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Treatment Interaction with Non-Experimental Data in Stata

Author

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  • Graham Brown

    (University of Bath)

  • Thanos Mergoupis

    (University of Bath)

Abstract

Treatment effects may vary with the observed characteristics of the treated, often with important implications. In the context of experimental data, a growing literature deals with the problem of specifying treatment interaction terms that most effectively capture this variation. Some of the results of this literature are now implemented in Stata. With non-experimental (observational) data, and in particular when selection into treatment depends on unmeasured factors, treatment effects can be estimated using Stata's treatreg command. Although not originally designed for this purpose, treatreg can be used to consistently estimate treatment interactions parameters. In the presence of interactions, however, adjustments are required to generate predicted values and estimate the Average Treatment Effect (ATE). This paper introduces commands that perform this adjustment for the case of multiplicative interactions and shows the adjustment that is required for more complicated interactions.

Suggested Citation

  • Graham Brown & Thanos Mergoupis, 2010. "Treatment Interaction with Non-Experimental Data in Stata," Department of Economics Working Papers 10/10, University of Bath, Department of Economics.
    • Handle: RePEc:eid:wpaper:20960
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    References listed on IDEAS

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    1. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    2. Sauerbrei, Willi & Royston, Patrick & Zapien, Karina, 2007. "Detecting an interaction between treatment and a continuous covariate: A comparison of two approaches," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 4054-4063, May.
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    Cited by:

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