Title and Abstract
ardl: Estimating autoregressive distributed lag and equilibrium correction models
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 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 (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.
Kripfganz, S., and D. C. Schneider (2022). ardl: Estimating autoregressive distributed lag and equilibrium correction models.
Manuscript under review by the Stata Journal.
University of Exeter
Daniel C. Schneider
Max Planck Institute for Demographic Research