Measurement of Productivity and Efficiency
Theory and Practice

Provides a comprehensive approach to productivity and efficiency analysis using economic and econometric theory.

Robin C. Sickles (Author), Valentin Zelenyuk (Author)

9781107036161, Cambridge University Press

Hardback, published 28 March 2019

626 pages, 53 b/w illus. 4 tables
23.5 x 15.7 x 3.9 cm, 1.02 kg

'The book thoroughly covers theory (index numbers, axiomatic production theory, DEA, FDH, stochastic models, inference) and practice of measurement of efficiency and productivity, including issues and sources of data with links, as well as links to software and models. A rigorous and truly indispensable guide - and all this and more in a mere 630 pages.' Rolf Fare and Shawna Grosskopf, Oregon State University

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® 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.

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.

Subject Areas: Optimization [PBU], Economic statistics [KCHS], Econometrics [KCH], Economics [KC]