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A Locally Most Mean Powerful Based Score Test for ARCH and GARCH Regression Disturbances

John H H Lee and Maxwell King

Journal of Business & Economic Statistics, 1993, vol. 11, issue 1, 17-27

Abstract: This paper considers testing for autoregressive conditional heteroskedasticity and generalized autoregressive conditional heteroskedasticity disturbances in the linear regression model. These testing problems are one-sided in nature; a fact ignored by the Lagrange multiplier test. A test that exploits this one-sided aspect is constructed based on the sum of the scores. The size and power properties of two versions of this test under normal and leptokurtic disturbances are investigated via a Monte Carlo experiment. The results indicate that both version s of the new test typically have superior power to two versions of the Lagrange multiplier test and possibly also more accurate asymptotic critical values.

Date: 1993
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