Bayesian Model Averaging in R

Shahram Amini and Christopher Parmeter
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Shahram Amini: Department of Economics, Virginia Polytechnic Institute and State University

No 2011-9, Working Papers from University of Miami, Department of Economics

Abstract: Bayesian model averaging has increasingly witnessed applications across an array of empirical contexts. However, the dearth of available statistical software which allows one to engage in a model averaging exercise is limited. It is common for consumers of these methods to develop their own code, which has obvious appeal. However, canned statistical software can ameliorate one's own analysis if they are not intimately familiar with the nuances of computer coding. Moreover, many researchers would prefer user ready software to mitigate the inevitable time costs that arise when hard coding an econometric estimator. To that end, this paper describes the relative merits and attractiveness of several competing packages in the statistical environment R to implement a Bayesian model averaging exercise.

Keywords: Model Averaging; Zellner's g Prior; BMS (search for similar items in EconPapers)
JEL-codes: C87 (search for similar items in EconPapers)
Pages: 35 pages
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

Forthcoming: Under Review

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