IDEAS home Printed from https://ideas.repec.org/p/yon/wpaper/2019rwp-154.html
   My bibliography  Save this paper

Two-Step Estimation of the Nonlinear Autoregressive Distributed Lag Model

Author

Listed:
  • Jin Seo Cho

    (Yonsei Univ)

  • Matthew Greenwood-Nimmo

    (Univ of Melbourne)

  • Yongcheol Shin

    (Univ of York)

Abstract

We consider estimation of and inference on the nonlinear autoregressive distributed lag (NARDL) model, which is a single-equation error correction model that allows for asymmetry with respect to positive and negative changes in the explanatory variable(s). We show that the NARDL model exhibits an asymptotic singularity issue that frustrates efforts to derive the asymptotic properties of the single-step estimator. Consequently, we propose a two-step estimation framework, in which the parameters of the long-run relationship are estimated first using the fully-modified least squares estimator before the dynamic parameters are estimated by OLS in the second step. We show that our two-step estimators are consistent for the parameters of the NARDL model and we derive their limit distributions. We also develop Wald test statistics for the hypotheses of short-run and long-run parameter asymmetry. We demonstrate the utility of our framework with an application to postwar dividend-smoothing in the U.S.

Suggested Citation

  • Jin Seo Cho & Matthew Greenwood-Nimmo & Yongcheol Shin, 2019. "Two-Step Estimation of the Nonlinear Autoregressive Distributed Lag Model," Working papers 2019rwp-154, Yonsei University, Yonsei Economics Research Institute.
    • Handle: RePEc:yon:wpaper:2019rwp-154
    as

    Download full text from publisher

    File URL: http://121.254.254.220/repec/yon/wpaper/2019rwp-154.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Núñez, Héctor M. & Otero, Jesús & Trujillo-Barrera, Andrés, 2023. "Wholesale price rigidities and exchange rate pass-through: Evidence from daily data of agricultural products," International Economics, Elsevier, vol. 176(C).
    2. Jin Seo Cho & Matthew Greenwood‐Nimmo & Yongcheol Shin, 2023. "Recent developments of the autoregressive distributed lag modelling framework," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 7-32, February.
    3. Kashif Islam & Ahmad Raza Bilal & Zeeshan Saeed & Samina Sardar & Muhammad Husnain Kamboh, 2023. "Impact of government integrity and corruption on sustainable stock market development: linear and nonlinear evidence from Pakistan," Economic Change and Restructuring, Springer, vol. 56(4), pages 2529-2556, August.

    More about this item

    Keywords

    Nonlinear Autoregressive Distributed Lag (NARDL) Model; Fully-Modified Least Squares Estimator; Two-Step Estimation; Wald Test Statistic; Dividend-Smoothing.;
    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
    • G35 - Financial Economics - - Corporate Finance and Governance - - - Payout Policy

    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:yon:wpaper:2019rwp-154. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: YERI (email available below). General contact details of provider: https://edirc.repec.org/data/eryonkr.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.