Sebastian Kripfganz

Lecturer (assistant professor) in Economics,
University of Exeter Business School, Department of Economics
 
© Sebastian Kripfganz
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Research
Stata Programs
Title and Abstract
ardl: Stata module to estimate autoregressive distributed lag models
We present a new 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 criterion. The regression results can be displayed in the ARDL levels form or in the equilibrium 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 bounds testing procedure for the existence of a (long-run) levels relationship suggested by Pesaran, Shin, and Smith (2001, Journal of Applied Econometrics 16: 289-326) is implemented as a postestimation feature.
Suggested Citation
Kripfganz, S. and D. C. Schneider (2016). ardl: Stata module to estimate autoregressive distributed lag models. Presented July 29, 2016, at the Stata Conference, Chicago.
Related Work
Kripfganz, S. and D. C. Schneider (2018). Response surface regressions for critical value bounds and approximate p-values in equilibrium correction models. Manuscript, University of Exeter and Max Planck Institute for Demographic Research.
Authors
Sebastian Kripfganz
University of Exeter
Daniel C. Schneider
Max Planck Institute for Demographic Research
Presentation
Presentation (July 29, 2016, Stata Conference, Chicago)
Stata Program
ardl

www.kripfganz.de