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Case-Based Reasoning and Dynamic Choice Modeling

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  • Priya Thomas
  • Todd Guilfoos

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.

Suggested Citation

  • Priya Thomas & Todd Guilfoos, 2023. "Case-Based Reasoning and Dynamic Choice Modeling," Land Economics, University of Wisconsin Press, vol. 99(1), pages 103-121.
    • Handle: RePEc:uwp:landec:v:99:y:2023:i:1:p:103-121
    Note: DOI: 10.3368/le.120820-0183R1
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    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • Q22 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Fishery

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