Consider a linear multiple regression model with scalar regressor \(x\) that is measured with error and a vector of other regressors \(\mathbf{z}\) that are free of measurement error.

(a) Maintaining the assumptions regarding measurement errors in the bivariate errors-in-variables model, extend the attenuation bias result and the identification-by-bounds result to this case.

(b) Check that the new results specialize to those for the bivariate case.