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Generalized Models for Estimation of Technical Efficiencies

Ngoc Nguyen, Arjun K. Gupta


In this paper, generalized models to estimate technical efficiencies are considerred. In many studies in the field, the two assumptions about the error terms are popular: (i) technical efficiency components and the noise component are assumed to be independent, and (ii) the noise components are independent among firms. These assumptions might not hold in some situations due to firms’ adaptivity to the input market and the dependence among firms in a common market or economical environment. In this paper, we propose two models used in case of fat-tailed errors, one considers the dependence between noise components, and the other considers the association between the noise component and the technical efficiency components. Then the models are applied to the data set of Vietnam tourism firms.


Technical Efficiency, Stochastic Frontier Analysis, Estimation, Fat-tailed Models, Maximum Likelihood Method, Cross-sectional Data

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