Testing preference formation in learning design contingent valuation (LDCV) using advanced information and repetitive treatments

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

Research output: Contribution to journalArticle

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. (JEL Q42, Q51)
Original languageEnglish
Pages (from-to)284-301
Number of pages18
JournalLand Economics
Volume94
Issue number2
DOIs
Publication statusPublished - 1 May 2018

Keywords

  • Contingent valuation
  • double bounded discrete choice
  • repetitive learning
  • advanced information learning
  • bid dependency
  • theories of preference formation

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