A Note on Common Cycles, Common Trends, and Convergence
比较结构时间序列模型与共同特征方法，用美国各州人均收入数据检验一个允许收敛到共同增长路径的新模型的预测表现，并提出共同周期检验。
This article compares and contrasts structural time series models and the common features methodology. The way in which trends are handled is highlighted by describing a recent structural time series model that allows convergence to a common growth path. Postsample data are used to test its forecasting performance for income per head in U.S. regions. A test for common cycles is proposed, its asymptotic distribution is given, and small-sample properties are studied by Monte Carlo experiments. Applications are presented, with special attention given to the implications of using higher-order cycles.