Robin C. Sickles

Measurement of Productivity and Efficiency (eBook, PDF)

Theory and Practice

• Format: PDF

Produktbeschreibung

Methods and perspectives to model and measure productivity and efficiency have made a number of important advances in the last decade. Using the standard and innovative formulations of the theory and practice of efficiency and productivity measurement, Robin C. Sickles and Valentin Zelenyuk provide a comprehensive approach to productivity and efficiency analysis, covering its theoretical underpinnings and its empirical implementation, paying particular attention to the implications of neoclassical economic theory. A distinct feature of the book is that it presents a wide array of theoretical and empirical methods utilized by researchers and practitioners who study productivity issues. An accompanying website includes methods, programming codes that can be used with widely available software like MATLAB(R) and R, and test data for many of the productivity and efficiency estimators discussed in the book. It will be valuable to upper-level undergraduates, graduate students, and professionals.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 28. März 2019
• Englisch
• ISBN-13: 9781108654166
• Artikelnr.: 56296031

Autorenporträt

Robin C. Sickles is the Reginald Henry Hargrove Professor of Economics and Professor of Statistics at Rice University, Houston. He served as Editor-in-Chief of the Journal of Productivity Analysis as well as an Associate Editor for a number of other economics and econometrics journals. He is currently an Associate Editor of the Journal of Econometrics.

Inhaltsangabe

Preface
Introduction
1. Production theory: primal approach
2. Production theory: dual approach
3. Efficiency measurement
4. Productivity indexes: part 1
5. Aggregation
6. Functional forms
7. Productivity indexes: part 2
8. Envelopment-type estimators
9. Statistical analysis for DEA and FDH: Part 1
10. Statistical analysis for DEA and FDH: part 2
11. Cross-sectional stochastic frontiers
12. SF models-first generation panel approaches
13. SF models-second generation approaches
14. Endogeneity
15. Dynamic models
16. Shape restrictions and model averaging
17. Measurement, KLEMS, and other data
Afterword.