This chapter reviews methods for eliciting risk, time, and social preferences. We first outline the major conceptual issues in preference elicitation, including how preferences are defined and formed, and the significance and potential challenges of eliciting them. Next, we present a ``toolkit'' of preference elicitation techniques, highlighting the strengths and limitations of prominent methods and providing an overview of important econometric techniques. The discussion covers both classic elicitation methods that have formed the foundation for insights into preferences, including binary choices and matching techniques, and more recent methods, such as multiple price lists and convex time budgets. We then consider two newer tools that offer promise for future research—dynamic optimal adaptive methods, such as DOSE, and experimentally-validated preference modules. We provide a step-by-step guide to best practices when choosing an elicitation method and implementing preference elicitations in various research contexts. This includes strategies for managing common concerns, including how best to deal with measurement error, whether incentivized measures are needed, the potential for framing effects, and other issues. The chapter concludes by identifying future directions for methodological research and possible applications of preference measures.
Fisher, G., Chapman, J. (2025). Preference elicitation: common methods and potential pitfalls. Amsterdam : North-Holland, Elesevier.
Preference elicitation: common methods and potential pitfalls
Jonathan Chapman
2025
Abstract
This chapter reviews methods for eliciting risk, time, and social preferences. We first outline the major conceptual issues in preference elicitation, including how preferences are defined and formed, and the significance and potential challenges of eliciting them. Next, we present a ``toolkit'' of preference elicitation techniques, highlighting the strengths and limitations of prominent methods and providing an overview of important econometric techniques. The discussion covers both classic elicitation methods that have formed the foundation for insights into preferences, including binary choices and matching techniques, and more recent methods, such as multiple price lists and convex time budgets. We then consider two newer tools that offer promise for future research—dynamic optimal adaptive methods, such as DOSE, and experimentally-validated preference modules. We provide a step-by-step guide to best practices when choosing an elicitation method and implementing preference elicitations in various research contexts. This includes strategies for managing common concerns, including how best to deal with measurement error, whether incentivized measures are needed, the potential for framing effects, and other issues. The chapter concludes by identifying future directions for methodological research and possible applications of preference measures.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


