Overview, Objectives and General Contents
Discrete choice experiment is a stated-preference multi-attribute method used to systematically explore the trade-offs implied in qualitative choices. It has long and widely been employed in different applied fields such as transport, market research, health, environmental, rural, and food economics. The most common goals are the elicitation of individual preferences, individual willingness to pay, and choice forecasting. It can be applied for both public and private goods in developed and developing economies.
The main objective of the summer school is to deliver an organic treatment of theoretical and practical knowledge so as to enable participants to use them in their own applied research. Particular attention will be given to recent developments in the context of experimental designs for stated choice surveys. In particular, during the course participants will learn the empirical and theoretical foundations behind diverse experimental designs and random utility models. The practical component of the course will be based on recent software developments in estimation and experimental design. For estimation the course will be based on the well-known Nlogit5 software (an extension of the LimDep package), while the experimental design component will be taught using Ngene, which is a dedicated software recently developed by ChoiceMetrics. An overview of estimations of discrete choice models in R will also be covered. Specific applied research case studies will be used to illustrate and discuss the practical challenges researchers can face in the following research areas: transportation, environmental economics, and food choices. These will cover experiences in both developed and developing economies.
The course is open to academics, graduate students at different levels (MSc, MPhil, PG-diploma, and PhD),consultants, and other practitioners. Applications will be evaluated on a first-come first-serve basis. Presentation letters by academic supervisors endorsing the good standing of the candidate are welcome.