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Modeling Stochastic Production Frontier with Panel Data

Arjun K. Gupta, Ngoc Nguyen


The stochastic frontier analysis has been widely used to estimate the technical efficiency of firms. The basic idea lies in the introduction of a composed error term consisting of a noise V and an inefficiency term U. From there, the technical efficiency of each firm is estimated by utilizing distributional assumptions on the two error components. In the literature, the Normal-Half Normal model has been widely used in the context of panel data. In this study, we will consider other models which are more realistic than the Normal model in accounting for heavy tail data. The model is considered for both balanced and unbalanced panel data.
We apply the models to the WHO health data set for illustration.


Technical Efficiency, Stochastic Frontier Annalysis, Estimation, Fat-tailed Models, Maximum Likelihood Method, Panel Data

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