This book provides a comprehensive approach to productivity and efficiency analysis for upper-level undergraduates, graduate students, and professionals. An accompanying website includes programming codes that can be used with widely available software like MATLAB (R) and R, and test data for many of the estimators in the book.
This book provides a comprehensive approach to productivity and efficiency analysis for upper-level undergraduates, graduate students, and professionals. An accompanying website includes programming codes that can be used with widely available software like MATLAB (R) and R, and test data for many of the estimators in the book.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
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.
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