Open Access Open Access  Restricted Access Subscription Access

Modeling Technical Efficiency using Truncated Skewed Laplace Distribution

Ngoc Nguyen, Arjun K. Gupta, Junyi Wang


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.


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

Full Text:


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.