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Exogenous Treatment and Endogenous Factors: Vanishing of Omitted Variable Bias on the Interaction Term

Author

Listed:
  • Nizalova, Olena Y.

    (University of Kent)

  • Murtazashvili, Irina

    (Drexel University)

Abstract

Whether interested in the differential impact of a particular factor in various institutional settings or in the heterogeneous effect of policy or random experiment, the empirical researcher confronts a problem if the factor of interest is correlated with an omitted variable. This paper considers circumstances under which the estimate of the mentioned effect is consistent. We find that if the source of heterogeneity and omitted variable are jointly independent of policy or treatment, then the OLS estimate on the interaction term between the treatment and endogenous factor turns out to be consistent.

Suggested Citation

  • Nizalova, Olena Y. & Murtazashvili, Irina, 2012. "Exogenous Treatment and Endogenous Factors: Vanishing of Omitted Variable Bias on the Interaction Term," IZA Discussion Papers 6282, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp6282
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    References listed on IDEAS

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    1. Abhijit V. Banerjee & Shawn Cole & Esther Duflo & Leigh Linden, 2007. "Remedying Education: Evidence from Two Randomized Experiments in India," The Quarterly Journal of Economics, Oxford University Press, vol. 122(3), pages 1235-1264.
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    3. Sylvie Moulin & Michael Kremer & Paul Glewwe, 2009. "Many Children Left Behind? Textbooks and Test Scores in Kenya," American Economic Journal: Applied Economics, American Economic Association, vol. 1(1), pages 112-135, January.
    4. Blank, Rebecca M, 1991. "The Effects of Double-Blind versus Single-Blind Reviewing: Experimental Evidence from The American Economic Review," American Economic Review, American Economic Association, vol. 81(5), pages 1041-1067, December.
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    More about this item

    Keywords

    treatment effect; heterogeneity; policy evaluation; random experiments; omitted variable bias;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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