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Should instrumental variables be used as matching variables?

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  • Wooldridge, Jeffrey M.

Abstract

I show that for a linear model and estimating a coefficient on an endogenous explanatory variable, adding covariates that satisfy instrumental variables assumptions increases the amount of inconsistency. A special case is an endogenous binary treatment and estimating a constant treatment effect when matching on covariates that satisfy instrumental variables, rather than ignoribility, assumptions. I also establish a general result that implies that regression adjustment using the propensity score based on instrumental variables actually maximizes the inconsistency among regression-type estimators.

Suggested Citation

  • Wooldridge, Jeffrey M., 2016. "Should instrumental variables be used as matching variables?," Research in Economics, Elsevier, vol. 70(2), pages 232-237.
    • Handle: RePEc:eee:reecon:v:70:y:2016:i:2:p:232-237
    DOI: 10.1016/j.rie.2016.01.001
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    References listed on IDEAS

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    1. James Heckman & Salvador Navarro-Lozano, 2004. "Using Matching, Instrumental Variables, and Control Functions to Estimate Economic Choice Models," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 30-57, February.
    2. Wooldridge, Jeffrey M., 2005. "Violating Ignorability Of Treatment By Controlling For Too Many Factors," Econometric Theory, Cambridge University Press, vol. 21(5), pages 1026-1028, October.
    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
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