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) model's specification can be corrected by adding an additional lag variable.

C) regression parameters will be incorrect.

Suppose you estimate the following model of residuals from an autoregressive model:

ε_t² = 0.25 + 0.6ε²_t-1 + μ_t, where ε = ε^{^}

If the residual at time t is 0.9, the forecasted variance for time t+1 is:

A) 0.736.

B) 0.790.

C) 0.850.

Suppose you estimate the following model of residuals from an autoregressive model:

ε_t² = 0.4 + 0.80ε_t-1² + μ_t, where ε = ε^{^}

If the residual at time t is 2.0, the forecasted variance for time t+1 is:

A) 3.2.

B) 2.0.

C) 3.6.