American Journal of Political Science
Although recent articles have stressed the importance of testing for unit-roots and cointegration in time series analysis, practitioners have been left without a straightforward procedure to implement this advice. I propose using the autoregressive distributed lag model and bounds cointegration test as an approach to dealing with some the most commonly encountered issues in time series analysis. Through Monte Carlo experiments I show that this procedure performs better than existing cointegration tests under a variety of situations. I illustrate how to implement this strategy with two step-by-step replication examples. To further aid users, I have designed software programs in order to test and dynamically model the results from this approach.
Philips, Andrew Q., "Have Your Cake and Eat it Too? Cointegration and Dynamic Inference from Autoregressive Distributed Lag Models" (2018). Political Science Faculty Contributions. 36.