Testing the Assumptions Behind the Use of Importance Sampling

Nuffield College, Oxford, Economics Working Paper No. 2002-W17

Posted: 13 Aug 2002

See all articles by Siem Jan Koopman

Siem Jan Koopman

Vrije Universiteit Amsterdam - School of Business and Economics; Tinbergen Institute; Aarhus University - CREATES

Neil Shephard

Harvard University

Date Written: June 2002

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

Suggested Citation

Koopman, Siem Jan and Shephard, Neil, Testing the Assumptions Behind the Use of Importance Sampling (June 2002). Nuffield College, Oxford, Economics Working Paper No. 2002-W17. Available at SSRN: https://ssrn.com/abstract=316560

Siem Jan Koopman

Vrije Universiteit Amsterdam - School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081 HV
Netherlands
+31205986019 (Phone)

HOME PAGE: http://sjkoopman.net

Tinbergen Institute ( email )

Gustav Mahlerplein 117
1082 MS Amsterdam
Netherlands

HOME PAGE: http://personal.vu.nl/s.j.koopman

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Neil Shephard (Contact Author)

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

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