An easy-to-understand guide to modelling productivity and efficiency using modern statistical tools. Introduces the fundamentals of stochastic frontier analysis (SFA) and the latest concepts and methods related to the use of copulas in SFA. A useful reference for those interested in the newest robust methods of business analytics.
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"Artem Prokhorov has pulled together a comprehensive survey of results for copula methods for Stochastic Frontier models. Many of these are from his own published work. Analysts and practitioners will want to complete their examination with this guide to leading edge extensions and tools for the Stochastic Frontier methodology."
William H. Greene, New York University and University of South Florida; Past Editor in Chief, Journal of Productivity Analysis
"Modeling dependence in stochastic frontier models has long been underutilized and misunderstood. This text provides a cutting edge and comprehensive treatment of the subject from the leading expert in this area. Full of examples, intuition and code, this work will move both applied and theoretical researchers closer to the 'frontier'."
Christopher F. Parmeter, Associate Professor, University of Miami, United States
"This is the first, and so far only, book that brings together the approach of statistical copulas and the Stochastic Frontier models, and does so in rigorous way, while also being user-friendly for practitioners, due to the well-designed examples, exercises and programming codes it provides to the readers."
Valentin Zelenyuk, Professor, The University of Queensland, Australia
"This revolutionary book utilizes state-of-the-art copula approaches to precisely model dependency in stochastic frontier models. Through well-crafted chapters, practical examples, and program codes, it provides graduate students, analysts, and practitioners with comprehensive tools to master these advanced techniques. Highly recommend it!"
Kien C. Tran, Professor, University of Lethbridge and Research Affiliate, Center for Econometrics and Business Analytics (CEBA), St. Petersburg State University, Russia
William H. Greene, New York University and University of South Florida; Past Editor in Chief, Journal of Productivity Analysis
"Modeling dependence in stochastic frontier models has long been underutilized and misunderstood. This text provides a cutting edge and comprehensive treatment of the subject from the leading expert in this area. Full of examples, intuition and code, this work will move both applied and theoretical researchers closer to the 'frontier'."
Christopher F. Parmeter, Associate Professor, University of Miami, United States
"This is the first, and so far only, book that brings together the approach of statistical copulas and the Stochastic Frontier models, and does so in rigorous way, while also being user-friendly for practitioners, due to the well-designed examples, exercises and programming codes it provides to the readers."
Valentin Zelenyuk, Professor, The University of Queensland, Australia
"This revolutionary book utilizes state-of-the-art copula approaches to precisely model dependency in stochastic frontier models. Through well-crafted chapters, practical examples, and program codes, it provides graduate students, analysts, and practitioners with comprehensive tools to master these advanced techniques. Highly recommend it!"
Kien C. Tran, Professor, University of Lethbridge and Research Affiliate, Center for Econometrics and Business Analytics (CEBA), St. Petersburg State University, Russia