Thomas R. Gulledge / C.A. Knox Lovell (Hgg.)

International Applications of Productivity and Efficiency Analysis

A Special Issue of the Journal of Productivity Analysis
Herausgegeben:Gulledge, Thomas R.; Knox Lovell, C. A.

• Gebundenes Buch

Produktbeschreibung

International Applications of Productivity and Efficiency Analysis features a complete range of techniques utilized in frontier analysis, including extensions of existing techniques and the development of new techniques. Another feature is that most of the contributions use panel data in a variety of approaches. Finally, the range of empirical applications is at least as great as the range of techniques, and many of the applications are of considerable policy relevance.

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Produktdetails

• Verlag: Springer / Springer Netherlands
• Artikelnr. des Verlages: 978-0-7923-9240-8
• Reprinted from `JOURNAL OF PRODUCTIVITY ANALYSIS', 3: 1-2 (1992), 1992
• Seitenzahl: 208
• Erscheinungstermin: 30. Juni 1992
• Englisch
• Abmessung: 241mm x 160mm x 16mm
• Gewicht: 479g
• ISBN-13: 9780792392408
• ISBN-10: 079239240X
• Artikelnr.: 22225669

Inhaltsangabe

Editors' Introduction.- Efficiency and Ownership in Swedish Electricity Retail Distribution.- A Comparison of Parametric and Non-Parametric Efficiency Measures: The Case of Norwegian Ferries.- Allowing for Inefficiency in Parametric Estimation of Production Functions for Urban Transit Firms.- The Relative Efficiency of Public versus Private Municipal Bus Firms: An Application of Data Envelopment Analysis.- Productivity Changes in Swedish Pharmacies 1980-1989: A Non-Parametric Malmquist Approach.- Variation in Productive Efficiency in French Workers' Cooperatives.- Technical Inefficiency and Productive Decline in the U.S. Interstate Natural Gas Pipeline Industry Under the Natural Gas Policy Act.- Measuring Technical Efficiency in European Railways: A Panel Data Approach.- Frontier Production Functions, Technical Efficiency and Panel Data: With Application to Paddy Farmers in India.- Estimating Efficiencies from Frontier Models with Panel Data: A Comparison of Parametric, Non-Parametric and Semi-Parametric Methods with Bootsrapping.