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ardl: Estimating autoregressive distributed lag and equilibrium correction models

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  • Sebastian Kripfganz
  • Daniel C. Schneider

Abstract

We present a Stata package for the estimation of autoregressive distributed lag (ARDL) models in a time-series context. The ardl command can be used to estimate an ARDL model with the optimal number of autoregressive and distributed lags based on the Akaike or Schwarz/Bayesian information cri- terion. The regression results can be displayed in the ARDL levels form or in the error-correction representation of the model. The latter separates long-run and short-run effects and is available in two different parameterizations of the long-run (cointegrating) relationship. The popular bounds testing procedure for the existence of a long-run levels relationship is implemented as a postestimation feature. Comprehensive critical values and approximate p-values obtained from response-surface regressions facilitate statistical inference.

Suggested Citation

  • Sebastian Kripfganz & Daniel C. Schneider, 2022. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," TUPD Discussion Papers 18, Graduate School of Economics and Management, Tohoku University.
    • Handle: RePEc:toh:tupdaa:18
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    1. Cheung, Yin-Wong & Lai, Kon S, 1995. "Lag Order and Critical Values of a Modified Dickey-Fuller Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(3), pages 411-419, August.
    2. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    3. Cheung, Yin-Wong & Lai, Kon S, 1995. "Lag Order and Critical Values of the Augmented Dickey-Fuller Test," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 277-280, July.
    4. Uwe Hassler & Jürgen Wolters, 2006. "Autoregressive distributed lag models and cointegration," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 59-74, March.
    5. Sebastian Kripfganz & Daniel C. Schneider, 2021. "Response Surface Regressions for Critical Value Bounds and Approximate p‐values in Equilibrium Correction Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1456-1481, December.
    6. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    7. Sebastian Kripfganz & Daniel C. Schneider, 2020. "Response Surface Regressions for Critical Value Bounds and Approximate p‐values in Equilibrium Correction Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1456-1481, December.
    8. Paresh Kumar Narayan, 2005. "The saving and investment nexus for China: evidence from cointegration tests," Applied Economics, Taylor & Francis Journals, vol. 37(17), pages 1979-1990.
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