CONSISTENT ESTIMATION IN COINTEGRATED VECTOR AUTOREGRESSIVE MODELS WITH NONLINEAR TIME TRENDS IN COINTEGRATING RELATIONS
研究了协整向量自回归模型中带非线性时间趋势的协整关系的高斯最大似然估计的一致性，在坐标无关框架下证明，允许一般非线性参数约束，并得到一致性阶数。
This paper studies the consistency of the Gaussian maximum likelihood estimator in a cointegrated vector autoregressive model with nonlinear time trends in cointegrating relations. The results are proved in a coordinate free framework that readily allows for general nonlinear parameter restrictions and makes it possible to show the consistency of reduced form parameter estimators without assuming identifiability of underlying structural parameters. Various consistency results for structural parameter estimators can then be obtained by imposing suitable identification conditions for the parameters of interest but not necessarily for nuisance parameters. Orders of consistency are also obtained because they are needed to develop a related asymptotic theory of statistical inference.