Linear Models with Random Regressors

In many situations, assuming exogeneity for the regressors is likely to be incorrect. Indeed, it is well—known that in simultaneous equations models, some of the regressors in a given equation are the dependent variables in others and then, are correlated with the disturbances of the equation under consideration. Further examples, when exogeneity cannot be assumed for regressors, are when they are subject to measurement errors or the case of autoregressive models.