Please wait a minute...
金融研究  2022, Vol. 499 Issue (1): 19-37    
  本期目录 | 过刊浏览 | 高级检索 |
“稳增长”与“防风险”双目标的宏观调控政策抉择
陈创练, 高锡蓉, 刘晓彬
暨南大学经济学院/南方高等金融研究院,广东广州 510632;
浙江大学经济学院/金融研究院,浙江杭州 310013
Macro-control Policy Choices for the Dual Objectives of Steady Growth and Risk Prevention
CHEN Chuanglian, GAO Xirong, LIU Xiaobin
College of Economics and Southern China Institute of Finance, Jinan University;
School of Economics and Academy of Financial Research, Zhejiang University
下载:  PDF (2052KB) 
输出:  BibTeX | EndNote (RIS)      
摘要 “防风险”和“稳增长”是当前宏观调控的两大政策目标,为此,本文构建一个平衡兼顾双重政策目标的门限理论模型框架,基于反事实方法评估了动态平衡上述两大目标的最优财政货币政策组合。研究表明:(1)2008年以前,财政政策和货币政策都表现出较强的稳增长政策功效,但国际金融危机后,政策取向更倾向于动态平衡“稳增长”与“防风险”目标。(2)财政政策对三部门杠杆的影响呈现显著增强态势,数量型货币政策效果则在经历“增加—下降”周期后趋于稳定,利率政策效果显著而且近年来呈现增强态势,由此表明利率的传导效果正在不断得以强化。(3)从反事实结果看,宏观调控的最优政策搭配抉择取决于政策当局在动态平衡不同目标中的政策取向,特别是,依赖于精准调控“稳增长”与“防风险”目标的偏好强度。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
陈创练
高锡蓉
刘晓彬
关键词:  货币政策  财政政策  杠杆率  经济增长    
Summary:  High leverage has helped China to pursue economic growth for a long time, but it has begun restricting sustainable development. Therefore, determining how to balance macro leverage and economic growth is extremely important. This article constructs a macro-control model that dynamically balances the dual policy objectives of risk prevention and steady growth and uses a latent threshold-time varying parameter-vector autoregressive (LT-TVP-VAR) model to evaluate the time-varying impulse response function of China's monetary and fiscal policy effects on household, corporate, and government leverage and economic growth in various periods from 1996 to 2019. Then, a counterfactual method is used to evaluate the optimal fiscal and monetary policy combination of steady growth and risk prevention.
This article's contributions are mainly the following: First, in theory, risk prevention and steady growth are mutually complementary opposites. Therefore, this article constructs a macro-control theoretical model to measure the dynamic balance between the two. The model can also test the effects of fiscal and monetary policy in achieving the goals of risk prevention and steady growth. Second, the traditional constant coefficient model cannot identify the time-varying relationship between variables, and the TVP-VAR model is limited by the subjectivity of setting time-varying parameters. Therefore, this paper uses the LT-TVP-VAR model. The advantage of this model is that there is only a time-varying relationship between variables when the relationship between the variables exceeds the latent threshold. Otherwise, there is a constant coefficient relationship between the variables, which is more in line with reality. The LT-TVP-VAR model accounts for the time-varying and structural mutations of the economic structure. In addition, the setting of latent thresholds can eliminate the instability between variables and characterize the dynamic and static relationship between the dual goals of macro-control. Third, this study assesses the time-varying effects of macro-control on the dual goals of steady growth and risk prevention by measuring and comparing the effects of fiscal and monetary policy combinations to find the combination with the desired policy effect. The results provide a theoretical basis and useful reference for policy formulation.
