Difference‐in‐Differences With a Misclassified Treatment

Akanksha Negi and Digvijay S. Negi

Journal of Applied Econometrics, 2025, vol. 40, issue 4, 411-423

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.

Date: 2025
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https://doi.org/10.1002/jae.3116

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Persistent link: https://EconPapers.repec.org/RePEc:wly:japmet:v:40:y:2025:i:4:p:411-423

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