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Model Selection in Equations with Many ‘Small’ Effects

Author

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  • Jennifer L. Castle
  • Jurgen A. Doornik
  • David F. Hendry

Abstract

General unrestricted models (GUMs) may include important individual determinants, many small relevant effects, and irrelevant variables. Automatic model selection procedures can handle perfect collinearity and more candidate variables than observations, allowing substantial dimension reduction from GUMs with salient regressors, lags, non-linear transformations, and multiple location shifts, together with all the principal components representing 'factor' structures, which can also capture small influences that selection may not retain individually. High dimensional GUMs and even the final model can implicitly include more variables than observations entering via 'factors'. We simulate selection in several special cases to illustrate.
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Suggested Citation

  • Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    • Handle: RePEc:bla:obuest:v:75:y:2013:i:1:p:6-22
    DOI: j.1468-0084.2012.00727.x
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    File URL: http://hdl.handle.net/10.1111/j.1468-0084.2012.00727.x
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    Citations

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    Cited by:

    1. Rahul Verma & Rajesh Mohnot, 2023. "Relative Impact of the U.S. Energy Market Sentiments on Stocks and ESG Index Returns: Evidence from GCC Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 290-300, March.
    2. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
    3. David F. Hendry & Felix Pretis, 2013. "Anthropogenic influences on atmospheric CO2," Chapters, in: Roger Fouquet (ed.), Handbook on Energy and Climate Change, chapter 12, pages 287-326, Edward Elgar Publishing.
    4. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
    5. Jurgen A. Doornik & David F. Hendry & Steve Cook, 2015. "Statistical model selection with “Big Data”," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1045216-104, December.
    6. Yuxuan Huang, 2016. "Forecasting the USD/CNY Exchange Rate under Different Policy Regimes," Working Papers 2016-001, The George Washington University, The Center for Economic Research.

    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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