A Note on Endogenous Control Variables in Evaluation Studies
The paper addresses the issue of potentially endogenous control variables in evaluation studies based on the assumption that selection bias can be avoided by conditioning on observed variables. It shows that the standard formulation of the conditional independence (CIA) or selection on observables assumption obscures the endogeneity problem. The paper clarifies the issue by suggesting a CIA based on exogenous (potential) outcomes as well as explicit exogeneity conditions. The refined CIA allows to asses the endogeneity bias as well as the plausibility of the CIA, because it allows a separate discussion of (i) the problems of missing variables that are necessary to avoid selection bias, and (ii) the problem that some of the control variables may be influenced by the treatment.
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- Donald B. Rubin, 2004. "Direct and Indirect Causal Effects via Potential Outcomes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(2), pages 161-170.
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- Donald B. Rubin, 2005. "Causal Inference Using Potential Outcomes: Design, Modeling, Decisions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 322-331, March.
- Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
- Guido W. Imbens, 2003. "Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review," NBER Technical Working Papers 0294, National Bureau of Economic Research, Inc.