Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5096309 | Journal of Econometrics | 2013 | 10 Pages |
Abstract
We introduce two estimators for estimating the Marginal Data Density (MDD) from the Gibbs output. Our methods are based on exploiting the analytical tractability condition, which requires that some parameter blocks can be analytically integrated out from the conditional posterior densities. This condition is satisfied by several widely used time series models. An empirical application to six-variate VAR models shows that the bias of a fully computational estimator is sufficiently large to distort the implied model rankings. One of the estimators is fast enough to make multiple computations of MDDs in densely parameterized models feasible.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Cristina Fuentes-Albero, Leonardo Melosi,