Testing the Assumptions Behind the Use of Importance Sampling
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.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986.
"Classical estimation methods for LDV models using simulation,"
Handbook of Econometrics,
in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441
- Hajivassiliou, Vassilis A & Ruud, Paul A., 1993. "Classical Estimation Methods for LDV Models Using Simulation," Department of Economics, Working Paper Series qt3cg196fr, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
- Vassilis A. Hajivassiliou and Paul A. Ruud., 1993. "Classical Estimation Methods for LDV Models Using Simulation," Economics Working Papers 93-219, University of California at Berkeley.
- Vassilis A. Hajivassiliou & Paul A. Ruud, 1993. "Classical Estimation Methods for LDV Models Using Simulation," Cowles Foundation Discussion Papers 1051, Cowles Foundation for Research in Economics, Yale University.
- V.A. Hajivassiliou & P. A. Ruud, 1993. "Classical Estimation Methods for LDV Models Using Simulation," Econometrics 9311002, EconWPA.
- Shephard, N. & Pitt, M.K., 1995.
"Likelihood Analysis of Non-Gaussian Parameter-Driven Models,"
108, Economics Group, Nuffield College, University of Oxford.
- Neil Shephard & Michael K Pitt, 1995. "Likelihood analysis of non-Gaussian parameter driven models," Economics Papers 15 & 108., Economics Group, Nuffield College, University of Oxford.
- Elerain, Ola & Chib, Siddhartha & Shephard, Neil, 2001.
"Likelihood Inference for Discretely Observed Nonlinear Diffusions,"
Econometric Society, vol. 69(4), pages 959-993, July.
- Elerian, O. & Chib, S. & Shephard, N., 1998. "Likelihood INference for Discretely Observed Non-linear Diffusions," Economics Papers 146, Economics Group, Nuffield College, University of Oxford.
- Ola Elerian & Siddhartha Chib & Neil Shephard, 2000. "Likelihood inference for discretely observed non-linear diffusions," OFRC Working Papers Series 2000mf02, Oxford Financial Research Centre.
- Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
- Andersen, Torben G., 2000. "Simulation-Based Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(01), pages 131-138, February.
- Gourieroux, Christian & Holly, Alberto & Monfort, Alain, 1981. "Kuhn-Tucker, likelihood ratio and Wald tests for nonlinear models with inequality constraints on the parameters," Journal of Econometrics, Elsevier, vol. 16(1), pages 166-166, May.
- Hull, John C & White, Alan D, 1987. " The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
- Ghysels, E. & Harvey, A. & Renault, E., 1996.
Cahiers de recherche
9613, Universite de Montreal, Departement de sciences economiques.
- GHYSELS, Eric & HARVEY, Andrew & RENAULT, Eric, 1995. "Stochastic Volatility," CORE Discussion Papers 1995069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
- Eric Ghysels & Andrew Harvey & Éric Renault, 1995. "Stochastic Volatility," CIRANO Working Papers 95s-49, CIRANO.
- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
- Danielsson, J & Richard, J-F, 1993. "Accelerated Gaussian Importance Sampler with Application to Dynamic Latent Variable Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 153-173, Suppl. De.
- Tripathi, Gautam, 2000. "Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(01), pages 139-142, February.
- Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
- Sandmann, Gleb & Koopman, Siem Jan, 1998. "Estimation of stochastic volatility models via Monte Carlo maximum likelihood," Journal of Econometrics, Elsevier, vol. 87(2), pages 271-301, September.
- Danielsson, Jon, 1994. "Stochastic volatility in asset prices estimation with simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 375-400.
When requesting a correction, please mention this item's handle: RePEc:nuf:econwp:0217. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Maxine Collett)
If references are entirely missing, you can add them using this form.