Learning the Shape of the Likelihood of Typical Econometric Models using Gibbs Sampling
AbstractThe shape of the likelihood of several recently developed econometric models is often non-elliptical. Learning this shape using Gibbs sampling is discussed in this paper. A systematic analysis using graphical and computational methods is presented. Examples of the models considered in this paper are nearly non-stationary and non-identified models, weak-instrument models, mixture models and random-coefficients panel-data models
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 82.
Date of creation: 11 Aug 2004
Date of revision:
Gibbs sampler; MCMC; non-stationarity; reduced rank models; label switching; random coefficients panel data models;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
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