Paper #1357

Title:

Estimating Bayesian decision problems with heterogeneous priors

Authors:

Stephen Eliot Hansen and Michael McMahon

Date:

March 2013

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.

Keywords:

Bayesian decision making; expertise; preferences; estimation.

JEL codes:

D72, D81, C13

Area of Research:

Business Economics and Industrial Organization

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