Abstract
This papers considers an alternative estimation procedures for estimating stochastic frontier models with endogenous regressors when no external instruments are available. The approach we propose is based on copula function to directly model the correlation between the endogenous regressors and the composed errors. Estimation of model parameters is done using maximum likelihood. Monte Carlo simulations are used to assess and compare the finite sample performances of the proposed estimation procedures.
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