TUPD-2022-006
                                    
                                
                             
                        
                    
                    | TITLE | ardl: Estimating autoregressive distributed lag
and equilibrium correction models | 
| AUTHORS | Sebastian Kripfganz 
                                            Lecturer (assistant professor) in Economics, University of Exeter Business School, Exeter, United Kingdom
                                             Max Planck Institute for Demographic Research, Rostock, Germany | 
| P D F |   | 
| 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 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. | 
| KEYWORDS | Autoregressive distributed lag model, Error-correction model, Bounds test, Long-run relationship, Cointegration, Time-series data | 
| ISSUED | April 2022 | 
 
                        