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Does residential location matter to the employment of TANF recipients Evidence from a dynamic discrete choice model with unobserved effects

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  • Gurmu, Shiferaw
  • Ihlanfeldt, Keith R.
  • Smith, William J.

Abstract

We study the factors affecting the employment probability of temporary assistance for needy families (TANF) recipients using recent quarterly panel data from Atlanta, Georgia. A central focus of our study is to determine whether the TANF recipient's proximity to job opportunity and the availability of childcare affect her probability of full-time employment. Both static and dynamic models of employment choice are estimated that control for unobserved individual effects. We estimate models separately for a sub-sample of TANF recipients living in public housing, whose residential locations can be considered exogenously determined. We find substantial evidence that individual and family characteristics (such as, the education of the recipient and the number of children and adults in her family) are important determinants of the employment probability of welfare recipients. On the other hand, location-related variables are found to be relatively unimportant.

Suggested Citation

  • Gurmu, Shiferaw & Ihlanfeldt, Keith R. & Smith, William J., 2008. "Does residential location matter to the employment of TANF recipients Evidence from a dynamic discrete choice model with unobserved effects," Journal of Urban Economics, Elsevier, vol. 63(1), pages 325-351, January.
    • Handle: RePEc:eee:juecon:v:63:y:2008:i:1:p:325-351
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    References listed on IDEAS

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    1. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
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    Cited by:

    1. Weinhardt, Felix, 2010. "Moving into the projects: social housing neighbourhoods and school performance in England," LSE Research Online Documents on Economics 33612, London School of Economics and Political Science, LSE Library.
    2. Krupka, Douglas J. & Noonan, Douglas S., 2009. "Empowerment Zones, neighborhood change and owner-occupied housing," Regional Science and Urban Economics, Elsevier, vol. 39(4), pages 386-396, July.
    3. Olof Åslund & John Östh & Yves Zenou, 2010. "How important is access to jobs? Old question--improved answer," Journal of Economic Geography, Oxford University Press, vol. 10(3), pages 389-422, May.
    4. David J. Harding & Lisa Sanbonmatsu & Greg J. Duncan & Lisa A. Gennetian & Lawrence F. Katz & Ronald C. Kessler & Jeffrey R. Kling & Matthew Sciandra & Jens Ludwig, 2023. "Evaluating Contradictory Experimental and Nonexperimental Estimates of Neighborhood Effects on Economic Outcomes for Adults," Housing Policy Debate, Taylor & Francis Journals, vol. 33(2), pages 453-486, March.
    5. Weinhardt, Felix, 2014. "Social housing, neighborhood quality and student performance," Journal of Urban Economics, Elsevier, vol. 82(C), pages 12-31.
    6. Haney, Timothy, 2012. "Off to Market: Neighborhood and Individual Employment Barriers for Women in 21st Century American Cities," SocArXiv 57e4a, Center for Open Science.
    7. Lee, Han Bum & McNamara, Paul E., 2017. "Deconcentrating the poor via public housing policy: What really matters?," Socio-Economic Planning Sciences, Elsevier, vol. 59(C), pages 67-78.
    8. Merlin, Louis A. & Hu, Lingqian, 2017. "Does competition matter in measures of job accessibility? Explaining employment in Los Angeles," Journal of Transport Geography, Elsevier, vol. 64(C), pages 77-88.
    9. Urena Serulle, Nayel & Cirillo, Cinzia, 2017. "The optimal time to evacuate: A behavioral dynamic model on Louisiana resident data," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 447-463.
    10. Baum, Charles L., 2009. "The effects of vehicle ownership on employment," Journal of Urban Economics, Elsevier, vol. 66(3), pages 151-163, November.

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