The results show that, using the 2008 international financial crisis as a demarcation line, there are stage differences in the effects of macroeconomic policies. Before 2008, the steady growth effect of price-based monetary and fiscal policy was obvious, and quantitative monetary policy significantly affected steady growth and risk prevention. Since 2008, the policy orientation has been to dynamically balance the goals of steady growth and risk prevention. Historically, the influence of fiscal policy on leverage in the three sectors has shown an increasing trend, the effect of quantitative monetary policy has stabilized, and the regulatory advantages of price-based monetary policy have gradually emerged. The results of the counterfactual simulation show that without monetary policy coordination, fiscal policy cannot achieve the objectives of steady growth and risk prevention. Moreover, without the influence of fiscal policy, the effect of price-based and quantitative monetary policy on leverage in the three sectors and economic growth is weaker. Therefore, the policy or policy combination that is effective in regulating the economy depends on the policy objectives. For example, a combination of fiscal and monetary policies is effective for deleveraging the three sectors. In terms of stable growth, the effective coordination of fiscal and monetary policies from 1996 to 2007 was conducive to achieving steady growth. However, after the international financial crisis, large-scale fiscal expansion may weaken the effect of monetary policy in maintaining stable economic growth.
Keywords:  Monetary Policy    Fiscal Policy    Leverage Ratio    Economic Growth
JEL分类号:  E420   E62   E58  
基金资助: * 本文获得国家社会科学基金重点项目(21AZD027)、国家自然科学基金项目(72071094、72003171、71771093)、教育部人文社会科学研究规划项目(17YJA790009)以及广东省高等学校珠江学者岗位计划资助项目(2019)的资助。感谢匿名审稿人和编辑部老师提出的富有建设性的修改意见,文责自负。
通讯作者:  刘晓彬,经济学博士,助理教授,浙江大学经济学院/金融研究院,E-mail:liuxiaobin@zju.edu.cn.   
作者简介:  陈创练,经济学博士,教授,暨南大学经济学院/南方高等金融研究院,E-mail:chenchuanglian@aliyun.com.高锡蓉,博士研究生,暨南大学经济学院,E-mail:gaoxirong@aliyun.com.
引用本文:    
陈创练, 高锡蓉, 刘晓彬. “稳增长”与“防风险”双目标的宏观调控政策抉择[J]. 金融研究, 2022, 499(1): 19-37.
CHEN Chuanglian, GAO Xirong, LIU Xiaobin. Macro-control Policy Choices for the Dual Objectives of Steady Growth and Risk Prevention. Journal of Financial Research, 2022, 499(1): 19-37.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2022/V499/I1/19
[1]纪敏、严宝玉和李宏瑾,2017,《杠杆率结构、水平和金融稳定——理论分析框架和中国经验》,《金融研究》第2期,第15~29页。
[2]刘晓光、刘元春和王健,2018,《杠杆率、经济增长与衰退》,《中国社会科学》第6期,第50~70页。
[3]刘晓光和张杰平,2016,《中国杠杆率悖论——兼论货币政策“稳增长”和“降杠杆”真的两难吗》,《财贸经济》第8期,第5~19页。
[4]吕炜、高帅雄和周潮,2016,《投资建设性支出还是保障性支出——去杠杆背景下的财政政策实施研究》,《中国工业经济》第8期,第7~24页。
[5]马勇和陈雨露,2017,《金融杠杆、杠杆波动与经济增长》,《经济研究》第6期,第33~47页。
[6]申广军、张延和王荣,2018,《结构性减税与企业去杠杆》,《金融研究》第12期,第105~122页。
[7]谭小芬、李源和苟琴,2019,《美国货币政策推升了新兴市场国家非金融企业杠杆率吗?》,《金融研究》第8期,第38~57页。
[8]王朝才、汪超和曾令涛,2016,《财政政策、企业性质与资本结构动态调整——基于A股上市公司的实证研究》,《财政研究》第9期,第52~63页。
[9]周菲、赵亮和尹雷,2019,《去杠杆的路径选择:财政去杠杆还是金融去杠杆?——基于企业部门的分析》,《财政研究》第2期,第75~90页。
[10]Arcand, J. L., E. Berkes and U. Panizza, 2015, “Too Much Finance?” ,Journal of Economic Growth, 20(2):105~148.
[11]Benigno, P., G. B. Eggertsson and F. Romei, 2014, “Dynamic Debt Deleveraging and Optimal Monetary Policy,” NBER Working Paper, No.20556.
