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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).

Suggested Citation

  • Blazejowski, Marcin & Kwiatkowski, Jacek, 2013. "Bayesian Model Averaging and Jointness Measures for gretl," MPRA Paper 44322, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:44322
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    References listed on IDEAS

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    1. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
    2. Giuseppe De Luca & Jan R. Magnus, 2011. "Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues," Stata Journal, StataCorp LP, vol. 11(4), pages 518-544, December.
    3. Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001. "Model uncertainty in cross-country growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
    4. 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.
    5. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
    6. Giovanni Baiocchi & Walter Distaso, 2003. "GRETL: Econometric software for the GNU generation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 105-110.
    7. Alex Lenkoski & Theo S. Eicher & Adrian E. Raftery, 2014. "Two-Stage Bayesian Model Averaging in Endogenous Variable Models," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 122-151, June.
    8. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
    9. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher, 2014. "The Determinants of Economic Growth in European Regions," Regional Studies, Taylor & Francis Journals, vol. 48(1), pages 44-67, January.
    10. Lee C. Adkins, 2011. "Using gretl for Monte Carlo experiments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 880-885, August.
    11. Zeugner, Stefan & Feldkircher, Martin, 2015. "Bayesian Model Averaging Employing Fixed and Flexible Priors: The BMS Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i04).
    12. Gernot Doppelhofer & Melvyn Weeks, 2009. "Jointness of growth determinants," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 209-244, March.
    13. Yalta, A. Talha & Schreiber, Sven, 2012. "Random Number Generation in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(c01).
    14. Shahram Amini & Christopher F. Parmeter, 2011. "Bayesian Model Averaging in R," Working Papers 2011-9, University of Miami, Department of Economics.
    15. Baran, Sándor, 2014. "Probabilistic wind speed forecasting using Bayesian model averaging with truncated normal components," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 227-238.
    16. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Equity Premia using Bayesian Dynamic Model Averaging," CQE Working Papers 2914, Center for Quantitative Economics (CQE), University of Muenster.
    17. Lucchetti, Riccardo, 2011. "State Space Methods in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i11).
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    More about this item

    Keywords

    Bayesian model averaging; jointness measures; gretl; Hansl;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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