Monday, March 17, 2014

MCMC for Econometrics Students - I

This is the first of a short sequence of posts that discuss some material that I use when teaching Bayesian methods in my graduate econometrics courses.

This material focuses on Markov Chain Monte Carlo (MCMC) methods - especially the use of the Gibbs sampler to obtain marginal posterior densities. This first post discusses some of the computational issues associated with Bayesian econometrics, and introduces the Gibbs sampler. The follow-up posts will illustrate this technique with some specific examples.

So, what's the computational issue here?