[12]Boz, E. and E. G. Mendoza, 2014, “Financial Innovation, the Discovery of Risk, and the U.S. Credit Crisis,” Journal of Monetary Economics, 62(1): 1~22.
[13]Bruno, V. and H. S. Shin, 2015, “Capital Flows and the Risk-Taking Channel of Monetary Policy,” Journal of Monetary Economics, 71(2):119~132.
[14]Cecchetti, S. and E. Kharroubi, 2012, “Reassessing the Impact of Finance on Growth,” BIS Working Papers, No.381.
[15]Chen, K., J. Ren and T.Zha, 2018, “The Nexus of Monetary Policy and Shadow Banking in China,” American Economic Review, 108(12):3891~3936.
[16]Day, R. H. and C. Yang, 2011, “Economic Growth and the Effects of Fiscal Policy,” Metroeconomica, 62(1):218~ 234.
[17]Favero, A. C. and T. Monacelli, 2003, “Monetary-Fiscal Mix and Inflation Performance: Evidence from the US,” CEPR Discussion Paper, No. 3887.
[18]George, E. I., D. Sun and S. Ni, 2008, “Bayesian Stochastic Search for VAR Model Restrictions,” Journal of Econometrics, 142:553~580.
[19]Jerzmanowski and Micha, 2017, “Finance and Sources of Growth: Evidence from the U.S. States,” Journal of Economic Growth, 22(1):97~122.
[20]Kim, C. J. and C. R. Nelson, 2006, “Estimation of a Forward-looking Monetary Policy Rule: a Time-varying Parameter Model Using Ex-post Data,” Journal of Monetary Economics, 53:1949~1966.
[21]Lhuissier, S. and U. Szczerbowicz, 2018, “Monetary Policy and Corporate Debt Structure,” Banque de France Working Paper, No.697.
[22]Ng, S. and P. Perron, 2001, “Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power,” Econometrica, 69(6): 1519~1554.
[23]Nicoletta, B., M. Giovanni and V. Stefania, 2018, “Fiscal Buffers, Private Debt, and Recession: The Good, the Bad and the Ugly,” Journal of Macroeconomics, 62:S0164070417305621.
[24]Primiceri and E. Giorgio, 2005, “Time Varying Structural Vector Autoregressions and Monetary Policy,” Review of Economic Studies, 3:821~852.
[25]Reinhart, C. M. and K. S. Rogoff, 2010, “Growth in a Time of Debt,” American Economic Review, 100(2):573~578.
[26]Rozendaal, J., Y. Malevergne and D. Sornette, 2016, “Macroeconomic Dynamics of Assets, Leverage and Trust,” International Journal of Bifurcation & Chaos, 26(8):1650133-1~23.
[27]Stephan Kohns, 2017, “Monetary Policy and Financial Stability,” ifo DICE Report, 15:17~18.
[28]Storz, M., M. Koetter, R. Setzer, et al., 2017, “Do We Want These Two to Tango? On Zombie Firms and Stressed Banks in Europe,” ECB Working Paper, No. 2104.
[29]Taylor, J. B., 1993, “Discretion Versus Policy Rules in Practice,” Carnegie-Rochester Conference Series on Public Policy, 39:195~214.
[30]Taylor, S. A. M., 2012, “Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008,” The American Economic Review, 102(2):1029~1061.
[31]William, C. and L. Conway, 2016, “Can Business Firms Have Too Much Leverage? M&M, RJR 1990, and the Crisis of 2008,” Modern Economy, 7(2):194~203.
[1] 马勇, 吕琳. 货币、财政和宏观审慎政策的协调搭配研究[J]. 金融研究, 2022, 499(1): 1-18.
[2] 张成思, 刘泽豪, 何平. 流动性幻觉与高杠杆率之谜[J]. 金融研究, 2021, 493(7): 19-39.
[3] 牛欢, 严成樑. 环境税率、双重红利与经济增长[J]. 金融研究, 2021, 493(7): 40-57.
[4] 吴立元, 赵扶扬, 王忏, 龚六堂. 美国货币政策溢出效应、中国资产价格波动与资本账户管理[J]. 金融研究, 2021, 493(7): 77-94.
