@techreport{3ca603c953364ecb95216792bbff3ce7,
title = "On the Choice of Prior in Bayesian Model Averaging",
abstract = "Bayesian model averaging attempts to combine parameter estimation and model uncertainty in one coherent framework. The choice of prior is then critical. Within an explicit framework of ignorance we define a {\textquoteleft}suitable{\textquoteright} prior as one which leads to a continuous and suitable analog to the pretest estimator. The normal prior, used in standard Bayesian model averaging, is shown to be unsuitable. The Laplace (or lasso) prior is almost suitable. A suitable prior (the Subbotin prior) is proposed and its properties are investigated.",
keywords = "Model averaging, Bayesian analysis, Subbotin prior",
author = "J.H.J. Einmahl and J.R. Magnus and K. Kumar",
note = "Pagination: 29",
year = "2011",
language = "English",
volume = "2011-003",
series = "CentER Discussion Paper",
publisher = "Econometrics",
type = "WorkingPaper",
institution = "Econometrics",
}