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Recent Developments of the Autoregressive Distributed Lag Modelling Framework

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  • JIN SEO CHO

    (Yonsei Univ)

  • MATTHEW GREENWOOD-NIMMO

    (University of Melbourne)

  • YONGCHEOL SHIN

    (University of York)

Abstract

We review the literature on the Autoregressive Distributed Lag (ARDL) model, from its origins in the analysis of autocorrelated trend stationary processes to its subsequent applications in the analysis of cointegrated non-stationary time series. We then survey several recent extensions of the ARDL model, including asymmetric and nonlinear generalisations of the ARDL model, the quantile ARDL model, the pooled mean group dynamic panel data model and the spatio-temporal ARDL model.

Suggested Citation

  • Jin Seo Cho & Matthew Greenwood-Nimmo & Yongcheol Shin, 2021. "Recent Developments of the Autoregressive Distributed Lag Modelling Framework," Working papers 2021rwp-186, Yonsei University, Yonsei Economics Research Institute.
    • Handle: RePEc:yon:wpaper:2021rwp-186
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    More about this item

    Keywords

    Autoregressive Distributed Lag (ARDL) Model; Asymmetry; Nonlinearity and Threshold Effects; Quantile Regression; Panel Data; Spatial Analysis;
    All these keywords.

    JEL classification:

    • 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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