Large-sample results in the estimation of a linear transformation

Abstract

We obtain the asymptotic covariance matrix of the maximum likelihood estimators of the coefficients in a linear functional relationship between two vector variables observed with error. The matrix cannot be found by the usual method of inverting the information matrix due to the presence of incidental parameters. The joint asymptotic distribution of the estimators is shown to be normal under some mild conditions on the incidental parameters. A consistent estimator of the asymptotic co variance matrix is also suggested.