Consider the simple linear regression model \(y_{t}=\beta_{0}+\beta_{1} x+\varepsilon_{t}\), where the error are generated by the second-order autoregressive process

\[
\varepsilon_{t}=ho_{1} \varepsilon_{t-1}+ho_{2} \varepsilon_{t-2}+a_{t}
\]

Discuss how the Cochrane-Orcutt iterative procedure could be used in this situation. What transformations would be used on the variable \(y_{t}\) and \(x_{t}\) ? How would you estimate the parameters \(ho_{1}\) and \(ho_{2}\) ?