Testing AR(1) against MA(1) Disturbances in the Linear Regression Model: An Alternative Procedure
AbstractThis paper is concerned with the problem of testing the hypothesis that the disturbances of a regression model are generated by a first-order autoregressive process against the alternative assumption that they follow a first-order moving average scheme. The test proposed has the advantages of requiring only ordinary least squares estimation and of being simple to implement. Some Monte Carlo results on the finite sample behavior of the test are provided. Copyright 1990 by The Review of Economic Studies Limited.
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Review of Economic Studies.
Volume (Year): 57 (1990)
Issue (Month): 1 (January)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0034-6527
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- Chib, S. & Osiewalski, J. & Steel, M.F.J., 1990.
"Regression models under competing covariance matrices: A Bayesian perspective,"
1990-63, Tilburg University, Center for Economic Research.
- Chib, B. & Osiewalski, J. & Steel, M., 1990. "Regression Models Under Competing Covariance Matrices: A Baysian Perspective," Papers 9063, Tilburg - Center for Economic Research.
- Silvapulle, Paramsothy & King, Maxwell L., 1993. "Nonnested testing for autocorrelation in the linear regression model," Journal of Econometrics, Elsevier, vol. 58(3), pages 295-314, August.
- Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
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