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Stochastic Frontier Analysis

Autor Subal C. Kumbhakar, C. A. Knox Lovell
en Limba Engleză Paperback – 9 mar 2003

Remarcăm faptul că în economia producției tradiționale, producătorii sunt adesea portretizați ca optimizatori infailibili, orice abatere fiind atribuită erorilor statistice. Modelul propus de Subal C. Kumbhakar și C. A. Knox Lovell în Stochastic Frontier Analysis sparge această paradigmă, introducând un cadru econometric ce separă influența factorilor externi aleatorii de ineficiența tehnică și economică reală a agenților. Credem că forța acestei lucrări rezidă în capacitatea de a „anvelopa” datele mai degrabă decât de a le intersecta, oferind o metodologie riguroasă pentru estimarea frontierelor de producție, cost și profit.

Merită menționat că abordarea autorilor este una de referință pentru mediul academic și profesional, oferind instrumentele necesare pentru a analiza performanța în condiții de incertitudine. Cititorul care a aplicat ideile din Efficiency Analysis va găsi aici fundamentul teoretic extins și detalierea modelelor care permit o distincție clară între șocurile externe și managementul defectuos. De asemenea, lucrarea completează perspectivele din A Practitioner's Guide to Stochastic Frontier Analysis Using Stata, oferind rigoarea conceptuală necesară înainte de implementarea software-ului.

În contextul operei sale, această carte reprezintă pilonul teoretic al cercetărilor lui Kumbhakar, fiind strâns legată de Handbook of Production Economics. Dacă handbook-ul oferă o privire de ansamblu asupra întregului domeniu neoclasic, Stochastic Frontier Analysis se concentrează strict pe rafinarea metodelor de măsurare a eficienței. Structura este una academică, susținută de 38 de diagrame care clarifică tranziția de la regresia prin cele mai mici pătrate la modelele de frontieră stocastică.

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Livrare economică 26 mai-09 iunie


Specificații

ISBN-13: 9780521666633
ISBN-10: 0521666635
Pagini: 344
Ilustrații: 38 line diagrams
Dimensiuni: 156 x 234 x 18 mm
Greutate: 0.46 kg
Ediția:Revised
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States

De ce să citești această carte

Această carte este esențială pentru economiștii și cercetătorii care doresc să depășească modelele simpliste de optimizare. Cititorul câștigă o înțelegere profundă a modului în care pot fi măsurate pierderile de eficiență într-o organizație, separându-le de fluctuațiile pieței. Este un instrument indispensabil pentru oricine analizează productivitatea și performanța economică la nivel avansat, oferind rigoare matematică într-un limbaj academic precis.


Despre autor

Subal C. Kumbhakar este profesor emerit de cercetare la State University of New York, Binghamton, fiind considerat unul dintre cei mai importanți specialiști mondiali în analiza productivității și eficienței. Expertiza sa se concentrează pe dezvoltarea modelelor de frontieră stocastică (SF) aplicate atât pe date secvențiale, cât și pe date de tip panel. Contribuțiile sale includ modelarea ecuațiilor simultane și editarea unor publicații de prestigiu precum Journal of Econometrics și Empirical Economics. Lucrările sale sunt fundamentale pentru econometria modernă, definind standardele de bune practici în evaluarea performanței economice.


Cuprins

1. Introduction; 2. Analytical foundations; 3. The estimation of technical efficiency; 4. The estimation and decomposition of cost efficiency; 5. The estimation and decomposition of profit efficiency; 6. The shadow price approach to the estimation and decomposition of economic efficiency; 7. Incorporating exogenous influences on efficiency; 8. The estimation of efficiency change and productivity change.

Recenzii

'Stochastic Frontier Analysis is an excellent, up-to-date and complete summary of both the theory and techniques used in frontier production, cost and profit analysis. The authors are two of the leading researchers in the field. Students and practitioners in this area will find this book to be the only reference source they need.' William H. Greene, Stern School of Business, New York University
'Every so often a book is written that pulls together a large subject matter in an accessible way, covering both theoretical and applied developments. This is such a book. The contribution of this volume is that this large but complex literature is presented in a manner accessible to the general applied economist. It is must reading for anyone who measures firm production, cost functions, or profit functions. Those measuring productivity change will gain new enlightenment on how to better approach this important measurement problem. Furthermore, the book could be used as a text or supplementary text in an advanced course in production, productivity change, or econometrics. It is well worth the investment and will make a valuable and useful addition to one's library.' James L. Searle, Jr, Journal of Economic Literature
'This book is well written, comprehensive in its breadth and depth of coverage, and authoritative in its scholarship. It is certainly going to be the standard reference on stochastic frontier models for the foreseeable future.' Peter Schmidt, The Economic Journal
'This is the best book that exists on the topic of stochastic-frontier analysis. It is clearly an excellent book that concisely reports the state of the art of this approach to efficiency analysis. This is a well-written reference book for researchers in this field and for research students considering using stochastic-frontier analysis. Libraries should carry a copy. As the first book devoted exclusively to this topic, the authors have set a very high standard.' Kevin J. Fox, Economica
From the hardback: 'Stochastic Frontier Analysis is a complete textbook on stochastic frontier models. It deals with stochastic frontier production, cost and profit functions. Models for cross-sectional and panel data are presented and discussed. The analysis of technical change and inefficiency change with panel data is also discussed in detail. The authors are highly qualified to produce such a comprehensive book on stochastic frontiers. Lovell was one of the authors of the seminal paper on the stochastic frontier production function model. He has been undertaking research on many aspects of parametric and non-parametric frontier modelling and efficiency measurement for over twenty-five years. He is a 'pioneer' in this important research area. Kumbhakar has written outstanding papers on stochastic frontier models, both of a theoretical and applied nature, over the last 12 or more years. It will surely be a helpful and widely-cited book for researchers in the field.' George E. Battese, University of New England, Australia
'It is fascinating to see what has been accomplished in the field of stochastic frontier analysis since its beginning in 1977. The authors provide a luvidly written review of all the developments that have taken place in the past quarter of a century. Although hardly any publication has escaped their attention, Kumbhakar and Lovell succeed in keeping the reader focused on the grand lines of research. Well-rooted in recent history, this book will stimulate further research into measurement and explanation of efficiency and productivity (change). I expect this book to be at hand for a long time.' Bert M. Balk, Statistics Netherlands

Descriere

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.