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Bayesian Model Averaging and Jointness Measures for gretl

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  • Blazejowski, Marcin
  • Kwiatkowski, Jacek

Abstract

This paper presents a software package that implements Bayesian model averaging for Gnu Regression, Econometrics and Time-series Library - gretl. The Bayesian Model Averaging (BMA) is a model-building strategy that takes account of model uncertainty into conclusions about estimated parameters. It is an efficient tool for discovering the most probable models and obtaining estimates of their posterior characteristics. In recent years we have observed an increasing number of software package devoted to BMA for different statistical and econometric software. In this paper, we propose BMA package for gretl, which is more and more popular free, open-source software for econometric analysis with easy-to-use GUI. We introduce BMA package for the linear regression models with jointness measures proposed by Ley and Steel (2007) and Doppelhofer and Weeks (2009).

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File URL: http://mpra.ub.uni-muenchen.de/44322/
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 44322.

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Date of creation: 10 Feb 2013
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Handle: RePEc:pra:mprapa:44322

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Keywords: Bayesian model averaging; jointness measures; gretl; Hansl;

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  1. Ley, Eduardo & Steel, Mark F.J., 2007. "Jointness in Bayesian variable selection with applications to growth regression," Journal of Macroeconomics, Elsevier, vol. 29(3), pages 476-493, September.
  2. Enrique Moral-Benito, 2010. "Model Averaging In Economics," Working Papers wp2010_1008, CEMFI.
  3. Shahram Amini & Christopher F. Parmeter, 2011. "Bayesian Model Averaging in R," Working Papers 2011-9, University of Miami, Department of Economics.
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