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This paper proposes four metrics to measure sprawl in metropolitan regions as marginal changes in land use over time. The metrics (change in urban housing unit density, marginal land consumption per new urban household, housing unit density in newly urbanized areas and percent of new housing units located in previously developed areas) are computed for all 329 metropolitan areas in the continental USA for 1980 and 2000. Regression analysis is used to explain variations in sprawl metrics across metropolitan areas, incorporating variables representing market, geographic and policy factors. Changes in development patterns reflect interactions of market and geographic structures. States with a substantial state role in planning accommodate a higher percentage of new housing units in previously developed areas and with lower marginal land consumption, suggesting that policy can mitigate sprawl development.

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In this study, we examine the effect of access to employment opportunities on labour market outcomes, especially focusing on unemployment rates and household income in the Chicago metropolitan area during 2000–2010. Using accessibility measures derived from detailed employment data, we calculate job accessibility by race and income. In order to deal with the endogeneity problem, we employ instrumental variables with a generalised spatial two-stage least square (GS2SLS) model with fixed-effects. Our findings suggest that job accessibility plays a significant role in explaining unemployment rates and household income. Consistent with Kain’s spatial mismatch hypothesis, increases in job accessibility for African Americans lead to decreases in unemployment. Results also show that increased job accessibility for low-income households not only reduce unemployment but also improve household income.

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