IDEAS home Printed from https://ideas.repec.org/p/boc/lsug23/05.html
   My bibliography  Save this paper

Bayesian Model Averaging

Author

Listed:
  • Yulia Marchenko

    (StataCorp)

Abstract

Model uncertainty accompanies many data analyses. Stata's new bma suite that performs Bayesian model averaging (BMA) helps address this uncertainty in the context of linear regression. Which predictors are important given the observed data? Which models are more plausible? How do predictors relate to each other across different models? BMA can answer these and more questions. BMA uses the Bayes theorem to aggregate the results across multiple candidate models to account for model uncertainty during inference and prediction in a principled and universal way. In my presentation, I will describe the basics of BMA and demonstrate it with the bma suite. I will also show how BMA can become a useful tool for your regression analysis, Bayesian or not!

Suggested Citation

  • Yulia Marchenko, 2023. "Bayesian Model Averaging," UK Stata Conference 2023 05, Stata Users Group.
    • Handle: RePEc:boc:lsug23:05
    as

    Download full text from publisher

    File URL: http://repec.org/lsug2023/Stata_UK23_Marchenko.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    2. Yang Feng & Qingfeng Liu, 2020. "Nested Model Averaging on Solution Path for High-dimensional Linear Regression," Papers 2005.08057, arXiv.org.
    3. Dominika Ehrenbergerova & Josef Bajzik, 2020. "The Effect of Monetary Policy on House Prices - How Strong is the Transmission?," Working Papers 2020/14, Czech National Bank.
    4. Josef Bajzik, 2023. "Does Shareholder Activism Have a Long-Lasting Impact on Company Value? A Meta-Analysis," Working Papers 2023/10, Czech National Bank.
    5. Havranek, Tomas & Bajzík, Josef & Irsova, Zuzana & Novak, Jiri, 2023. "Does Shareholder Activism Create Value? A Meta-Analysis," CEPR Discussion Papers 18233, C.E.P.R. Discussion Papers.
    6. Ryan Greenaway-McGrevy & Kade Sorensen, 2021. "A spatial model averaging approach to measuring house prices," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-32, December.
    7. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    8. Yulia Marchenko, 2023. "Bayesian model averaging," 2023 Stata Conference 17, Stata Users Group.
    9. Zhang, Xinyu & Liu, Chu-An, 2023. "Model averaging prediction by K-fold cross-validation," Journal of Econometrics, Elsevier, vol. 235(1), pages 280-301.
    10. Taisuke Imai & Tom A Rutter & Colin F Camerer, 2021. "Meta-Analysis of Present-Bias Estimation using Convex Time Budgets," The Economic Journal, Royal Economic Society, vol. 131(636), pages 1788-1814.
    11. Bajzik, Josef, 2021. "Trading volume and stock returns: A meta-analysis," International Review of Financial Analysis, Elsevier, vol. 78(C).
    12. Nimonka Bayale & Brigitte Kanga Kouassi, 2022. "The Devil is in the Details: On the Robust Determinants of Development Aid in G5 Sahel Countries," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 64(4), pages 646-680, December.
    13. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    14. 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".
    15. Jean-Charles Bricongne & Leonor Coutinho & Alessandro Turrini & Stefan Zeugner, 2020. "Is Private Debt Excessive?," Open Economies Review, Springer, vol. 31(2), pages 471-512, April.
    16. Moral-Benito, Enrique & Roehn, Oliver, 2016. "The impact of financial regulation on current account balances," European Economic Review, Elsevier, vol. 81(C), pages 148-166.
    17. Piotr Dybka & Bartosz Olesiński & Marek Rozkrut & Andrzej Torój, 2023. "Measuring the model uncertainty of shadow economy estimates," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(4), pages 1069-1106, August.
    18. Anna Sokolova, 2023. "Marginal Propensity to Consume and Unemployment: a Meta-analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 813-846, December.
    19. 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.
    20. Nick Huntington‐Klein & Andreu Arenas & Emily Beam & Marco Bertoni & Jeffrey R. Bloem & Pralhad Burli & Naibin Chen & Paul Grieco & Godwin Ekpe & Todd Pugatch & Martin Saavedra & Yaniv Stopnitzky, 2021. "The influence of hidden researcher decisions in applied microeconomics," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 944-960, July.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:boc:lsug23:05. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F Baum (email available below). General contact details of provider: https://edirc.repec.org/data/stataea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.