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Testing Preference Formation in Learning Design Contingent Valuation Using Advance Information and Repetitive Treatments

Author

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  • Claudia Aravena
  • W. George Hutchinson
  • Fredrik Carlsson
  • David I. Matthews

Abstract

Policymakers have largely replaced single-bounded discrete choice valuation by the more statistically efficient repetitive method: double-bounded discrete choice and discrete choice experiments. Repetitive valuation permits classification into rational and irrational preferences: (1) a priori well formed; (2) consistent nonarbitrary values “discovered” through repetition and experience;, (3) consistent but arbitrary values as “shaped” by preceding bid level, and (4) inconsistent and arbitrary values. Policy valuations should demonstrate behaviorally rational preferences. We outline novel methods for testing this in double-bounded discrete choice experiments applied to renewable energy premiums in Chile.

Suggested Citation

  • Claudia Aravena & W. George Hutchinson & Fredrik Carlsson & David I. Matthews, 2018. "Testing Preference Formation in Learning Design Contingent Valuation Using Advance Information and Repetitive Treatments," Land Economics, University of Wisconsin Press, vol. 94(2), pages 284-301.
    • Handle: RePEc:uwp:landec:v:94:y:2018:i:2:p:284-301
    Note: DOI: 10.3368/le.94.2.284
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    File URL: http://le.uwpress.org/cgi/reprint/94/2/284
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    Cited by:

    1. Aravena, C. & Denny, E., 2021. "The impact of learning and short-term experience on preferences for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).

    More about this item

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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