Stata module to dynamically simulate autoregressive distributed lag (ARDL) models.
Stata module to dynamically simulate autoregressive distributed lag (ARDL) models.
You can download the most recent version of dynardl from the project site here. This program is part of a suite that also includes pssbounds (Jordan and Philips 2017), a Stata module to display the necessary critical values to conduct the Pesaran, Shin and Smith (2001) bounds test for cointegration.
Current version: 1.0.4. Note that a previous version of this program was called dynpss. dynardl provides a more flexible lag specification and adds additional plots.
dynardl is a program to produce dynamic simulations of autoregressive distributed lag models (ARDL) of the sort recommended by Pesaran, Shin, and Smith (2001). See Philips (2018) for a discussion of this approach, and Jordan and Philips (2017) for an in-depth discussion of this program.
dynardl is designed to dynamically simulate the effects of a counterfactual change in one weakly exogenous regressor at a point in time, using stochastic simulation techniques. Since the ARDL procedure can produce models that are complicated to interpret, dynardl is designed to ease the burden of substantive interpretations through the creation of predicted (or expected) values of the dependent variable (along with associated confidence intervals), which can be plotted to show how a change in one variable “flows” through the model over time. dynardl takes 1000 (or however many simulations a user desires) draws of the set of parameters from a multivariate normal distribution, using the estimated parameters and the variance-covariance matrix from the linear regression. All covariates are set to certain values (typically means), which are used to create predicted Y-hat values plus stochastic uncertainty.
If you use dynardl, please cite:
Jordan, Soren and Andrew Q. Philips. 2017 “Cointegration testing and dynamic simulations of autoregressive distributed lag models”. Working Paper.
and
Philips, Andrew Q. 2018. “Have your cake and eat it too? Cointegration and dynamic inference from autoregressive distributed lag models.” American Journal of Political Science: 62(1): 230-244.
Andrew Q. Philips, Department of Political Science, University of Colorado Boulder. andrew.philips [AT] colorado.edu. @andyphilips
Soren Jordan, Department of Political Science, Auburn University. sorenjordanpols [AT] gmail.com.
Pesaran, M Hashem, Yongcheol Shin and Richard J Smith. 2001. “Bounds testing approaches to the analysis of level relationships.” Journal of Applied Econometrics 16(3):289-326.
See the working paper for examples of dynardl in action.
Use dynardl in one of your papers? Let me know (andrew.philips [AT] colorado.edu) and I will add it to the list below: