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Benefit–Cost Analysis of an Innovative Program for Self-Sufficiency and Homeownership

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Listed:
  • George C. Galster
  • Anna Maria Santiago
  • Richard J. Smith
  • Joffre Leroux

Abstract

Background: Federal policy has increasingly sought to build financial capability, earnings, and assets of subsidized housing recipients. Objective: We conduct a benefit–cost analysis of the Denver Housing Authority’s (DHA) innovative Home Ownership Program (HOP), which incentivizes participants to increase earnings, build wealth, and purchase homes. Research design, subjects, and measures: In assessing HOP participant benefits (earnings, home-buying, and positive exits from DHA), we use parameter estimates from quasi-experimental methods (i.e., propensity score matching) that permit drawing causal inferences of program impacts. Impact estimates are robust to alternate model specification and mostly insensitive to omitted variable bias found in the social sciences. We deploy a comprehensive accounting framework, distinguishing benefits and costs accruing to program participants, nonparticipants (other citizens, taxpayers, and governments), and society as a whole. We use Monte Carlo simulation techniques to approximate distributions of benefit and cost parameters, thereby ascertaining how reliably participation in HOP yielded net benefits compared to if families had continued to receive housing assistance during the same period. Results: We estimate a net social benefit from HOP of US$6,015 per participant. The simulated standard deviation was only a third of this value and 99.9% of simulations returned positive net social benefits. Conclusion: We conclude with a high degree of statistical confidence that HOP produced substantial net benefits to society as a whole, program participants, and nonparticipants alike. HOP offers strong potential for poverty alleviation among housing subsidy recipients and should be replicated.

Suggested Citation

  • George C. Galster & Anna Maria Santiago & Richard J. Smith & Joffre Leroux, 2019. "Benefit–Cost Analysis of an Innovative Program for Self-Sufficiency and Homeownership," Evaluation Review, , vol. 43(1-2), pages 3-40, February.
    • Handle: RePEc:sae:evarev:v:43:y:2019:i:1-2:p:3-40
    DOI: 10.1177/0193841X19846697
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    References listed on IDEAS

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    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    2. Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
    3. Shadish, William R. & Clark, M. H. & Steiner, Peter M., 2008. "Can Nonrandomized Experiments Yield Accurate Answers? A Randomized Experiment Comparing Random and Nonrandom Assignments," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1334-1344.
    4. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, WZB Berlin Social Science Center.
    5. Galster, George & Santiago, Anna & Stack, Lisa & Cutsinger, Jackie, 2016. "Neighborhood effects on secondary school performance of Latino and African American youth: Evidence from a natural experiment in Denver," Journal of Urban Economics, Elsevier, vol. 93(C), pages 30-48.
    6. Abadie, Alberto & Imbens, Guido W., 2011. "Bias-Corrected Matching Estimators for Average Treatment Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 1-11.
    7. Simon Condliffe & Charles R. Link, 2008. "The Relationship between Economic Status and Child Health: Evidence from the United States," American Economic Review, American Economic Association, vol. 98(4), pages 1605-1618, September.
    8. James Heckman & Salvador Navarro-Lozano, 2004. "Using Matching, Instrumental Variables, and Control Functions to Estimate Economic Choice Models," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 30-57, February.
    9. George Galster & Anna Maria Santiago, 2017. "Do Neighborhood Effects on Low-Income Minority Children Depend on Their Age? Evidence From a Public Housing Natural Experiment," Housing Policy Debate, Taylor & Francis Journals, vol. 27(4), pages 584-610, July.
    10. Clemmer, Richard B., 1984. "Measuring welfare effects of in-kind transfers," Journal of Urban Economics, Elsevier, vol. 15(1), pages 46-65, January.
    11. Deven Carlson & Robert Haveman & Thomas Kaplan & Barbara Wolfe, 2011. "The benefits and costs of the Section 8 housing subsidy program: A framework and estimates of first‐year effects," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 30(2), pages 233-255, March.
    12. DiPasquale, Denise & Glaeser, Edward L., 1999. "Incentives and Social Capital: Are Homeowners Better Citizens?," Journal of Urban Economics, Elsevier, vol. 45(2), pages 354-384, March.
    13. Reeder, William J., 1985. "The benefits and costs of the section 8 existing housing program," Journal of Public Economics, Elsevier, vol. 26(3), pages 349-377, April.
    14. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    15. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(3), pages 199-236, July.
    16. Murray, Michael P, 1975. "The Distribution of Tenant Benefits in Public Housing," Econometrica, Econometric Society, vol. 43(4), pages 771-788, July.
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