Handling Endogeneity in Stochastic Frontier Analysis

23 Pages Posted: 18 May 2015 Last revised: 4 Oct 2016

See all articles by Mustafa U. Karakaplan

Mustafa U. Karakaplan

University of South Carolina, Darla Moore School of Business; Stanford University

Levent Kutlu

University of Texas Rio Grande Valley

Date Written: September 25, 2015

Abstract

We present a general maximum likelihood based framework to handle the endogeneity problem in the stochastic frontier models. We implement Monte Carlo experiments to analyze the performance of our estimator. Our findings show that our estimator outperforms standard estimators that ignore endogeneity.

Keywords: Battese-Coelli Estimator; Endogeneity; Efficiency

JEL Classification: C13

Suggested Citation

Karakaplan, Mustafa U. and Kutlu, Levent, Handling Endogeneity in Stochastic Frontier Analysis (September 25, 2015). Available at SSRN: https://ssrn.com/abstract=2607276 or http://dx.doi.org/10.2139/ssrn.2607276

Mustafa U. Karakaplan

University of South Carolina, Darla Moore School of Business ( email )

1014 Greene Street
Columbia, SC 29208
United States

Stanford University ( email )

Stanford, CA 94305
United States

Levent Kutlu (Contact Author)

University of Texas Rio Grande Valley ( email )

1201 West University Dr
Edinburg, TX TX 78539
United States

HOME PAGE: http://https://faculty.utrgv.edu/levent.kutlu/

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
621
Abstract Views
2,124
rank
62,418
PlumX Metrics