HEC Research Papers Series,
HEC Paris

Abstract: This paper proposes an indirect inference (Gourieroux, Monfort and Renault, 1993; Smith, 1993) estimation method for a large class of dynamic equilibrium models. The authors' approach is based on the observation that the econometric structure of these systems naturally generates auxiliary equilibria that can serve as building blocks for estimation. They use this insight to develop an accurate estimator for the long-run risk model of Bansal and Yaron (2004). The authors demonstrate the accuracy of our method by Monte Carlo simulation and estimate the long-run risk model on U.S. data. They also illustrate the good performance of the methodology on an asset pricing model with investor learning.

Keywords: Hidden Markov model; long-run risk; learning; value at risk; indirect inference; particle filters

JEL-codes: C01; C13; C15; C53; C58

58 pages, November 10, 2013

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