A Practitioner’s Guide to Stochastic Frontier Analysis Using Stata

A Practitioner’s Guide to Stochastic Frontier Analysis Using Stata by Subal C. Kumbhakar, published by Cambridge University Press on January 26, 2015, is an illustrated edition comprising 374 pages. This book serves as a comprehensive resource for practitioners in both academia and industry, detailing the process of conducting efficiency analysis through the stochastic frontier approach. It covers the estimation of production, cost, and profit efficiency while presenting the fundamental theories behind each model in an accessible manner, supported by empirical examples.
Readers will find a thorough exploration of various stochastic frontier models, including those addressing heteroscedasticity and exogenous factors influencing inefficiency. The book also introduces scaling models, panel models with time-varying inefficiency, and growth models, among others. Additionally, it provides computer code to facilitate the application of these models in practical work. By bridging the gap between theory and practice, this guide expands the potential applications of production frontier analysis, making it a valuable tool for applied researchers in the fields of business, economics, and statistics.
Official synopsis Publisher
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.
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