Estimation of Common Long-Memory Components in Cointegrated Systems
提出一种估计大型协整系统中共同长记忆成分的新方法，通过识别I(1)共同因子并分析其协整关系，利用误差修正模型进行估计和假设检验，适用于高维经济数据的降维分析。
The study of cointegration in large systems requires a reduction of their dimensionality. To achieve this, we propose to obtain the I(1) common factors in every subsystem and then analyze cointegration among them. In this article, a new way of estimating common long-memory components of a cointegrated system is proposed. The identification of these I(1) common factors is achieved by imposing that they be linear combinations of the original variables Xt , and that the error-correction terms do not cause the common factors at low frequencies. Estimation is done from a fully specified error-correction model, which makes it possible to test hypotheses on the common factors using standard chi-squared tests. Several empirical examples illustrate the procedure.