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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. Lise, Jeremy & Seitz, Shannon & Smith, Jeffrey, 2003. "Equilibrium Policy Experiments and the Evaluation of Social Programs," Queen's Economics Department Working Papers 273439, Queen's University - Department of Economics.
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    9. Kenneth I. Wolpin & Petra E. Todd, 2006. "Assessing the Impact of a School Subsidy Program in Mexico: Using a Social Experiment to Validate a Dynamic Behavioral Model of Child Schooling and Fertility," American Economic Review, American Economic Association, vol. 96(5), pages 1384-1417, December.
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    12. Christopher Ferrall, 2005. "Solving Finite Mixture Models: Efficient Computation in Economics Under Serial and Parallel Execution," Computational Economics, Springer;Society for Computational Economics, vol. 25(4), pages 343-379, June.
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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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    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.
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    6. Ferrall, Christopher, 2002. "Estimation and Inference in Social Experiments," Queen's Economics Department Working Papers 273435, Queen's University - Department of Economics.
    7. Sebastian Galiani & Juan Pantano, 2021. "Structural Models: Inception and Frontier," NBER Working Papers 28698, National Bureau of Economic Research, Inc.
    8. 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.
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    11. 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.
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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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