Parametric Recoverability of Preferences
AbstractWe propose a procedure to recover parametric preferences from choices made from convex budget sets. The objective of the method is to minimize the inconsistency between the revealed preference information contained in the choices and the ranking information contained in the recovered preferences. For a given parametric utility function the procedure calculates, for every choice, the minimal proportional adjustment to the budget such that the two rankings are aligned. The closest element in a parametric family is found by minimizing a metric that is based on these minimal adjustments. Additionally, we show that this method can be used to recover approximate preferences even for inconsistent decision makers. The goodness of ï¬t of such approximation can be decomposed into a familiar measure of inconsistency and a natural measure of misspeciï¬cation. This decomposition provides a reasonable way to test restrictions and to select among different parametric models. We apply this method to a data set constructed in a lab experiment on choice under risk. The recovered utility structure(within the same parametric family) exhibits, on average, higher ï¬rst-order risk aversion (non-expected utility) and lower second-order risk aversion (expected utility), thanthe standard method that is based on statistical distance.
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Bibliographic InfoPaper provided by Microeconomics.ca Website in its series Micro Theory Working Papers with number yoram_halevy-2012-20.
Length: 47 pages
Date of creation: 30 Jun 2012
Date of revision: 30 Jun 2012
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Revealed Preference; Recoverability of Preferences; GARP; non-expected utility; risk aversion;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-07-08 (All new papers)
- NEP-EXP-2012-07-08 (Experimental Economics)
- NEP-UPT-2012-07-08 (Utility Models & Prospect Theory)
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