On the Use of Panel Data in Bayesian Stochastic Frontier Models

On the Use of Panel Data in Bayesian Stochastic Frontier Models PDF Author: Carmen Fernandez
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

Book Description
We consider a Bayesian analysis of the stochastic frontier model with composed error. Under a commonly used class of (partly) noninformative prior distributions, the existence of the posterior distribution and of posterior moments is examined. Viewing this model as a Normal linear regression model with regression parameters corresponding to both the frontier and the inefficiency terms, generates the insights used to derive results in a very wide framework. It is found that in pure cross-section models posterior inference is precluded under this "usual" class of priors. Existence of a well-defined posterior distribution crucially hinges upon the structure imposed on the inefficiency terms. Exploiting panel data naturally suggests the use of more structured models, where Bayesian inference can be conducted.

On the Use of Panel Data in Bayesian Stochastic Frontier Models

On the Use of Panel Data in Bayesian Stochastic Frontier Models PDF Author: Carmen Fernández
Publisher:
ISBN:
Category : Bayesian statistical decision theory
Languages : en
Pages : 42

Book Description


Bayesian Estimation of Panel Stochastic Frontier Models with an Application to the Cost Efficiency Analysis of Taiwan Banks

Bayesian Estimation of Panel Stochastic Frontier Models with an Application to the Cost Efficiency Analysis of Taiwan Banks PDF Author: 李睿耆
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description


Stochastic Frontier Analysis

Stochastic Frontier Analysis PDF Author: Subal C. Kumbhakar
Publisher: Cambridge University Press
ISBN: 1107717302
Category : Business & Economics
Languages : en
Pages : 348

Book Description
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.

Topics in Advanced Econometrics

Topics in Advanced Econometrics PDF Author: Herman J. Bierens
Publisher: Cambridge University Press
ISBN: 9780521565110
Category : Business & Economics
Languages : en
Pages : 274

Book Description
A rigorous treatment of a number of timely topics in advanced econometrics.

Application of Bayesian Methods to Structural Models and Stochastic Frontier Production Models

Application of Bayesian Methods to Structural Models and Stochastic Frontier Production Models PDF Author: Kwang-shin Choi
Publisher:
ISBN:
Category : Baseball teams
Languages : en
Pages : 84

Book Description
This dissertation applies the Bayesian approach as a method to improve the estimation efficiency of existing econometric tools. The first chapter suggests the Continuous Choice Bayesian (CCB) estimator which combines the Bayesian approach with the Continuous Choice (CC) estimator suggested by Imai and Keane (2004). Using simulation study, I provide two important findings. First, the CC estimator clearly has better finite sample properties compared to a frequently used Discrete Choice (DC) estimator. Second, the CCB estimator has better estimation efficiency when data size is relatively small and it still retains the advantage of the CC estimator over the DC estimator. The second chapter estimates baseball's managerial efficiency using a stochastic frontier function with the Bayesian approach. When I apply a stochastic frontier model to baseball panel data, the difficult part is that dataset often has a small number of periods, which result in large estimation variance. To overcome this problem, I apply the Bayesian approach to a stochastic frontier analysis. I compare the confidence interval of efficiencies from the Bayesian estimator with the classical frequentist confidence interval. Simulation results show that when I use the Bayesian approach, I achieve smaller estimation variance while I do not lose any reliability in a point estimation. Then, I apply the Bayesian stochastic frontier analysis to answer some interesting questions in baseball.

Panel Data Econometrics

Panel Data Econometrics PDF Author: Mike Tsionas
Publisher: Academic Press
ISBN: 0128144319
Category : Business & Economics
Languages : en
Pages : 432

Book Description
Panel Data Econometrics: Theory introduces econometric modelling. Written by experts from diverse disciplines, the volume uses longitudinal datasets to illuminate applications for a variety of fields, such as banking, financial markets, tourism and transportation, auctions, and experimental economics. Contributors emphasize techniques and applications, and they accompany their explanations with case studies, empirical exercises and supplementary code in R. They also address panel data analysis in the context of productivity and efficiency analysis, where some of the most interesting applications and advancements have recently been made. Provides a vast array of empirical applications useful to practitioners from different application environments Accompanied by extensive case studies and empirical exercises Includes empirical chapters accompanied by supplementary code in R, helping researchers replicate findings Represents an accessible resource for diverse industries, including health, transportation, tourism, economic growth, and banking, where researchers are not always econometrics experts

A Practitioner's Guide to Stochastic Frontier Analysis Using Stata

A Practitioner's Guide to Stochastic Frontier Analysis Using Stata PDF Author: Subal C. Kumbhakar
Publisher: Cambridge University Press
ISBN: 1316194493
Category : Business & Economics
Languages : en
Pages : 375

Book Description
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.

Efficiency Analysis

Efficiency Analysis PDF Author: Subal Kumbhakar
Publisher: Now Publishers
ISBN: 9781601988966
Category : Business & Economics
Languages : en
Pages : 140

Book Description
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.

Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling

Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling PDF Author: Ivan Jeliazkov
Publisher: Emerald Group Publishing
ISBN: 1838674217
Category : Business & Economics
Languages : en
Pages : 252

Book Description
Volume 40B of Advances in Econometrics examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression.