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The summer school is designed to bridge the gap between theory and practice. It is organized into distinct parts: “Parametric, Static Approaches” (Week 1) and “Dynamic Approaches” (Week 2). Participants may enrol for either week 1 or 2, or both weeks. Although each week is independent, participants are encouraged to take both weeks.
Productivity growth entails changes in scale, efficiency gains and technological change. Innovations are needed to keep pushing the competitive envelope, and efficiency gains are needed to ensure that implemented technologies achieve their potential. Conventional economic approaches assume that all firms operate rationally and efficiently. This summer school, however, challenges this assumption and presents concepts, models and tools needed to analyse and quantify the levels of inefficiency and productivity at a point in time and their movement over time. Course activities
The course consists of theory and method sessions in the morning followed by an afternoon practicum session. The practicum 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.
The course is oriented toward PhD candidates, postdoctoral researchers and others with background in agricultural and applied economics.