STOCHASTIC PRODUCTION FRONTIER: FRAMEWORK AND DEVELOPMENT

Production Possibility Frontier and Stochastic Programming

Data Envelopment Analysis (DEA) is the methodology for evaluating the relative productive efficiency of decision making units (DMUs) that produce multiple-outputs using multiple-inputs. DEA was proposed for the first time in 1957 by Farrell; nonetheless, the wide usage of this method begun with its generalization and the linear programming formulation which is due to Charnes et al. (1978) (for ...

Comparative Analysis of Stochastic Frontier Partially non-parametric and Stochastic Frontier Parametric Methods Case Study: Measuring Cost Efficiency in Wheat Production in Iran

Estimating Production Uncertainty in Stochastic Frontier Production Function Models

One of the main purposes of the frontier literature is to estimate inefficiency. Given this objective, it is unfortunate that the issue of estimating “firm-specific” inefficiency in cross sectional context has not received much attention. To estimate firm-specific (technical) inefficiency, the standard procedure is to use the mean of the inefficiency term conditional on the entire composed erro...

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...

Estimating Technological Change Using a Stochastic Frontier Production Function Framework: Evidence from U.S. Firm-Level Data

This paper presents a methodology for estimating an index of technological change using firm-level data in a stochastic frontier production function model that takes into account time-varying technical inefficiency. In contrast to the Solow divisia index approach, econometric estimation of the index with panel data allows the researcher to separate technical progress from the stochastic measure...