# Consider a stationary model that combines the (operatorname{AR}(2)) model (y_{t}=delta+theta_{1} y_{t-1}+theta_{2} y_{t-2}+e_{t}) with an (mathrm{AR}(1)) error model

## Question:

Consider a stationary model that combines the \(\operatorname{AR}(2)\) model \(y_{t}=\delta+\theta_{1} y_{t-1}+\theta_{2} y_{t-2}+e_{t}\) with an \(\mathrm{AR}(1)\) error model \(e_{t}=ho e_{t-1}+v_{t}\) where \(E\left(v_{t} \mid I_{t-1}\right)=0\). Show that

Why will the assumption \(E\left(y_{t} \mid I_{t-1}\right)=\delta+\theta_{1} y_{t-1}+\theta_{2} y_{t-2}\) be violated if the errors are autocorrelated?

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**Related Book For**

## Principles Of Econometrics

**ISBN:** 9781118452271

5th Edition

**Authors:** R Carter Hill, William E Griffiths, Guay C Lim