Bayesian model averaging and forecasting

This paper focuses on the problem of variable selection in linear regression models. I briefy review the method of Bayesian model averaging, which has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. Some of the literature is discussed with particular emphasis on forecasting in economics. The role of the prior assumptions in these procedures is highlighted, and some recommendations for applied users are given