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

  • Lee, John H H
  • King, Maxwell L

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.

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Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 11 (1993)
Issue (Month): 1 (January)
Pages: 17-27

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Handle: RePEc:bes:jnlbes:v:11:y:1993:i:1:p:17-27
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