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Estimating Risk Preferences from Deductible Choice Author info | Abstract | Publisher info | Download info | Related research | Statistics Alma Cohen
Liran Einav
We use a large data set of deductible choices in auto insurance contracts to estimate the distribution of risk preferences in our sample. To do so, we develop a structural econometric model, which accounts for adverse selection by allowing for unobserved heterogeneity in both risk (probability of an accident) and risk aversion. Ex-post claim information separately identifies the marginal distribution of risk, while the joint distribution of risk and risk aversion is identified by the deductible choice. We find that individuals in our sample have on average an estimated absolute risk aversion which is higher than other estimates found in the literature. Using annual income as a measure of wealth, we find an average two-digit coefficient of relative risk aversion. We also find that women tend to be more risk averse than men, that proxies for income and wealth are positively related to absolute risk aversion, that unobserved heterogeneity in risk preferences is higher relative to that of risk, and that unobserved risk is positively correlated with unobserved risk aversion. Finally, we use our results for counterfactual exercises that assess the profitability of insurance contracts under various assumptions.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number
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Date of creation: Jul 2005Date of revision:
Handle: RePEc:nbr:nberwo:11461Note: IOContact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A. Phone: 617-868-3900 Email: Web page: http://www.nber.org More information through EDIRC
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Keywords: Find related papers by JEL classification: D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies
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