中国和美国信贷冲击跨境溢出效应的比较研究

罗融, 陈浪南, 黄守军

系统工程理论与实践 ›› 2019, Vol. 39 ›› Issue (9) : 2216-2230.

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系统工程理论与实践 ›› 2019, Vol. 39 ›› Issue (9) : 2216-2230. DOI: 10.12011/1000-6788-2018-0188-15
论文

中国和美国信贷冲击跨境溢出效应的比较研究

    罗融1, 陈浪南2, 黄守军2
作者信息 +

Comparative studies on the spillover effects of credit market shocks between China and the US

    LUO Rong1, CHEN Langnan2, HUANG Shoujun2
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文章历史 +

摘要

本文构建了基于符号约束识别的GVAR模型，并用以考察中国和美国的信贷市场冲击对全球41个国家的不同溢出效应.研究结果表明，中国紧缩性信贷市场冲击对本国实体经济有显著的负效应，但仅限于短中期；而美国信贷冲击对本国乃至全球经济都具有相当大且持久的负影响.中国信贷冲击的跨国效应较小，且主要通过贸易渠道.中国信贷市场的本国冲击能解释中国产出近10%的波动，但无论是本国效应还是跨境传导，总需求冲击仍是驱动中国经济周期波动的最主要力量.

Abstract

We investigate the global spillover effects of identified credit market shocks from China and the US by employing a structural GVAR model with sign restrictions. We find that the tighten credit market shocks from China have a significantly negative spillover effect on domestic output, but only in short term. However, the tighten credit market shocks from the US have a significantly negative effect on domestic output, and strong and persistent effects on the GDP in other countries. We also find that spillover effects of the credit market shocks from China on the GDP in other countries are small and transmitted only through the trade channel. The credit market shocks from China explain about 10% of output fluctuations in China, suggesting that the aggregate demand shocks are still the most important driving force for China's business cycle.

关键词

信贷市场冲击 / 跨境溢出效应 / 结构性GVAR模型 / 符号约束识别

Key words

credit market shocks / spillover effects / structural global vector autoregression (GVAR) model / sign restrictions

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罗融 , 陈浪南 , 黄守军. 中国和美国信贷冲击跨境溢出效应的比较研究. 系统工程理论与实践, 2019, 39(9): 2216-2230 https://doi.org/10.12011/1000-6788-2018-0188-15
LUO Rong , CHEN Langnan , HUANG Shoujun. Comparative studies on the spillover effects of credit market shocks between China and the US. Systems Engineering - Theory & Practice, 2019, 39(9): 2216-2230 https://doi.org/10.12011/1000-6788-2018-0188-15
中图分类号： F832.4   

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基金

国家社会科学基金青年项目（18CJL015）；教育部人文社会科学研究规划基金（17YJA790011）；广东省自然科学基金（2017A030311038）；中南财经政法大学中央高校基本科研业务费专项基金（2722019JCT006）
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