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Combining information from Heckman and matching estimators: testing and controlling for hidden bias

Author

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  • Gerry H. Makepeace

    (Cardiff Business School, Cardiff University and IZA, Bonn)

  • Michael J. Peel

    (Cardiff Business School, Cardiff University)

Abstract

We demonstrate how the Heckman methodology can be applied to the Rosenbaum sensitivity model and the Rubin matched difference estimator. We develop a statistical test of the conditional independence assumption (CIA), based on Heckit for matched pairs. If the CIA is rejected, the method facilitates the estimation of matched treatment effects adjusted for hidden bias. We illustrate this methodology empirically for the full-time/part-time pay gap for British women. The proposed method has clear utility in establishing whether propensity score matched treatment estimates are prone to unobserved selection bias and for controlling for such bias

Suggested Citation

  • Gerry H. Makepeace & Michael J. Peel, 2013. "Combining information from Heckman and matching estimators: testing and controlling for hidden bias," Economics Bulletin, AccessEcon, vol. 33(3), pages 2422-2436.
    • Handle: RePEc:ebl:ecbull:eb-13-00321
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    Cited by:

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    2. Liu, Haiyue & Wang, Yile & Huang, Ling & Zhang, Xueyong, 2021. "Outward FDI and stock price crash risk---Evidence from China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).

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    More about this item

    Keywords

    matching; Rosenbaum bounds; Heckit; unobserved bias; women's part-time pay penalty;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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