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Modeling Technical Efficiency using Truncated Skewed Laplace Distribution

Ngoc Nguyen, Arjun K. Gupta, Junyi Wang

Abstract


The stochastic frontier analysis has been widely used to estimate 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, technical efficiency of each firm is estimated by utilizing distributional assumptions on the two error components. In the literature, V is usually assumed to be normally distributed and the distribution of U can be exponential, truncated normal or Gamma. In this paper, we consider Truncated Skewed Laplace (TSL) distribution for technical inefficiency term U. This model is a generalized model for the exponential distribution, which allows better coverage range for skewness and kurtosis coefficients. An application of the model is conducted for a data set of 100 tourism companies in Vietnam. For the same data set, Normal-Exponential model is also applied for the comparison purpose.

Keywords


Technical Efficiency, Stochastic Frontier Analysis, Estimation, Maximum Likelihood Method, Cross-sectional Data.

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