Using Instrumental Variable Estimation to Evaluate Randomized Experiments with Imperfect Compliance
DOI
https://doi.org/10.7275/k0p6-yj16
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. Accessed 3,266 times on https://pareonline.net from February 24, 2018 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Huang, Francis L.
(2019)
"Using Instrumental Variable Estimation to Evaluate Randomized Experiments with Imperfect Compliance,"
Practical Assessment, Research, and Evaluation: Vol. 23, Article 2.
DOI: https://doi.org/10.7275/k0p6-yj16
Available at:
https://scholarworks.umass.edu/pare/vol23/iss1/2