Which of the following is least likely a consequence of a model containing ARCH(1) errors? The:
 
A. variance of the errors can be predicted.
 
B. regression parameters will be incorrect.
 
C. model's specification can be corrected by adding an additional lag variable.
 
solution：C
 
The presence of autoregressive conditional heteroskedasticity (ARCH) indicates that the variance of the error terms is not constant. This is a violation of the regression assumptions upon which time series models are based. The addition of another lag variable to a model is not a means for correcting for ARCH (1) errors.

 
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