Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data
提出一种利用混合频率和混合样本数据估计协整向量的简单方法，推导了谱回归估计量的渐近性质，并验证了其有限样本表现良好。
This paper proposes a simple method for exploiting the information contained in mixed frequency and mixed sample data in the estimation of cointegrating vectors. The asymptotic properties of easy-to-compute spectral regression estimators of the cointegrating vectors are derived and these estimators are shown to belong to the class of optimal cointegration estimators. Furthermore, Wald statistics based on these estimators have asymptotic chi-square distributions which enable inferences to be made straightforwardly. Simulation experiments suggest that the spectral regression estimators considered perform well in finite samples and are at least as good as time domain fully modified estimators. The finite sample size and power properties of the spectral regression-based Wald statistic are also found to be good.