二维Copula模型与Bayes估计法下美联储加息联动效应测度  

Measurement on Linkage Effect of Fed’s Interest Rate Increase under Two-dimensional Copula Model and Bayes Estimation Method

作　　者：陈莉 Chen Li(School of Economics and Management,Zhoukou Normal University,Zhoukou Henan 466000,China)

机构地区：[1]周口师范学院经济与管理学院,河南周口466000

出　　处：《统计与决策》2020年第3期125-130,共6页Statistics & Decision

基　　金：国家社会科学基金资助项目(16BGL105)。

摘　　要：文章运用二维动态Copula模型与贝叶斯估计方法,研究美联储加息与我国货币市场间的联动性。结果表明:美联储加息对我国货币市场具有当期正向联动效应,并对我国货币信贷投放及市场融资规模、基础货币供应量、GDP平减指数、实际汇率水平、社会投资价格指数等指标具有显著冲击;短期看,美联储加息将造成我国信贷投放规模与实际利率水平上涨,加大我国社会通胀压力;美联储加息对我国货币市场的负向冲击效应具有较持久性特点。This paper uses the two-dimensional dynamic copula model and Bayesian estimation method to study the linkage effect between the Fed’s interest rate hike and China’s money market.The results show that the interest rate hike of the Federal Reserve has a positive correlation effect on China’s money market,and has a significant impact on China’s money and credit supply,market financing scale,base money supply,GDP deflator index,real exchange rate level,social investment price index and other indicators;in the short term,the Fed’s interest rate hike will cause China’s credit scale and real interest rate level to rise,increasing the social inflationary pressure in China;the negative shock effect of the Fed’s interest rate increase on China’s money market has a relatively persistent characteristic.

关 键 词：美联储加息 ARMA边际分布模型 动态Copula模型 尾部相依性 

分 类 号：F832[经济管理—金融学]