Document Type
Article
Date of Original Version
2-2023
Department
Environmental and Natural Resource Economics
Abstract
Estimating discrete choices under uncertainty typically rely on assumptions of expected utility theory. We build on the dynamic choice modeling literature by using a nonlinear case-based reasoning approach based on cognitive processes and forms expectations by comparing the similarity between past problems and the current problem faced by a decision maker. This study provides a proof of concept of a behavioral model of location choice applied to recreational fishers’ location choice behavior in Connecticut. We find the case-based decision model does well in explaining the observed data and provides value in explaining the dynamic value of attributes.
Publication Title, e.g., Journal
Land Economics
Citation/Publisher Attribution
Thomas, P., & Guilfoos, T. (2023). Case-Based Reasoning and Dynamic Choice Modeling. Land Economics, 98(4), 120820-0183R1. https://doi.org/10.3368/le.120820-0183R1
Available at: https://doi.org/10.3368/le.120820-0183R1
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