A Gamma-distributed stochastic frontier model

A Laplace Stochastic Frontier Model

We propose a Laplace stochastic frontier model as an alternative to the traditional model with normal errors. An interesting feature of the Laplace model is that the distribution of inefficiency conditional on the composed error is constant for positive values of the composed error, but varies for negative values. Therefore, it may be ideally suited for analyzing industries with many forms on o...

Stochastic Non-Parametric Frontier Analysis

In this paper we develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specically, our approach first allows for statistical noise, similar to Stochastic frontier analysis, and second, it allows modeling multiple-inputs-multiple-outputs technologies without imposing parametric assumptions on production relationship, similar to...

Simulated Likelihood Estimation of the Normal-Gamma Stochastic Frontier Function

The normal-gamma stochastic frontier model was proposed in Greene (1990) and Beckers and Hammond (1987) as an extension of the normalexponential proposed in the original derivations of the stochastic frontier by Aigner, Lovell, and Schmidt (1977). The normal-gamma model has the virtue of providing a richer and more flexible parameterization of the inefficiency distribution in the stochastic fro...

Distributed Generation Expansion Planning Considering Load Growth Uncertainty: A Novel Multi-Period Stochastic Model

Abstract – Distributed generation (DG) technology is known as an efficient solution for applying in distribution system planning (DSP) problems. Load growth uncertainty associated with distribution network is a significant source of uncertainty which highly affects optimal management of DGs. In order to handle this problem, a novel model is proposed in this paper based on DG solution, consideri...

Stochastic Frontier Models