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Difference‐in‐Differences With a Misclassified Treatment

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  • Akanksha Negi
  • Digvijay S. Negi

Abstract

This paper studies identification and estimation of the average treatment effect of a latent treated subpopulation in difference‐in‐difference designs when the observed treatment is differentially (or endogenously) mismeasured for the truth. Common examples include misreporting and mistargeting. We propose a two‐step estimator that corrects for the empirically common phenomenon of one‐sided misclassification in the treatment status. The solution uses a single exclusion restriction embedded in a partial observability probit to point identify the latent parameter. We demonstrate the method by revisiting two large‐scale national programs in India: one where pension benefits are underreported and second where the program is mistargeted.

Suggested Citation

  • Akanksha Negi & Digvijay S. Negi, 2025. "Difference‐in‐Differences With a Misclassified Treatment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(4), pages 411-423, June.
    • Handle: RePEc:wly:japmet:v:40:y:2025:i:4:p:411-423
    DOI: 10.1002/jae.3116
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