Gated communities - often depicted as the standard symbol of neighborhoods of wealth and exclusion - were present within the selected study clusters of tracts. However, these were by far the minority. Instead, forms of wealth varied, sometimes within tracts of the same municipality. In particular, the study areas revealed more traditional forms of wealth as old money, characterized by the presence of both larger homes and sprawling mansions on manicured lawns. However, newer enclaves of pre-packaged wealth were present as well. These were characterized by the presence of smaller dwellings that were identical in architectural design, construction material, as well as color, and were built upon lots that also appeared to be the exact same size. Other study areas appeared to demonstrate traces of rural wealth, characterized by the presence of rugged, hilly terrain, and medium to large dwellings complete with horse stables and sizeable front setbacks. Finally, various forms of residential defensiveness were evident. Previous research on affluent landscapes has emphasized the reliance of wealthy residents on long- standing tactics such as restrictive covenants and exclusionary zoning, as well as the more recent influence of homeowner’s associations in order to create and maintain varying degrees of seclusion. In contrast, findings revealed the presence of more sophisticated and clandestine methods of ensuring cohesion amongst residents. These strategies ranged from the posting of signage urging residents to assist in maintaining the 206 high quality of education offered within local schools through monetary contributions in some neighborhoods, the widespread posting of stickers and yard signs advertising private security patrols and alarms in others, and the purposeful design of neighborhoods without street lights resulting in total nighttime darkness. While such strategies are designed to communicate messages to neighborhood residents as well as ‘outsiders’, they differ significantly from previous strategies that were overtly racist or malicious in intent. However, the provision of quality schools, the presence (or at least threat) of a strong police presence, and the provision of a quiet nighttime environment are sure to attract those who both believe in such measures and - more importantly - can afford them. These findings articulate that conventional notions of what constitutes an upscale community warrant modification, as our notions regarding their physical and social composition stand to be redefined. Policy Implications This dissertation has significant policy implications as well. First, the results of the statistical analysis revealed that regions commonly believed to be suffering solely from extreme levels of concentrated poverty can also be characterized by the presence of varying levels of affluence concentration. As these landscapes become increasingly heterogeneous and complex, policy makers must be open to the development and implementation of more flexible, innovative policies that are place-specific in nature and better able to address emerging conditions of poverty and affluence segregation, in addition to the multi-faceted needs of residents. 207 For example, federal initiatives such as the HOPE VI and Moving to Opportunity (MTO) Programs have been implemented predominantly within cities in the Midwest and East Coast with the goal of mitigating the concentration of public housing within neighborhoods of poverty concentration. Moreover, these programs work to relocate low-income families to middle-income neighborhoods so that they might attend better schools and obtain more favorable employment positions. Although, the assessment of these programs has been on-going, they have been viewed as being moderately successful. However, they have also received sharp criticism given their tendency to decrease the number of housing units in order to provide lower-density communities that allow for greater levels of social networking and urban integration. While not necessarily a problem in some areas of the Midwest and East Coast, this type of strategy represents a significant barrier for the viability of such projects in cities such as Los Angeles, which face burgeoning populations but also long-standing affordable housing crises. To that end, these and related initiatives must be sensitive to the complex nature of emerging conditions of economic polarization as well as associated place-specific factors. Also in light of burgeoning levels of economic polarization, Regionalism has been promoted as a means of spurring economic growth, while mitigating social disparities. Indeed, several successful examples such initiatives exist, with tax-base sharing in Minneapolis serving as the most notable (Orfield 1997). These types of initiatives, including alternative methods of governance, carry with them the potential to curb declining infrastructures - particularly within inner suburban areas - by improving levels of municipal service delivery and educational systems, while alleviating private-sector 208 disinvestment - thus providing much-needed stability. However, the ability of these initiatives to benefit the entire region, rather than individual municipalities alone depends heavily upon the ability of advocates to package them in ways that make them attractive to all residents. Particularly within inner-suburban areas, African Americans (and members of other historically marginalized groups) may be less likely to buy into strategies that require them to share resources that are miniscule at best, unless the benefits and rewards are presented in very clear and tangible ways. With respect to wealth segregation, future studies should investigate the ways in which class and race-based fears, crime, and other perceived behavioral tendencies associated with the inner-city play a role in the affluence concentration process, despite the fact that inner-city stereotypes no longer characterize many areas of concentrated poverty. However, we need to understand where such fears come from and what continues to drive them (for ex: local media reports driven by crime reporting, long- standing fears of people of color, including immigrants)? Additionally, with respect to burgeoning levels of economic polarization, several issues regarding the wealthy remain as well. For example, what do NIMBY attitudes regarding the development of affordable housing, the enactment of exclusionary zoning ordinances, and a bias in favor of home rule that results in an unwillingness of the affluent to tax themselves for the betterment of their region tell us about this particular population and their desires to remain separate from the rest of urban society? Finally, in light of the changing faces of both poverty and affluence, future analyses should assess whether or not more recent examples of urban renaissance, 209 including gentrified inner-city developments, gated enclaves, and New Urbanist villages within central cities has played a role in increasing levels of poverty concentration within inner-ring suburbs. Broadening our knowledge and understanding of the formation and maintenance of privatized public spaces, such as gated communities may serve as the first step in the development and advancement of policies aimed at mitigating such conditions. 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Creator Sessoms, Nathan J. (author)

Core Title The changing geographies of concentrated poverty and concentrated affluence in the United States, 1990-2000

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Geography

Publication Date 05/20/2010

Defense Date 01/22/2010

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

Tag 40 percent threshold,concentrated affluence,concentrated poverty,economic polarization,OAI-PMH Harvest,urban underclass

Place Name USA (countries)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Wolch, Jennifer R. (committee chair), Myers, Dowell (committee member), Pulido, Laura (committee member)

Creator Email njsessoms@hotmail.com,sessoms@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m3088

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