Using instrumental variable estimation to evaluate randomized experiments with imperfect compliance

Abstract

Among econometricians, instrumental variable (IV) estimation is a commonly used technique to estimate the causal effect of a particular variable on a specified outcome. However, among applied researchers in the social sciences, IV estimation may not be well understood. Although there are several IV estimation primers from different fields, most manuscripts are not readily accessible by researchers who may only be familiar with regression-based techniques. The manuscript provides a conceptual framework of why and how IV works in the context of evaluating treatment effects using randomized evaluations. I discuss the issue of imperfect treatment compliance, explain the logic of IV estimation, provide a sample dataset, and syntax for conducting IV analysis using R. A goal of the current manuscript is to demystify the use of IV estimation and make evaluation studies that use this technique more readily understood by researchers.

Publication
In Practical Assessment, Research, & Evaluation.
Date
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