Foundations and Trends® in Econometrics > Vol 7 > Issue 3–4

Efficiency Analysis: A Primer on Recent Advances

Christopher F. Parmeter, Department of Economics, University of Miami, USA, cparmeter@bus.miami.edu Subal C. Kumbhakar, Department of Economics, State University of New York, kkar@binghamton.edu
 
Suggested Citation
Christopher F. Parmeter and Subal C. Kumbhakar (2014), "Efficiency Analysis: A Primer on Recent Advances", Foundations and Trends® in Econometrics: Vol. 7: No. 3–4, pp 191-385. http://dx.doi.org/10.1561/0800000023

Published: 18 Dec 2014
© 2014 C. F. Parmeter and S. C. Kumbhakar
 
Subjects
Estimation frameworks,  Panel data,  Semiparametric and nonparametric estimation
 
Keywords
C10 Econometric and Statistical Methods and Methodology
Efficiency analysisStochastic frontier modelsMeasurement errorEfficiency estimationProductivity
 

Free Preview:

Article Help

Share

Download article
In this article:
1. Overview
2. The Benchmark Stochastic Production Frontier Model
3. Multiple Outputs in Stochastic Frontier Model
4. Stochastic Cost and Profit Frontier Models
5. Determinants of Inefficiency
6. Accounting for Heterogeneity in Stochastic Frontier Model
7. The Stochastic Frontier Model with Panel Data
8. Nonparametric Estimation in the Stochastic Frontier Model
9. The Environmental Production Function and Efficiency
10. Concluding Remarks
References

Abstract

This monograph reviews the econometric literature on the estimation of stochastic frontiers and technical efficiency. Special attention is devoted to current research.

DOI:10.1561/0800000023
ISBN: 978-1-60198-896-6
211 pp. $99.00
Buy book
 
ISBN: 978-1-60198-897-3
211 pp. $240.00
Buy E-book
Table of contents:
1. Overview
2. The Benchmark Stochastic Production Frontier Model
3. Multiple Outputs in Stochastic Frontier Model
4. Stochastic Cost and Profit Frontier Models
5. Determinants of Inefficiency
6. Accounting for Heterogeneity in Stochastic Frontier Model
7. The Stochastic Frontier Model with Panel Data
8. Nonparametric Estimation in the Stochastic Frontier Model
9. The Environmental Production Function and Efficiency
10. Concluding Remarks
References

Efficiency Analysis

Efficiency Analysis details the important econometric area of efficiency estimation, both past approaches as well as new methodology. There are two main camps in efficiency analysis: that which estimates maximal output and attributes all departures from this as inefficiency, known as Data Envelopment Analysis (DEA), and that which allows for both unobserved variation in output due to shocks and measurement error as well as inefficiency, known as Stochastic Frontier Analysis (SFA). This volume focuses exclusively on SFA.

The econometric study of efficiency analysis typically begins by constructing a convoluted error term that is composed on noise, shocks, measurement error, and a one-sided shock called inefficiency. Early in the development of these methods, attention focused on the proposal of distributional assumptions which yielded a likelihood function whereby the parameters of the distributional components of the convoluted error could be recovered. The field evolved to the study of individual specific efficiency scores and the extension of these methods to panel data. Recently, attention has focused on relaxing the stringent distributional assumptions that are commonly imposed, relaxing the functional form assumptions commonly placed on the underlying technology, or some combination of both. All told exciting and seminal breakthroughs have occurred in this literature, and reviews of these methods are needed to effectively detail the state of the art.

The generality of SFA is such that the study of efficiency has gone beyond simple application of frontier methods to study firms and appears across a diverse set of applied milieus. This review should appeal to those outside of the efficiency literature seeking to learn about new methods which might assist them in uncovering phenomena in their applied area of interest.

 
ECO-023