Bounding program benefits when participation is misreported: Estimation and inference with Stata

Andy Lin (), Denni Tommasi and Lina Zhang ()
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Andy Lin: Institute for Digital Research and Education
Lina Zhang: University of Amsterdam and Tinbergen Institute

Stata Journal, 2024, vol. 24, issue 2, 185-212

Abstract: Instrumental-variables estimation is an approach commonly used to evaluate the effect of a program in case of noncompliance. However, when the binary treatment status is misreported, standard techniques are not sufficient to point identify and consistently estimate the effect of interest. We present a new command, ivbounds, that implements three partial identification strategies de- veloped by Tommasi and Zhang (2024, Journal of Econometrics 238: 105556) to bound the heterogeneous treatment effect when both noncompliance and misre- porting of treatment status are present. We illustrate the use of the command by reassessing the benefits of participating in the 401(k) pension plan on savings in the United States.

Keywords: ivbounds; heterogeneous treatment effect; local average treat- ment effect; LATE; differential misclassification; instrumental variable; partial identification; external information (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1177/1536867X241257347

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