Document Type

Article

Publication Date

2018

Publication Title

American Journal of Political Science

ISSN

1540-5907

Volume

62

Issue

1

DOI

https://doi.org/10.1111/ajps.12318

Abstract

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.

Comments

The data, code, and any additional materials required to replicate all analyses in this article are available on the American Journal of Political Science Dataverse within the Harvard Dataverse Network, at: http://dx.doi.org/10.7910/DVN/MPQQC0.

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