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Treatment interactions with nonexperimental data in Stata

Author

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  • Graham K. 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 results of this literature are now implemented in Stata. With nonexperimental (observational) data, and in particular when selection into treatment depends on unmeasured factors, treatment effects can be estimated using Stata’s treatreg command. Though not originally designed for this purpose, treatreg can be used to consistently estimate treatment interaction parameters. With interactions, however, adjustments are required to generate predicted values and estimate the average treatment effect. In this article, we introduce commands that perform this adjustment for multiplicative interactions, and we show the required adjustment for more complicated interactions. Copyright 2011 by StataCorp LP.

Suggested Citation

  • Graham K. Brown & Thanos Mergoupis, 2011. "Treatment interactions with nonexperimental data in Stata," Stata Journal, StataCorp LP, vol. 11(4), pages 545-555, December.
    • Handle: RePEc:tsj:stataj:v:11:y:2011:i:4:p:545-555
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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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