Board of Governors of the Federal Reserve System (US)
Finance and Economics Discussion Series
Measuring Ambiguity Aversion
We confront the generalized recursive smooth ambiguity aversion preferences of Klibanoff, Marinacci, and Mukerji (2005, 2009) with data using Bayesian methods introduced by Gallant and McCulloch (2009) to close two existing gaps in the literature. First, we use macroeconomic and financial data to estimate the size of ambiguity aversion as well as other structural parameters in a representative-agent consumption-based asset pricing model. Second, we use estimated structural parameters to investigate asset pricing implications of ambiguity aversion. Our structural parameter estimates are comparable with those from existing calibration studies, demonstrate sensitivity to sampling frequencies, and suggest ample scope for ambiguity aversion.
Cite this item
A. Ronald Gallant & Mohammad Jahan-Parvar & Hening Liu, Measuring Ambiguity Aversion, Board of Governors of the Federal Reserve System (US), Finance and Economics Discussion Series 2015-105, 23 Nov 2015.
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
Keywords: Ambiguity aversion; Bayesian estimation; Equity premium puzzle; Markov switching
This item with handle RePEc:fip:fedgfe:2015-105
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