Handling Endogeneity in Stochastic Frontier Analysis

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.