SOME ADVANCES IN BAYESIAN ESTIMATION METHODS USING MONTE CARLO INTEGRATION

Herman van Dijk

No 272361, Econometric Institute Archives from Erasmus University Rotterdam

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.

Keywords: Agricultural and Food Policy; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 51
Date: 1987-02
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Citations: View citations in EconPapers (3)

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Related works:
Working Paper: Some advances in Bayesian estimations methods using Monte Carlo Integration (1987)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:eureia:272361

DOI: 10.22004/ag.econ.272361

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