Testing for ARMA(1,1) Disturbances in the Linear Regression Model

Shahidur Rahman and Maxwell L. King

No 267386, Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: Serious alternatives to the AR(1) disturbance model in econometric applications of linear regression include MA(1) disturbances and the sum of independent white noise and AR(1) disturbance components. All three are special cases of ARMA(1,1) processes. This paper reports an empirical power comparison of tests for AR(1), MA(1) and ARMA(1,1) disturbances assuming ARMA(1,1) disturbances. Tests compared include the Durbin-Watson test, the locally best invariant test and various point optimal invariant (POI) tests. The results suggest that the power of the POI test is largely invariant to the choice of AR(1) parameter value at which power is maximized. This conclusion is strengthened by a theoretical result.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 25
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Persistent link: https://EconPapers.repec.org/RePEc:ags:monebs:267386

DOI: 10.22004/ag.econ.267386

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