An Improved Selection Test between Autoregressive and Moving Average Disturbances in Regression Models

Pierre Nguimkeu

Journal of Time Series Econometrics, 2016, vol. 8, issue 1, 41-54

Abstract: This paper proposes an improved likelihood-based method to test the hypothesis that the disturbances of a linear regression model are generated by a first-order autoregressive process against the alternative that they follow a first-order moving average scheme. Compared with existing tests which usually rely on the asymptotic properties of the estimators, the proposed method has remarkable accuracy, particularly in small samples. Simulations studies are provided to show the superior accuracy of the method compared to the traditional tests. An empirical example using Canada real interest rate illustrates the implementation of the proposed method in practice.

Keywords: autoregressive errors; moving average errors; likelihood analysis; p-value (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1515/jtse-2014-0036

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