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Estimating Bayesian decision problems with heterogeneous priors

By Stephen Hansen and Michael McMahon

Abstract

In many areas of economics there is a growing interest in how expertise and preferences drive individual and group decision making under uncertainty. Increasingly, we wish to estimate such models to quantify which of these drive decision making. In this paper we propose a new channel through which we can empirically identify expertise and preference parameters by using variation in decisions over heterogeneous priors. Relative to existing estimation approaches, our “Prior-Based Identification” extends the possible environments which can be estimated, and also substantially improves the accuracy and precision of estimates in those environments which can be estimated using existing methods

Topics: HB Economic Theory
Publisher: Centre for Economic Performance, London School of Economics and Political Science
Year: 2013
OAI identifier: oai:eprints.lse.ac.uk:51547
Provided by: LSE Research Online

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