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作 者:苏梽芳[1] 傅一铮 包浩华 Su Zhifang;Fu Yizheng;Bao Haohua
机构地区:[1]华侨大学经济与金融学院
出 处:《宏观经济研究》2021年第5期20-30,共11页Macroeconomics
基 金:国家社会科学基金重大项目“从制造向服务转型过程中二三产业统筹协调发展的重要问题研究”(编号:20&ZD087);泉州市社科规划重点项目“全球新冠疫情背景下泉州市重点领域金融风险防范与化解”(批准号:2020C02)的阶段性成果。
摘 要:监测宏观经济走势,对经济周期转换进行及时预警,有利于为宏观经济调控政策制定提供有益参考。本文基于2008年至2019年日度中国国债收益率曲线数据,重构7组长、短期国债期限利差函数型数据分析对象,构建函数型数据Logit模型实证分析不同期限利差对经济周期转换的预警指示作用。研究发现:(1)7组利差函数型数据分析对象所构建的函数型数据Logit模型均能预测出经济下行区间。其中,7年期与1年期利差函数型数据分析对象的预测正确率最高。(2)函数型数据Logit模型的预测正确率高于Nelson-Siegel模型三因子构建的Logit模型。本文基于函数型数据分析视角,使用更完整的原始日度信息,减少了信息损失,提高对经济下行区间的预测正确率,对于当前经济下行阶段的宏观调控政策具有重要参考价值。Monitoring macroeconomic trends, and timely early warning of business cycle transitions, are conducive to providing a useful reference for the formulation of macroeconomic regulation and control policies. Based on the data of the daily yield curve of Chinese government bonds from 2008 to 2019, this paper reconstructs the functional data analysis objects of 7 groups of long-term and short-term government bond term spreads, and construct a functional data Logit model to empirically analyze the early warning and indication effect of interest rate spreads of different maturities on business cycle transitions. The study finds that:(1) The functional data Logit model constructed by the seven groups of spread functional data analysis objects can all predict the economic downturn interval. Among them, the 7-year and 1-year spread functional data analysis objects have the highest prediction accuracy.(2) The prediction accuracy of the functional data Logit model is higher than that of the Logit model constructed by the three-factor Nelson-Siegel model. Based on the perspective of functional data analysis, this paper uses more complete original daily information, reduces information loss, and improves the accuracy of forecasting the economic downturn interval. It has important reference value for the macro-control policies in the current economic downturn.
关 键 词:国债收益率曲线 经济周期 函数型数据Logit模型
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