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The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators

Author

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  • Bodory, Hugo

    (University of St. Gallen)

  • Camponovo, Lorenzo

    (University of St. Gallen)

  • Huber, Martin

    (University of Fribourg)

  • Lechner, Michael

    (University of St. Gallen)

Abstract

This paper investigates the finite sample properties of a range of inference methods for propensity score-based matching and weighting estimators frequently applied to evaluate the average treatment effect on the treated. We analyse both asymptotic approximations and bootstrap methods for computing variances and confidence intervals in our simulation design, which is based on large scale labor market data from Germany and varies w.r.t. treatment selectivity, effect heterogeneity, the share of treated, and the sample size. The results suggest that in general, the bootstrap procedures dominate the asymptotic ones in terms of size and power for both matching and weighting estimators. Furthermore, the results are qualitatively quite robust across the various simulation features.

Suggested Citation

  • Bodory, Hugo & Camponovo, Lorenzo & Huber, Martin & Lechner, Michael, 2016. "The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators," IZA Discussion Papers 9706, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9706
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    References listed on IDEAS

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    12. Michael Lechner & Anthony Strittmatter, 2019. "Practical procedures to deal with common support problems in matching estimation," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 193-207, February.
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    19. Martin Huber & Michael Lechner & Andreas Steinmayr, 2015. "Radius matching on the propensity score with bias adjustment: tuning parameters and finite sample behaviour," Empirical Economics, Springer, vol. 49(1), pages 1-31, August.
    20. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
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    Cited by:

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    2. Ferman, Bruno, 2017. "Matching Estimators with Few Treated and Many Control Observations," MPRA Paper 78940, University Library of Munich, Germany.
    3. Arun Advani & Toru Kitagawa & Tymon Słoczyński, 2019. "Mostly harmless simulations? Using Monte Carlo studies for estimator selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 893-910, September.
    4. Lombardi, Stefano & van den Berg, Gerard J. & Vikström, Johan, 2020. "Empirical Monte Carlo evidence on estimation of Timing-of-Events models," Working Paper Series 2020:26, IFAU - Institute for Evaluation of Labour Market and Education Policy, revised 05 Jan 2021.
    5. Krumer, Alex & Lechner, Michael, 2016. "Midweek Effect on Performance: Evidence from the German Soccer Bundesliga," Economics Working Paper Series 1609, University of St. Gallen, School of Economics and Political Science.
    6. Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2017. "The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 91-102.
    7. Cushman, David O. & De Vita, Glauco, 2017. "Exchange rate regimes and FDI in developing countries: A propensity score matching approach," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 143-163.
    8. Advani, Arun & Sloczynski, Tymon, 2013. "Mostly Harmless Simulations? On the Internal Validity of Empirical Monte Carlo Studies," IZA Discussion Papers 7874, Institute of Labor Economics (IZA).
    9. Donna Feir & Kelly Foley & Maggie E. C. Jones, 2021. "The Distributional Impacts of Active Labor Market Programs for Indigenous Populations," AEA Papers and Proceedings, American Economic Association, vol. 111, pages 216-220, May.
    10. Krumer, Alex & Lechner, Michael, 2016. "First In First Win: Evidence on Unfairness of Round-Robin Tournaments in Mega-Events," Economics Working Paper Series 1611, University of St. Gallen, School of Economics and Political Science.
    11. Lajos Baráth & Imre Fertő & Štefan Bojnec, 2020. "The Effect of Investment, LFA and Agri‐environmental Subsidies on the Components of Total Factor Productivity: The Case of Slovenian Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 853-876, September.
    12. Strittmatter, Anthony & Lechner, Michael, 2020. "Sorting in the used-car market after the Volkswagen emission scandal," Journal of Environmental Economics and Management, Elsevier, vol. 101(C).
    13. Goller, Daniel & Krumer, Alex, 2019. "Let’s meet as usual: Do games on non-frequent days differ? Evidence from top European soccer leagues," Economics Working Paper Series 1907, University of St. Gallen, School of Economics and Political Science.
    14. Huber, Martin & Camponovo, Lorenzo & Bodory, Hugo & Lechner, Michael, 2016. "A wild bootstrap algorithm for propensity score matching estimators," FSES Working Papers 470, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    15. Finn Tarp & Sam Jones & Felix Schilling, 2021. "Doing business while holding public office: Evidence from Mozambique’s firm registry," DERG working paper series 21-08, University of Copenhagen. Department of Economics. Development Economics Research Group (DERG).
    16. Caliendo, Marco & Tübbicke, Stefan, 2019. "Do Start-Up Subsidies for the Unemployed Affect Participants' Well-Being? A Rigorous Look at (Un-)Intended Consequences of Labor Market Policies," IZA Discussion Papers 12755, Institute of Labor Economics (IZA).
    17. Goller, Daniel & Krumer, Alex, 2020. "Let's meet as usual: Do games played on non-frequent days differ? Evidence from top European soccer leagues," European Journal of Operational Research, Elsevier, vol. 286(2), pages 740-754.
    18. Krumer, Alex & Lechner, Michael, 2017. "First in first win: Evidence on schedule effects in round-robin tournaments in mega-events," European Economic Review, Elsevier, vol. 100(C), pages 412-427.
    19. Alex Krumer & Michael Lechner, 2018. "Midweek Effect On Soccer Performance: Evidence From The German Bundesliga," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 193-207, January.

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    More about this item

    Keywords

    inference; variance estimation; treatment effects; matching; inverse probability weighting;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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