Title and Abstract
ardl: Estimating autoregressive distributed lag and equilibrium correction 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.
Kripfganz, S., and D. C. Schneider (2018). ardl: Estimating autoregressive distributed lag and equilibrium correction models.
Proceedings of the 2018 London Stata Conference.
University of Exeter
Daniel C. Schneider
Max Planck Institute for Demographic Research