IV estimation is examined when some instruments may be invalid. This is relevant because the initial just-identifying orthogonality conditions are untestable, whereas their validity is required when testing the orthogonality of additional instruments by so-called overidentification restriction...

In dynamic regression models conditional maximum likelihood (least-squares) coefficient and variance estimators are biased. Using expansion techniques an approximation is obtained to the bias in variance estimation yielding a bias corrected variance estimator. This is achieved for both the...

An approximation to order T−2 is obtained for the bias of the full vector of least-squares estimates obtained from a sample of size T in general stable but not necessarily stationary ARX(1) models with normal disturbances. This yields generalizations, allowing for various forms of initial...

No abstract received.