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Combining Aggregate Demand and Discrete Choice Data with Application to Deer License Demand in Indiana

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Listed:
  • Carson Reeling
  • Dane Erickson
  • Yusun Kim
  • John G. Lee
  • Nicole J. O. Widmar

Abstract

Estimating demand for licenses for recreational activities is complicated because of a lack of meaningful variation across time, space, buyer types, and license attributes, including price. Prior work uses discrete choice experiments (DCEs) to overcome this challenge, but the resulting demand models are unlikely to replicate observed demands in the absence of ad hoc calibration procedures. We use a generalized method of moments–based approach that combines DCE data with observed market share data to estimate a choice model that yields demand functions that much more closely replicate observed data.

Suggested Citation

  • Carson Reeling & Dane Erickson & Yusun Kim & John G. Lee & Nicole J. O. Widmar, 2023. "Combining Aggregate Demand and Discrete Choice Data with Application to Deer License Demand in Indiana," Land Economics, University of Wisconsin Press, vol. 99(4), pages 477-489.
    • Handle: RePEc:uwp:landec:v:99:y:2023:i:4:p:477-489
    Note: DOI: https://doi.org/10.3368/le.99.4.120621-0144R1
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    More about this item

    JEL classification:

    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices
    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources

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