Quantile Treatment Effects with Endogeneity: A Monte Carlo Comparison of 3 Quantile IV Estimators

Authors

Alexander Poulsen, Brigham Young University
Brigham Frandsen, Brigham Young University

Keywords

quantile treatment effects, endogeneity, Monte Carlo, 3 quantile IV estimators

College

Family, Home, and Social Sciences

Department

Economics

Abstract

Quantile instrumental variables estimators are a relatively new development in the econometric literature. Modern quantile regression was introduced in Koenker and Basset (1978), and has been used in many important applications in which researchers are interested in learning about the effects of variables on the distribution of an outcome variable, rather than just mean effects. Examples of these applications include changes in U.S. wage structure (Buchinsky 1994), the effect of school quality on student performance (Eide and Showalter 1998), and the relationship between innovation and firm growth (Coad and Rao 2008).

Recommended Citation

Poulsen, Alexander and Frandsen, Brigham (2016) "Quantile Treatment Effects with Endogeneity: A Monte Carlo Comparison of 3 Quantile IV Estimators," Journal of Undergraduate Research: Vol. 2016: Iss. 1, Article 30.
Available at: https://scholarsarchive.byu.edu/jur/vol2016/iss1/30