Testing Preference Formation in Learning Design Contingent Valuation Using Advance Information and Repetitive Treatments
提出新方法，在重复性离散选择实验中检验偏好是否理性，并应用于智利可再生能源溢价研究，帮助政策制定者识别行为理性的偏好。
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. <i></i>