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Likelihood Based Inference for Diffusion Driven State Space Models

INFORMATION AND OPERATIONS MANAGEMENT DEPARTMENT, MARSHALL SCHOOL OF BUSINESS PRESENTSDr. Siddhartha ChibHarry C. Hartkop Professor of Econometrics and Statistics, Olin School of Business, Washington State University in St. LouisFriday, November 10, 2006Hoffman Hall 40410:30 am – 12:00 noonABSTRACT: In this paper we develop likelihood based inferential methods for a novel class of (potentially non-stationary) diffusion driven state space models. Examples of models in this class are continuous time stochastic volatility models and counting process models. 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 on related but simpler models. The proposed methods are easy to implement and simulation efficient. Importantly, unlike methods for related models, the performance of our method is not worsened, in fact it improves, as the degree of latent augmentation is increased to reduce the bias of the Euler approximation. We also consider the problems of model choice, model checking and filtering and apply the techniques and ideas to both simulated and real data.Keywords: Bayes estimation, Brownian bridge, Non-linear diffusion, Euler approximation, Markov chain Monte Carlo, Metropolis-Hastings algorithm, Missing data, Simulation, Stochastic differential equation.SPEAKER BIO: Professor Chib's research is in the area of Bayesian statistics and Markov chain Monte Carlo computational methods. He has published papers on a number of different topics including the analysis of binary and ordinal data, Markov mixture models, stochastic volatility, Metropolis-Hastings algorithms and model choice. He is a Fellow of the American Statistical Association.*Paper co-authored with Michael K. Pitt, Department of Economics, University of Warwick and Neil Shephard, Nuffield College, University of Oxford.

Location: H. Leslie Hoffman Hall Of Business Administration (HOH) - 404

Audiences: Everyone Is Invited

Contact: Georgia Lum