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Optimal Model Averaging Of Varying Coefficient Models

Author

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  • Cong Li
  • Qi Li
  • Jeffrey Racine
  • DAIQIANG ZHANG

Abstract

We consider the problem of model averaging over a set of semiparametric varying coefficient models where the varying coefficients can be functions of continuous and categorical variables. We propose a Mallows model averaging procedure that is capable of delivering model averaging estimators with solid finite-sample performance. Theoretical underpinnings are provided, finite-sample performance is assessed via Monte Carlo simulation, and an illustrative application is presented. The approach is very simple to implement in practice and R code is provided in an appendix.

Suggested Citation

  • Cong Li & Qi Li & Jeffrey Racine & DAIQIANG ZHANG, 2017. "Optimal Model Averaging Of Varying Coefficient Models," Department of Economics Working Papers 2017-01, McMaster University.
  • Handle: RePEc:mcm:deptwp:2017-01
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    File URL: http://socserv.mcmaster.ca/econ/rsrch/papers/archive/McMasterEconWP2017-01.pdf
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    References listed on IDEAS

    as
    1. Qingfeng Liu & Ryo Okui & Arihiro Yoshimura, 2016. "Generalized Least Squares Model Averaging," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1692-1752, December.
    2. Qingfeng Liu & Ryo Okui, 2013. "Heteroscedasticity‐robust C(p) model averaging," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 463-472, October.
    3. Andrews, Donald W. K., 1991. "Asymptotic optimality of generalized CL, cross-validation, and generalized cross-validation in regression with heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 359-377, February.
    4. Xinyu Zhang & Dalei Yu & Guohua Zou & Hua Liang, 2016. "Optimal Model Averaging Estimation for Generalized Linear Models and Generalized Linear Mixed-Effects Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1775-1790, October.
    5. Tomohiro Ando & Ker-Chau Li, 2014. "A Model-Averaging Approach for High-Dimensional Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 254-265, March.
    6. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
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    Citations

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    Cited by:

    1. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2017. "Econom\'etrie et Machine Learning," Papers 1708.06992, arXiv.org, revised Mar 2018.
    2. 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.
    3. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Économétrie & Machine Learning," Working Papers hal-01568851, HAL.
    4. Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019. "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(1), pages 35-60.

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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