[5] 董兵兵, 徐慧伦, 谭小芬. 货币政策能够兼顾稳增长与防风险吗?——基于动态随机一般均衡模型的分析[J]. 金融研究, 2021, 490(4): 19-37.
[6] 陆军, 黄嘉. 利率市场化改革与货币政策银行利率传导[J]. 金融研究, 2021, 490(4): 1-18.
[7] 战明华, 李帅, 姚耀军, 吴周恒. 投资潮涌、双重金融摩擦与货币政策传导——转型时期货币政策的结构调控功能探究[J]. 金融研究, 2021, 489(3): 1-17.
[8] 陆婷, 徐奇渊. 中国企业杠杆:一个周期性问题?[J]. 金融研究, 2021, 488(2): 1-19.
[9] 文书洋, 张琳, 刘锡良. 我们为什么需要绿色金融?——从全球经验事实到基于经济增长框架的理论解释[J]. 金融研究, 2021, 498(12): 20-37.
[10] 庄毓敏, 张祎. 流动性覆盖率监管会影响货币政策传导效率吗?——来自中国银行业的证据[J]. 金融研究, 2021, 497(11): 1-21.
[11] 刘贯春, 司登奎, 刘芳. 人力资本偏向金融部门如何影响实体经济增长?[J]. 金融研究, 2021, 496(10): 78-97.
[12] 尚玉皇, 赵芮, 董青马. 混频数据信息下的时变货币政策传导行为研究——基于混频 TVP-FAVAR模型[J]. 金融研究, 2021, 487(1): 13-30.
[13] 吕有吉, 景鹏, 郑伟. 人口老龄化、养老保险基金缺口弥补与经济增长[J]. 金融研究, 2021, 487(1): 51-70.
[14] 侯成琪, 黄彤彤. 流动性、银行间市场摩擦与借贷便利类货币政策工具[J]. 金融研究, 2020, 483(9): 78-96.
[15] 庄子罐, 贾红静, 刘鼎铭. 居民风险偏好与中国货币政策的宏观经济效应——基于DSGE模型的数量分析[J]. 金融研究, 2020, 483(9): 40-58.
[1] 李少昆. 美国货币政策是全球发展中经济体外汇储备影响因素吗?[J]. 金融研究, 2017, 448(10): 68 -82 .
[2] 康书隆, 余海跃, 刘越飞. 住房公积金、购房信贷与家庭消费——基于中国家庭追踪调查数据的实证研究[J]. 金融研究, 2017, 446(8): 67 -82 .
[3] 纪敏, 严宝玉, 李宏瑾. 杠杆率结构、水平和金融稳定——理论分析框架和中国经验[J]. 金融研究, 2017, 440(2): 11 -25 .
[4] 况伟大, 王琪琳. 房价波动、房贷规模与银行资本充足率[J]. 金融研究, 2017, 449(11): 34 -48 .
[5] 龙海明, 王志鹏. 征信系统、法律权利保护与银行信贷[J]. 金融研究, 2017, 440(2): 117 -130 .
[6] 白俊红, 吕晓红. FDI质量与中国经济发展方式转变[J]. 金融研究, 2017, 443(5): 47 -62 .
[7] 孙淑伟, 梁上坤, 阮刚铭, 付宇翔. 高管减持、信息压制与股价崩盘风险[J]. 金融研究, 2017, 449(11): 175 -190 .
[8] 邓路, 刘瑞琪, 江萍. 公司超额银行借款会导致过度投资吗?[J]. 金融研究, 2017, 448(10): 115 -129 .
[9] 梁巨方, 韩乾. 商品期货可以提供潜在组合多样化收益吗?[J]. 金融研究, 2017, 446(8): 129 -144 .
[10] 刘凤良, 章潇萌, 于泽. 高投资、结构失衡与价格指数二元分化[J]. 金融研究, 2017, 440(2): 54 -69 .
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 《金融研究》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持:support@magtech.com.cn
京ICP备11029882号-1