中文摘要：

本文构建能够结合月度数据和季度数据的马尔科夫区制转换混频数据抽样（MS-MIDAS）模型,用于对中国经济周期的区制监测。通过利用实时数据对MS-MIDAS类模型进行最优选取和参数估计,监测中国1993—2013年间的经济周期区制变化,并得到中国经济运行状况的区制转换概率。实证结果表明：中国经济周期波动呈现三区制的阶段性变化;不同区制的持续时间具有非对称性;MS-MIDAS模型监测经济周期波动具有相对精确性与时效性。

英文摘要：

This paper constructs Markov Regime Switching mixed-frequency data sampling （MS-MIDAS） model which can be combined monthly data and quarterly data for monitoring Chinese business cycle regime. By using of the real-time data,it makes the optimal selection and the parameter estimation for MS-MIDAS model, monitors China＇ s business cycle regime switching from 1993 to 2013, and gets the regime transition probabilities which is used for description of China＇ s economic situation. Empirical evidence shows that, China＇ s business cycle displays periodic fluctuations in three regimes; different regimes have made the asymmetry of duration ; it also verifies that the MS-MIDAS model monitoring fluctuations of the business cycle is accuracy and timeliness.