When a nuisance parameter is unidentified under the null hypothesis, standard testing procedures cannot be applied due to the singularity of the information matrix. Probably best known examples are the problems of unknown change points and the mixtures of distributions in econometrics and...

This dissertation concerns theoretical and empirical aspects of a class of conditionally heteroskedastic models. We apply the White's information matrix (IM) test to the linear regression model with autocorrelated errors. A special case of one component of the test is found to be identical to...

Following Farrell's (1957) definitions of firm's technical and allocative efficiencies and the formulation of composite error stochastic frontier model by Aigner, Lovell and Schmidt (1977), a substantial amount of research work has been performed measuring firm's technical inefficiency using...

This dissertation concerns with some estimations of heteroskedastic models and tests for heteroskedasticity. We reconsider the minimum norm quadratic unbiased estimation (MINQUE) to obtain an alternative estimator of variance-covariance matrix in heteroskedastic models. We derive the analytical...