Learning the Shape of the Likelihood of Typical Econometric Models using Gibbs Sampling
The 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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