Bayesian evaluation of non-admissible conditioning [An article from: Journal of Econometrics]

This digital document is a journal article from Journal of Econometrics, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Virtually all econometric models are conditional models. Nevertheless many of such models lose information by involving non-admissible conditionings. In this article we analyse, from a Bayesian point of view, the problem of admissible conditioning. Next, we design a methodology to evaluate the loss of information when a non-admissible conditioning is used as an approximation of the exact posterior distribution. Considering the Fisher test as a case study we conclude that, in the usual situations of multinomial or of independent binomial samplings, conditioning on the two margins involves a loss of information which does not decrease when the sample size increases.