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ardl: Estimating autoregressive distributed lag and equilibrium correction models

Author

Listed:
  • Sebastian Kripfganz

    (University of Exeter Business School)

  • Daniel C. Schneider

    (Max Planck Institute for Demographic Research)

Abstract

We present a command, ardl, for the estimation of autoregressive distributed lag (ARDL) models in a time-series context. The ardl command can be used to fit an ARDL model with the optimal number of autoregressive and distributed lags based on the Akaike or Bayesian (Schwarz) information criterion. 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 (cointe- grating) relationship. The popular bounds-testing procedure for the existence of a long-run levels relationship is implemented as a postestimation feature. Compre- hensive critical values and approximate p-values obtained from response-surface regressions facilitate statistical inference.

Suggested Citation

  • Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    • Handle: RePEc:tsj:stataj:v:23:y:2023:i:4:p:983-1019
    DOI: 10.1177/1536867X231212434
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Peter C. B. Phillips & Bruce E. Hansen, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(1), pages 99-125.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
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