Robust tests for heteroskedasticity and autocorrelation in the multiple regression model: Working paper series--02-05 (original) (raw)

2002

Abstract

The standard Rao's (1948) score or Lagrange multiplier test for heteroskedasticity was originally developed assuming normality of the disturbance term [see Godfrey (1978b), and Bruesch and Pagan (1979)]. Therefore, the resulting test depends heavily on the normality assumption. Koenker (1981) suggests a studentized for which is robust to nonnormality. This approach seems to be limited because of the unavailability of a general procedure that transforms a test to a robust one. Following Bickel (1978), we use a different approach to take account of nonnormality. Our tests will be based on the score function which is defined as the negative derivitive of the log-density function with respect to the underlying random variable. To implement the test we use a nonparametric estimate of the score function. Our robust test for heteroskedasticity is obtained by running a regression of the product of the score function and ordinary least squares residuals on some exogenous variables which ...

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