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Explaining and Forecasting Results of the Self-sufficiency Project

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  • Christopher Ferrall

Abstract

This paper studies the self-sufficiency project (SSP), a controlled randomized experiment concerning welfare, by estimating a model of endogenous skill accumulation, multidimensional job opportunities, and time-varying opportunity costs of labour market time. Methods for estimating dynamic programming models with unobserved heterogeneity are extended to account for unexpected policy interventions and endogenous sample selection and initial conditions. Parameters are identified and consistently estimated by imposing optimal responses to the exact form of the SSP earnings supplement and the experimental program, which induces exogenous variation between treatment groups and within groups as treatment progresses. The estimated model tracks primary outcomes well in and out of sample, except for underestimating trends in the sample of new welfare applicants. Predictions from counterfactual experiments run counter to non-structural results reported elsewhere, and they suggest that details of the SSP's design are critical for interpretation of results. The separate SSP Plus treatment may have longer lasting and more generalized impacts than the in-sample impacts suggest. Copyright , Oxford University Press.

Suggested Citation

  • Christopher Ferrall, 2012. "Explaining and Forecasting Results of the Self-sufficiency Project," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(4), pages 1495-1526.
  • Handle: RePEc:oup:restud:v:79:y:2012:i:4:p:1495-1526
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    File URL: http://hdl.handle.net/10.1093/restud/rds008
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    1. GMM and its application outside finance
      by Chris Auld in ChrisAuld.com on 2013-10-22 00:55:38

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    Cited by:

    1. Marc K. Chan & Kai Liu, 2018. "Life‐cycle and intergenerational effects of child care reforms," Quantitative Economics, Econometric Society, vol. 9(2), pages 659-706, July.
    2. Schorfheide, Frank & Wolpin, Kenneth I., 2016. "To hold out or not to hold out," Research in Economics, Elsevier, vol. 70(2), pages 332-345.
    3. Christopher Ferrall, 2002. "Estimation And Inference In Social Experiments," Working Paper 1008, Economics Department, Queen's University.
    4. Jeremy Lise & Shannon Seitz & Jeffrey Smith, 2015. "Evaluating search and matching models using experimental data," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-35, December.
    5. Pierre Cahuc & Stéphane Carcillo & Thomas Le Barbanchon, 2019. "The Effectiveness of Hiring Credits," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(2), pages 593-626.
    6. Sebastian Galiani & Juan Pantano, 2021. "Structural Models: Inception and Frontier," NBER Working Papers 28698, National Bureau of Economic Research, Inc.
    7. Pierre Cahuc & Pauline Carry & Franck Malherbet & Pedro S Martins, 2022. "Employment Effects of Restricting Fixed-Term Contracts: Theory and Evidence," Working Papers hal-03881622, HAL.
    8. repec:hal:spmain:info:hdl:2441/3dn0o0jvtp972r5lmr1fd29k5c is not listed on IDEAS
    9. R. Vincent Pohl, 2018. "Medicaid And The Labor Supply Of Single Mothers: Implications For Health Care Reform," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(3), pages 1283-1313, August.
    10. Marc K. Chan, 2017. "Welfare Dependence and Self-Control: An Empirical Analysis," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(4), pages 1379-1423.
    11. Maibom, Jonas, 2021. "The Welfare Effects of Mandatory Reemployment Programs: Combining a Structural Model and Experimental Data," IZA Discussion Papers 14866, Institute of Labor Economics (IZA).
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    13. Esther Duflo & Rema Hanna & Stephen P. Ryan, 2012. "Incentives Work: Getting Teachers to Come to School," American Economic Review, American Economic Association, vol. 102(4), pages 1241-1278, June.

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    More about this item

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • J0 - Labor and Demographic Economics - - General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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