The course consists of theory and method sessions in the morning followed by an afternoon practicum session. The computer lab will include applications of the theory, computer analyses with actual data sets, and interpretations in practice. Applications to various economic sectors will be considered such as agriculture, banking and finance, chain management, health, electrical power generation, and sports. Extensions of these models will be addressed that measure input-specific technical efficiency and characterize the dynamic linkages in decision making, and introduce hybrid nonparametric-parametric approaches.
Participants will learn the theories concerning efficiency and productivity measurement and will develop proficiency with software to facilitate the initiation of their own research in efficiency and productivity measurement. The course deals with both conceptual and methodological issues.
In particular, after successful completion (of either module) participants are expected to be able to:
- Understand sources of efficiency from the perspective of technical feasibility, allocating scarce resource among competing ends, and the firm scale of operations;
- Understand the input and output perspectives of technical and allocative efficiency;
- Characterize efficiency and productivity growth from a primal, dual and distance function perspective;
- Decompose productivity growth that explicitly accounts for the presence of inefficiency;
- Use DEA models to measure technical, allocative, and scale efficiency levels and productivity growth;
- Characterize definitions of variables of interest to be employed (goods and services; inputs, outputs, environmental, nonmarket goods/services);
- Assess the appropriate use of parametric and nonparametric approaches given the data and problem setting (understanding the advantages and disadvantages of both perspectives);
- Use these approaches to articulate the forces driving efficiency gains and productivity growth;
- Use these approaches for benchmarking, identifying best practice and role models to plan for performance enhancement/gains;
The Data Envelopment Analysis course will further cover:
- Delineation of variable and quasi-fixed factors and their treatment in efficiency and productivity;
- Use of econometric approaches to address efficiency and productivity change measurement over time.
The course is oriented toward PhD candidates, postdoctoral researchers and others with background in economics.
Assumed prior knowledge
Microeconomic theory at the graduate level such as the treatment in H. Varian, Microeconomic Analysis, W.W. Norton. Completion of a course in dynamic optimization is strongly recommended. Econometric theory and applications at the graduate level to include topics in Maximum Likelihood Estimation and System Estimation are required and some exposure to panel data econometrics is desirable.
- Kumbhakar, S. and C.A.K. Lovell, Stochastic Frontier Analysis, Cambridge University Press, 2000.
- Subal C. Kumbhakar, Christopher F. Parmeter and Valentin Zelenyuk, `Stochastic Frontier Analysis: Foundations and Advances I, Handbook of Production Economics, edited by R. Chambers, S. C. Kumbhakar and S. Ray, Springer, 2022.
- Subal C. Kumbhakar, Christopher F. Parmeter and Valentin Zelenyuk, `Stochastic Frontier Analysis: Foundations and Advances II,' Handbook of Production Economics}, edited by R. Chambers, S. C. Kumbhakar and S. Ray, Springer, 2022.
- Koop, G, and MFJ Steel. "Bayesian Analysis of Stochastic Frontier Models." A companion to Theoretical Econometrics 1 (2001): 520-73.
- Silva, E., S. Stefanou and A. Oude Lansink (2021). Dynamic Efficiency and Productivity Measurement. Oxford University Press, 28 Jan 2021, Oxford University Press. 248 p.
Participants should make sure they have the books of Kumbhakar et al. (2000) and Silva et al. (2021) before the course starts; the costs of these books are not included in participation fee. The two chapters from the handbooks of production economics (Kumbhakar et al. (2022)) and other accompanying materials will be distributed during the course
The course fee for each week is 650 euro for those registering for one week and 1100 euro for those registering for both weeks. The course fee does not include books. It includes additional training material, coffee / tea, lunches and an informal dinner.
A cancellation fee of 50% applies if participants cancel before 1 November 2023. A cancellation fee of 100% applies if participants cancel the course after 1 November 2023. The organisers have a right to cancel the course not later than 1 December 2023 and participants will be fully reimbursed in that case. The participants will be notified of any changes at their e-mail addresses.
Outline of the Course in Hours
Students can choose to participate in the course and receive 1.5 ECTS per week, or write a paper (one for each week) and receive 3 ECTS per week. 1 ECTS is equivalent to 28 hours of work load. For participation in the full 2-week programme, which entails 168 hours of preparation, attendance and two papers, 6 ECTS can be obtained.
Summer School Theory and Practice of Efficiency and Productivity MeasurementRegistration website for Summer School Theory and Practice of Efficiency and Productivity Measurement
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Summer School Theory and Practice of Efficiency and Productivity MeasurementSummer School Theory and Practice of Efficiency and Productivity Measurement0.00EUROnlineOnly2019-01-01T00:00:00Z
Universidade Federal do CearaUniversidade Federal do CearaAv. da Universidade, 2431 60020 Fortaleza Brazil