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Author : Léopold Simar
Publisher :
Page : 34 pages
File Size : 10,7 MB
Release : 1991
Category :
ISBN :
Author : Subal C. Kumbhakar
Publisher : Cambridge University Press
Page : 375 pages
File Size : 39,5 MB
Release : 2015-01-26
Category : Business & Economics
ISBN : 1316194493
A Practitioner's Guide to Stochastic Frontier Analysis Using Stata provides practitioners in academia and industry with a step-by-step guide on how to conduct efficiency analysis using the stochastic frontier approach. The authors explain in detail how to estimate production, cost, and profit efficiency and introduce the basic theory of each model in an accessible way, using empirical examples that demonstrate the interpretation and application of models. This book also provides computer code, allowing users to apply the models in their own work, and incorporates the most recent stochastic frontier models developed in academic literature. Such recent developments include models of heteroscedasticity and exogenous determinants of inefficiency, scaling models, panel models with time-varying inefficiency, growth models, and panel models that separate firm effects and persistent and transient inefficiency. Immensely helpful to applied researchers, this book bridges the chasm between theory and practice, expanding the range of applications in which production frontier analysis may be implemented.
Author : Subal C. Kumbhakar
Publisher : Cambridge University Press
Page : 348 pages
File Size : 32,45 MB
Release : 2003-03-10
Category : Business & Economics
ISBN : 1107717302
Modern textbook presentations of production economics typically treat producers as successful optimizers. Conventional econometric practice has generally followed this paradigm, and least squares based regression techniques have been used to estimate production, cost, profit and other functions. In such a framework deviations from maximum output, from minimum cost and cost minimizing input demands, and from maximum profit and profit maximizing output supplies and input demands, are attributed exclusively to random statistical noise. However casual empiricism and the business press both make persuasive cases for the argument that, although producers may indeed attempt to optimize, they do not always succeed. This book develops econometric techniques for the estimation of production, cost and profit frontiers, and for the estimation of the technical and economic efficiency with which producers approach these frontiers. Since these frontiers envelop rather than intersect the data, and since the authors continue to maintain the traditional econometric belief in the presence of external forces contributing to random statistical noise, the work is titled Stochastic Frontier Analysis.
Author : Subal Kumbhakar
Publisher : Now Publishers
Page : 140 pages
File Size : 33,76 MB
Release : 2014-12-19
Category : Business & Economics
ISBN : 9781601988966
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.
Author : Masoomeh Rashidghalam
Publisher :
Page : 32 pages
File Size : 15,85 MB
Release : 2016
Category :
ISBN :
The purpose of this paper is two-fold. First, it compares the performance of various panel data models in estimating technical efficiency in production. Second, it applies various stochastic frontier panel data models to estimate the technical efficiency of Iran's cotton production and to provide empirical evidence on the sources of technical inefficiency of cotton producing provinces. The results indicate that labor and seeds are determinants of cotton production and inorganic fertilizers result in reducing technical efficiency. The mean technical efficiency of the models is around 80 percent. Variations in the distribution of estimated efficiency amongst the different models is large.
Author : James LeSage
Publisher : CRC Press
Page : 362 pages
File Size : 16,57 MB
Release : 2009-01-20
Category : Business & Economics
ISBN : 1420064258
Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observat
Author : George Edward Battese
Publisher :
Page : 31 pages
File Size : 13,73 MB
Release : 1991
Category : Agricultural productivity
ISBN : 9780858349704
Author : Lászlo Mátyás
Publisher : Springer Science & Business Media
Page : 966 pages
File Size : 28,95 MB
Release : 2008-04-06
Category : Business & Economics
ISBN : 3540758925
This restructured, updated Third Edition provides a general overview of the econometrics of panel data, from both theoretical and applied viewpoints. Readers discover how econometric tools are used to study organizational and household behaviors as well as other macroeconomic phenomena such as economic growth. The book contains sixteen entirely new chapters; all other chapters have been revised to account for recent developments. With contributions from well known specialists in the field, this handbook is a standard reference for all those involved in the use of panel data in econometrics.
Author : Subal C. Kumbhakar
Publisher : Cambridge University Press
Page : 348 pages
File Size : 27,1 MB
Release : 2003-03-10
Category : Business & Economics
ISBN : 9780521666633
This book develops econometric techniques for the estimation of production, cost and profit frontiers, and for the estimation of the technical and economic efficiency with which producers approach these frontiers. Since these frontiers envelop rather than intersect the data, and since the authors continue to maintain the traditional econometric belief in the presence of external forces contributing to random statistical noise, the work is titled Stochastic Frontier Analysis. Hb ISBN (2000): 0-521-48184-8
Author : J. Paul Elhorst
Publisher : Springer Science & Business Media
Page : 125 pages
File Size : 14,69 MB
Release : 2013-09-30
Category : Business & Economics
ISBN : 3642403409
This book provides an overview of three generations of spatial econometric models: models based on cross-sectional data, static models based on spatial panels and dynamic spatial panel data models. The book not only presents different model specifications and their corresponding estimators, but also critically discusses the purposes for which these models can be used and how their results should be interpreted.