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Have Your Cake and Eat It Too? Cointegration and Dynamic Inference from Autoregressive Distributed Lag Models

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  • Andrew Q. Philips

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 of 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.

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  • Andrew Q. Philips, 2018. "Have Your Cake and Eat It Too? Cointegration and Dynamic Inference from Autoregressive Distributed Lag Models," American Journal of Political Science, John Wiley & Sons, vol. 62(1), pages 230-244, January.
    • Handle: RePEc:wly:amposc:v:62:y:2018:i:1:p:230-244
    DOI: 10.1111/ajps.12318
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    18. Rasool Dehghanzadeh Shahabad & Mehmet Balcilar, 2022. "Modelling the Dynamic Interaction between Economic Policy Uncertainty and Commodity Prices in India: The Dynamic Autoregressive Distributed Lag Approach," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
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    21. Alberto Di Iorio & Marco Fanari, 2020. "Break-even inflation rates: the Italian case," Questioni di Economia e Finanza (Occasional Papers) 578, Bank of Italy, Economic Research and International Relations Area.
    22. Olivier Jacques & Alain Noel, 2022. "Austerity Reduces Public Health Investment," CIRANO Working Papers 2022s-02, CIRANO.

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