Joblessness and poverty in America's central cities: Causes and policy prescriptions

Abstract

Two paradigms pervade the policy debate on the causes of urban joblessness and poverty: (1) a structural, nonvoluntaristic perspective emphasizing the roles of urban economic change, residential segregation, and spatial and skills mismatches, and (2) a rational-choice, voluntaristic perspective contending that the generosity and ready availability of welfare programs have removed the incentive for poor persons to accept low-paying jobs. This article brings together propositions of each paradigm into a comprehensive theoretical model. The study measured and tested key causal operators of the model for a sample of 67 large U.S. cities, with special attention to race and gender.Results show that structural and welfare disincentive perspectives are not in conflict but rather operate side by side to reinforce joblessness and poverty. Race and gender, especially the role of urban space for women's work, are important. The article raises pertinent policy issues derived from the two perspectives and from the analysis.

Exploring the connections among job accessibility, employment, income, and auto ownership using structural equation modeling

“…Income and auto ownership also affect residential location choice and job accessibility (Holzer 1991;Schimek 1996). Job accessibility, education attainment, and auto ownership are expected to have positive impacts on employment (Cervero et al 2000;Kasarda and Ting 1996;Kockelman 1997;Ong and Blumenberg 1998), while living in a single-headed household with children is hypothesized to have negative impacts on employment due to heavy family responsibilities. It is plausible to assume that auto ownership is a function of job accessibility, employment, income, and household size (Dargay 2001;Kockelman 1997).…”

Spatial mismatch, transport mode and search decisions in England

“…Relationship between estimated search intensities and job access differences between races. the importance of transport mode in shaping job seekers search decisions is empirically validated by the positive and significant estimate of the coefficient of the car ownershipusage ratio (δ) in both model (17) and (18). Clearly, this difference in search intensity is also due to unobservable factors (such as workers' discrimination).…”

“…skill composition, population structure, economic activity, 16 sectoral composition, income and wealth, cost of living, labor market conditions, ethnic composition among NUTS3 areas respectively. 17 Precise definitions of all variables used in the empirical analysis can be found in Appendix B. Table 1 contains the summary statistics of all variables.…”

“…16 The correlation between the activity rate (labor force over residing population aged 16-64) and our indicator of search intensity is far from perfect, showing a correlation coefficient of 0.63. 17 All data can be obtained on line from the NOMIS database run by the University of Durham (on behalf of the Office for National Statistics, Labour Market Statistics Group) or in the UK Data Archive with the exception of house prices, that are available on line from the HM Land Registry. We acknowledge the original data creators and depositors.…”

The Causes of Inner-City Poverty: Eight Hypotheses in Search of Reality

“…Discrimination in employment persists even when minority workers have good geographic access to opportunities (Turner, 1997). Overall, industrial transformation has a far greater impact on job prospects for inner-city residents who are African American than for those who are white (Kasarda and Ting, 1996).…”