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本文以次贷危机前后美国房地产市场与信贷供给间的相互作用为研究起点，分析美国1995年至2022年间的GDP和CPI波动特征，发现金融因素的过度繁荣会引发宏观经济的衰退。同理，本文剖析我国同时期的GDP和CPI波动特征，发现金融因素对守住不发生系统性金融风险的底线和维护宏观经济稳定格外重要。为了能够全面地测度一段时期内的金融状况，本文以金融因素为基础，对我国的金融周期进行测度。研究发现我国金融周期具有以下特点：(1)平均长度为11～15个季度，比经济周期更长，波幅更大，但绝对值小于欧美国家；(2)长度和波幅取决于政策阶段，与宏观经济运行联系紧密；(3)波动虽存在一定的不对称性，但并不明显，与欧美国家存在差异。此外，本文发现金融周期对宏观经济运行有很强的“预警”作用，作为门槛变量可“捕捉”到我国亚洲金融危机爆发至新冠疫情后绝大多数宏观经济波动，具有较强的宏观调控应用价值。
Abstract：Starting from the interaction between the US real estate market and credit supply before and after the subprime crisis, this paper analyzes the fluctuation characteristics of GDP and CPI in the US from 1995 to 2022, and finds that excessive prosperity of financial factors will lead to macroeconomic recession. Similarly, this paper analyzes the fluctuation characteristics of China's GDP and CPI in the same period, and also finds that financial factors are particularly important for preventing systemic financial risks and maintaining macroeconomic stability. In order to comprehensively measure the financial situation in a period of time, this paper measures China's financial cycle based on financial factors. It is found that China's financial cycle has the following characteristics: first, the average length is 11 to 15 quarters, which is longer than the business cycle, and the amplitude is larger, but the absolute value is smaller than that of European and American countries; second, the length and amplitude depend on the policy stage and are closely related to the macroeconomic operation; third, although there is a certain asymmetry in the fluctuation, but it is not obvious, which is different from European and American countries to some extent. In addition, this paper finds that the financial cycle has a strong “early warning” effect on macroeconomic operation, and as a threshold variable, it can “capture” the vast majority of macroeconomic fluctuations after the Asian financial crisis to the COVID-19 epidemic in China, and has strong macro-control application value.
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(1)本文未将新冠疫情期间纳入,是因为新冠疫情为全球公共安全的极端事件,如以全球人均计算,新冠疫情对美国宏观经济所产生的短期波动强度已大大超过了互联网“泡沫”和次贷危机(Jordà et al.,2022)。其冲击机制和作用点也有所不同,还需要进一步研究。
(2)以BP滤波所得数据为基准。
(3)由美联储亚特兰大分行发布,其基准数据来源于国家统计局和中国人民银行统计数据,运用插值法经过季节调整得出季度数据。
(4)本文使用由波谷到波谷的长度,遵循转折点分析法的原则(Harding and Pagan,2002;Canova and Schlaepfer,2015)。
(5)当然,这只是本节运用门限回归模型做计量分析所得的结论,相关研究可继续深化和细化。
(6)1995年4季度至1997年的数据的预测效果较差,经济周期的预测值与实际值出现完全相反的结果,这可能与数据缺失和数据质量有关。
基本信息:
DOI：
中图分类号:F832
引用信息:
[1]王三川,范从来.我国金融周期的测度、特征及其“预警”应用[J].经济学报,2024,11(04):86-122.
基金信息:
国家社科基金重大项目“金融业制度型开放助推构建新发展格局的路径研究”(项目号:23&ZD059)的资助