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

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 developed by Tommasi and Zhang (2024, Journal of Econometrics 238: 105556) to bound the heterogeneous treatment effect when both noncompliance and misreporting 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

st0744 ivbounds heterogeneous treatment effect local average treatment effect LATE differential misclassification instrumental variable partial identification external information

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