FULLY MODIFIED ESTIMATION OF SEASONALLY COINTEGRATED PROCESSES
FULLY MODIFIED ESTIMATION OF SEASONALLY COINTEGRATED PROCESSES
复制标题
完全修改的季节性协整过程估计
作者：
S. Gregoir
我们将菲利普斯和汉森（1990）提出的完全修正的普通最小二乘（OLS）估计的框架扩展到给定频率下的季节协整过程的情况。首先，我们推广了样本协方差矩阵（菲利普斯，1988年）的弱收敛结果的情况下，季节单位根。使用复数框架，我们然后表明，我们可以考虑存在于季节性协整的情况下，如Gregoir（1999 a）所示的约束，并推导出协整向量的估计，允许渐近正态推断。这使我们能够提出一个检验，其零假设是季节性协整的存在。蒙特卡洛演习调查有限样本的性质，这个测试程序。本文最后分析的情况下，存在一个以上的频率，可以观察到的季节协整。
We extend the framework of the fully modified, ordinary least squares (OLS) estimator introduced by Phillips and Hansen (1990) to the case of seasonally cointegrated processes at a given frequency. First we extend a weak convergence result of sample covariance matrices (Phillips, 1988) to the case of seasonal unit roots. Using a complex number framework, we then show that we can take into account the constraints that exist in a situation of seasonal cointegration as illustrated in Gregoir (1999a) and derive estimates of the cointegration vectors that allow for asymptotic normal inference. This allows us to propose a test whose null hypothesis is the existence of seasonal cointegration. A Monte Carlo exercise investigates the finite sample properties of this test procedure. The paper closes with the analysis of situations in which there exist more than one frequency at which seasonal cointegration can be observed.