Testing the Assumptions Behind the Use of Importance Sampling

Siem Jan Koopman () and Neil Shephard ()

No 2002-W17, Economics Papers from Economics Group, Nuffield College, University of Oxford

Abstract: Importance sampling is used in many aspects of modern econometrics to approximate unsolvable integrals. Its reliable use requires the sampler to possess a variance, for this guarantees a square root speed of convergence and asymptotic normality of the estimator of the integral. However, this assumption is seldom checked. In this paper we propose to use extreme value theory to empirically assess the appropriateness of this assumption. We illustrate this method in the context of a maximum simulated likelihood analysis of the stochastic volatility model.

Keywords: Extreme value theory; Importance sampling; Simulation; Stochastic Volatility. (search for similar items in EconPapers)
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Date: Written
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