Siddhartha Chib (Olin School of Business, Washington University) Michael K Pitt (University of Warwick) Neil Shephard () (Nuffield College, University of Oxford, UK)
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This paper provides methods for carrying out likelihood based inference for diffusion driven models, for example discretely observed multivariate diffusions, continuous time stochastic volatility models and counting process models. The diffusions can potentially be non-stationary. Although our methods are sampling based, making use of Markov chain Monte Carlo methods to sample the posterior distribution of the relevant unknowns, our general strategies and details are different from previous work along these lines. The methods we develop are simple to implement and simulation efficient. Importantly, unlike previous methods, the performance of our technique is not worsened, in fact it improves, as the degree of latent augmentation is increased to reduce the bias of the Euler approximation. In addition, our method is not subject to a degeneracy that afflicts previous techniques when the degree of latent augmentation is increased. We also discuss issues of model choice, model checking and filtering. The techniques and ideas are applied to both simulated and real data.
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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number
2004-W20.
References listed on IDEAS 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.:
Gourieroux, C & Monfort, A & Renault, E, 1993.
"Indirect Inference,"
Journal of Applied Econometrics,
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Other versions:
Gourieroux, C. & Monfort, A. & Renault, E., 1992.
"Indirect Inference,"
Papers
92.279, Toulouse - GREMAQ.
Gourieroux, C. & Monfort, A & Renault, E., 1992.
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Working Papers
9215, Centre de Recherche en Economie et Statistique.
Ghysels, E. & Harvey, A. & Renault, E., 1996.
"Stochastic Volatility,"
Cahiers de recherche
9613, Universite de Montreal, Departement de sciences economiques.
[Downloadable!]
Other versions:
Ghysels, E. & Harvey, A. & Renault, E., 1996.
"Stochastic Volatility,"
Cahiers de recherche
9613, Centre interuniversitaire de recherche en économie quantitative, CIREQ.