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BACE: A gretl Package for Model Averaging in Limited Dependent Variable Models


  • Marcin Blazejowski

    (WSB University in Toruń)

  • Jacek Kwiatkowski

    (Nicolaus Copernicus University in Toru´n)


This paper presents a software package called BACE (BayesianAveraging of Classical Estimates) which offers model-building strategy for various limited dependent variable models, including logit and probit models, ordered logit and probit models, multinomial logistic regression, Poisson regression, Tobit model, and interval regression. BACE strategy is a model selection method that incorporates both classical estimation and Bayesian techniques. It solves the problem of computation speed and model uncertainty that arise when dealing with a large number of competing advanced statistical models. Our BACE package is both fast and capable of delivering consistent results. The package also provides implementation of the latest proposals of BIC variants, and the latest measures of jointness. We use gretl, a popular, free, and open-source software for econometric analysis that features an easy-to-use graphical user interface.

Suggested Citation

  • Marcin Blazejowski & Jacek Kwiatkowski, 2023. "BACE: A gretl Package for Model Averaging in Limited Dependent Variable Models," gretl working papers 9, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
  • Handle: RePEc:anc:wgretl:9

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    References listed on IDEAS

    1. Mark B. Stewart, 1983. "On Least Squares Estimation when the Dependent Variable is Grouped," Review of Economic Studies, Oxford University Press, vol. 50(4), pages 737-753.
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    3. 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.
    4. 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.
    5. 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).
    6. Ram Tripathi & Ramesh Gupta & John Gurland, 1994. "Estimation of parameters in the beta binomial model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(2), pages 317-331, June.
    7. Rainer Winkelmann, 2008. "Econometric Analysis of Count Data," Springer Books, Springer, edition 0, number 978-3-540-78389-3, January.
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    More about this item


    BMA; model selection; BIC; gretl; Hansl;
    All these keywords.

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