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The consistency of model selection for dynamic Semi-varying coefficient models with autocorrelated errors

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  • Lei Huang
  • Hui Jiang
  • Haitao Tian

Abstract

The consistency of model selection criterion BIC has been well and widely studied for many nonlinear regression models. However, few of them had considered models with lag variables as regressors and auto-correlated errors in time series settings, which is common in both linear and nonlinear time series modeling. This paper studies a dynamic semi-varying coefficient model with ARMA errors, using an approach based on spectrum analysis of time series. The consistency property of the proposed model selection criteria is established and an implementation procedure of model selection is proposed for practitioners. Simulation studies have also been conducted to numerically show the consistency property.

Suggested Citation

  • Lei Huang & Hui Jiang & Haitao Tian, 2019. "The consistency of model selection for dynamic Semi-varying coefficient models with autocorrelated errors," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(3), pages 549-558, February.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:3:p:549-558
    DOI: 10.1080/03610926.2017.1414265
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