Dhrymes (1994, Econometric Theory, 10, 254-285) demonstrates the arising identification and estimation problems in singular equation systems when the error vector obeys an autoregressive scheme, as an extension of restricted least squares. Unfortunately, his main theorem concerning the...

For both deterministic or stochastic regressors, as well as parametric nonlinear or linear regression functions, we prove the weak consistency of the coefficient estimators for the Type I censored quantile regression model under different censoring mechanisms with censoring points depending on...

This paper derives the asymptotic normality of the nonlinear quantile regression estimator with dependent errors. The required assumptions are weak, and it is neither assumed that the error process is stationary nor that it is mixing. In fact, the notion of weak dependence introduced in this...

Dhrymes (1994, Econometric Theory, 10, 254-285) demonstrates the arising identification and estimation problems in singular equation systems when the error vector obeys an autoregressive scheme, as an extension of restricted least squares. Unfortunately, his main theorem concerning the...

The topic of this paper is the problem of a singular disturbance covariance matrix in (seemingly unrelated) systems of linear regression equations. This singularity is considered as being caused by exact linear restrictions on the endogenous variables, adding-up to a predetermined aggregate. It...

This paper addresses the combination of incomplete prior and sample information. In difference to the mixed estimation approach developed by H. Theil and A.S. Goldberger, dealing with prior knowledge of regression coefficients, we consider prior information on future observations of the...