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The matching method for treatment evaluation with selective participation and ineligibles

Author

Listed:
  • Monica Costa Dias

    (Institute for Fiscal Studies and Institute for Fiscal Studies)

  • Hidehiko Ichimura

    (Institute for Fiscal Studies and University of Arizona, University of Tokyo)

  • Gerard Van Den Berg

    (Institute for Fiscal Studies and University of Mannheim)

Abstract

The matching method for treatment evaluation does not balance selective unobserved differences between treated and non-treated. We derive a simple correction term if there is an instrument that shifts the treatment probability to zero in specific cases. Within the same framework we also suggest a new test of the conditional independence assumption justifying matching. Policies with eligibility restrictions, where treatment is impossible if some variable exceeds a certain value, provide a natural application. In an empirical analysis, we exploit the age eligibility restriction in the Swedish Youth Practice subsidized work program for young unemployed, where compliance is imperfect among the young. Adjusting the matching estimator for selectivity changes the results towards making of subsidized work detrimental in moving individuals into employment. This paper is a revised version of cemmap working paper CWP33/07.

Suggested Citation

  • Monica Costa Dias & Hidehiko Ichimura & Gerard Van Den Berg, 2010. "The matching method for treatment evaluation with selective participation and ineligibles," CeMMAP working papers CWP35/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:35/10
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    File URL: http://cemmap.ifs.org.uk/wps/cwp3510.pdf
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    Cited by:

    1. de Luna Xavier & Johansson Per, 2014. "Testing for the Unconfoundedness Assumption Using an Instrumental Assumption," Journal of Causal Inference, De Gruyter, vol. 2(2), pages 187-199, September.
    2. Gerard J. van den Berg & Antoine Bozio & Mónica Costa Dias, 2020. "Policy discontinuity and duration outcomes," Quantitative Economics, Econometric Society, vol. 11(3), pages 871-916, July.
    3. de Luna, Xavier & Johansson, Per, 2012. "Testing for Nonparametric Identification of Causal Effects in the Presence of a Quasi-Instrument," IZA Discussion Papers 6692, Institute of Labor Economics (IZA).
    4. Joseph, Olivier & Pailhé, Ariane & Recotillet, Isabelle & Solaz, Anne, 2013. "The economic impact of taking short parental leave: Evaluation of a French reform," Labour Economics, Elsevier, vol. 25(C), pages 63-75.
    5. Bruno Arpino & Arnstein Aassve, 2013. "Estimating the causal effect of fertility on economic wellbeing: data requirements, identifying assumptions and estimation methods," Empirical Economics, Springer, vol. 44(1), pages 355-385, February.

    More about this item

    Keywords

    evaluation;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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