Article

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.

Creator

• Philips, Andrew Q.

Date Issued

• 2018-01-01

Academic Affiliation

• Political Science

Journal Title

• American Journal of Political Science

Journal Issue/Number

• 1

Journal Volume

• 62

Subject

• error-correction
• cointegration
• dynamic modeling
• time series

Last Modified

• 2019-12-05

Resource Type

• Article

Rights Statement

• In Copyright

DOI

•  https://doi.org/10.1111/ajps.12318

ISSN

• 1540-5907

Language

• English [eng]

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