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Individual determinants of homelessness: A descriptive approach

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  • Jarvis, Justin

Abstract

In this paper, I utilize a novel data set collected in 2012 to investigate the determinants of homelessness intensity among those who are street homeless in Costa Mesa, California. By restricting the sample to only those who are already homeless and introducing the concept of a homelessness intensity measure, I exploit variation in individual characteristics and usage of a Check-In Center to predict the intensity of homelessness (defined as the ratio of actual homeless nights to potential homeless nights). By making use of a novel application of the weighted least squares estimator, I am able to estimate coefficients that are design-unbiased for the population values. By using an instrument, I find that the Check-In Center has a large negative effect on the intensity of homelessness. The self-reported cause of homelessness is a determining factor as well. I also find, as would be expected, that education and the presence of family nearby lessens the intensity of homelessness.

Suggested Citation

  • Jarvis, Justin, 2015. "Individual determinants of homelessness: A descriptive approach," Journal of Housing Economics, Elsevier, vol. 30(C), pages 23-32.
  • Handle: RePEc:eee:jhouse:v:30:y:2015:i:c:p:23-32
    DOI: 10.1016/j.jhe.2015.10.001
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    References listed on IDEAS

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    1. Goodman, Sarena & Messeri, Peter & O’Flaherty, Brendan, 2014. "Reprint of “How effective homelessness prevention impacts the length of shelter spells”," Journal of Housing Economics, Elsevier, vol. 24(C), pages 101-108.
    2. John Quigley & Steven Raphael, 2001. "The Economics Of Homelessness: The Evidence From North America," International Journal of Housing Policy, Taylor & Francis Journals, vol. 1(3), pages 323-336.
    3. Goodman, Sarena & Messeri, Peter & O’Flaherty, Brendan, 2014. "How effective homelessness prevention impacts the length of shelter spells," Journal of Housing Economics, Elsevier, vol. 23(C), pages 55-62.
    4. William J Carrington & John L Eltinge & Kristin McCue, 2000. "An Economist's Primer on Survey Samples," Working Papers 00-15, Center for Economic Studies, U.S. Census Bureau.
    5. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    6. M. Braga & L. Corno, 2011. "Being Homeless: Evidence from Italy," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 70(3), pages 33-73, December.
    7. Honig, Marjorie & Filer, Randall K, 1993. "Causes of Intercity Variation in Homelessness," American Economic Review, American Economic Association, vol. 83(1), pages 248-255, March.
    8. Jeffrey M. Wooldridge, 1999. "Asymptotic Properties of Weighted M-Estimators for Variable Probability Samples," Econometrica, Econometric Society, vol. 67(6), pages 1385-1406, November.
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    More about this item

    Keywords

    Homelessness; Development; Regional inequality; Labor supply;

    JEL classification:

    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General
    • J4 - Labor and Demographic Economics - - Particular Labor Markets
    • J6 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers
    • O2 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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