SOME ADVANCES IN BAYESIAN ESTIMATION METHODS USING MONTE CARLO INTEGRATION

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.


Issue Date:
1987-02
Publication Type:
Working or Discussion Paper
DOI and Other Identifiers:
Record Identifier:
https://ageconsearch.umn.edu/record/272361
Language:
English
Total Pages:
51
Series Statement:
REPORT 8704/A




 Record created 2018-04-30, last modified 2020-10-28

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