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Bayesian Model Averaging and Jointness Measures for gretl

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  • Błażejowski, Marcin
  • Kwiatkowski, Jacek

Abstract

This paper presents a software package that implements Bayesian model averaging for gretl, the GNU regression, econometrics and time-series library. Bayesian model averaging is a model-building strategy that takes account of model uncertainty in 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 packages devoted to Bayesian model averaging for different statistical and econometric software. In this paper, we propose the BMA package for gretl, which is an increasingly popular free, open-source software for econometric analysis with an easy-to-use graphical user interface. We introduce the BMA package for linear regression models with jointness measures proposed by Ley and Steel (2007) and Doppelhofer and Weeks (2009).

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  • Błażejowski, Marcin & Kwiatkowski, Jacek, 2015. "Bayesian Model Averaging and Jointness Measures for gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i05).
    • Handle: RePEc:jss:jstsof:v:068:i05
    DOI: http://hdl.handle.net/10.18637/jss.v068.i05
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    1. 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.
    2. 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.
    3. 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.
    4. Gernot Doppelhofer & Melvyn Weeks, 2009. "Jointness of growth determinants," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 209-244, March.
    5. Doppelhofer, G. & Weeks, M., 2005. "Jointness of Growth Determinants," Cambridge Working Papers in Economics 0542, Faculty of Economics, University of Cambridge.
    6. 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.
    7. 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.
    8. Shahram Amini & Christopher F. Parmeter, 2011. "Bayesian Model Averaging in R," Working Papers 2011-9, University of Miami, Department of Economics.
    9. 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.
    10. 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.
    11. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
    12. 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.
    13. 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.
    14. 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).
    15. Yalta, A. Talha & Schreiber, Sven, 2012. "Random Number Generation in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(c01).
    16. 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.
    17. 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.
    18. Lucchetti, Riccardo, 2011. "State Space Methods in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i11).
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    Cited by:

    1. Krzysztof Beck, 2017. "Bayesian Model Averaging And Jointness Measures: Theoretical Framework And Application To The Gravity Model Of Trade," Statistics in Transition New Series, Polish Statistical Association, vol. 18(3), pages 393-412, September.
    2. Riccardo (Jack) Lucchetti & Luca Pedini, 2020. "ParMA: Parallelised Bayesian Model Averaging for Generalised Linear Models," Working Papers 2020:28, Department of Economics, University of Venice "Ca' Foscari".
    3. Magdalena Florek & Jakub Gazda, 2021. "Traditional Food Products—Between Place Marketing, Economic Importance and Sustainable Development," Sustainability, MDPI, vol. 13(3), pages 1-14, January.
    4. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    5. Beck Krzysztof, 2017. "Bayesian Model Averaging and Jointness Measures: Theoretical Framework and Application to the Gravity Model of Trade," Statistics in Transition New Series, Polish Statistical Association, vol. 18(3), pages 393-412, September.
    6. Marcin Błażejowski & Jacek Kwiatkowski & Jakub Gazda, 2019. "Sources of Economic Growth: A Global Perspective," Sustainability, MDPI, vol. 11(1), pages 1-14, January.
    7. Magdalena Osińska & Atif Maqbool Khan & Jacek Kwiatkowski, 2024. "Identifying Economic Factors of Renewable Energy Consumption—A Global Perspective," Energies, MDPI, vol. 17(15), pages 1-26, July.
    8. Błażejowski, Marcin & Gazda, Jakub & Kwiatkowski, Jacek, 2016. "Bayesian Model Averaging in the Studies on Economic Growth in the EU Regions – Application of the gretl BMA package," MPRA Paper 89366, University Library of Munich, Germany, revised Oct 2016.
    9. Krzysztof Beck & Michał Możdżeń, 2020. "Institutional Determinants of Budgetary Expenditures. A BMA-Based Re-Evaluation of Contemporary Theories for OECD Countries," Sustainability, MDPI, vol. 12(10), pages 1-31, May.

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    More about this item

    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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