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Some advances in Bayesian estimations methods using Monte Carlo Integration

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  • VAN DIJK, Herman K.

Abstract

In this paper some Monte Carlo integration methods are discussed that can be used for the efficient computation of posterior moments and densities of parameters of econometric and, more generally, statistical models. The methods are based on the principle of importance sampling and are intended for the evaluation of multi-dimensional integrals where the integrand is unimodal and multivariate skew. That is, the integrand has different tail behavior in different directions. Illustrative results are presented on the dynamic behavior and the probability of explosion of a small scale macro-economic model. This application involves nine-dimensional numerical integration.
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Suggested Citation

  • VAN DIJK, Herman K., 1987. "Some advances in Bayesian estimations methods using Monte Carlo Integration," LIDAM Reprints CORE 783, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:783
    Note: In : Advances in Econometrics, 6, 215-261, 1987
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    2. Bauwens, L. & Dijk, H. K., 1989. "Bayesian Limited Information Analysis Revisited," Econometric Institute Archives 272386, Erasmus University Rotterdam.
    3. van Dijk, H.K., 2002. "On Bayesian structural inference in a simultaneous equation model," Econometric Institute Research Papers EI 2002-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Hop, J. P. & van Duk, H. K., 1990. "Two Algorithms For The Computation Of Posterior Moments And Densities Using Monte Carlo Integration," Econometric Institute Archives 272483, Erasmus University Rotterdam.

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