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The Selection and Co-location of Traditional and Structure Monetary Policy Instruments: An Analysis from the Perspective of Structural Leverage Resolving |
YIN Xingshan, YI Zhenhua, XIANG Yanbiao
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Hangzhou Central Sub-branch, the People's Bank of China |
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Abstract The degree of leverage of China's non-financial corporate sector has risen rapidly since the international financial crisis in 2008. China has the highest leverage level among major global economies, and has the structural characteristic that large and state-owned enterprises have a more significant process of leverage increase than private SMEs. The reasons are complex, but we observe that when the financial structure is dominated by indirect financing, the non-market-oriented interest rate factor weakens the pricing function of financial resources, combined with rigid redemption due to implicit government guarantees, insufficient competition, and serious homogeneity in the financial industry. This results in a credit bias in terms of the property rights and scale discrimination of enterprises during the allocation of credit resources, which leads to a structural mismatch of financial resources and exacerbates the structural leverage problem. The traditional monetary policy is the monetary aggregate adjustment policy, but this faces a dilemma in dealing with structural leverage. An expansionary monetary policy helps to reduce the interest burden and may stimulate the real sector to obtain more loans. However, a tight monetary policy can restrain the overall leverage level, and thus further exacerbate structural leverage problems. The People's Bank of China recently implemented various structural monetary policy instruments, such as the targeted medium-term lending facility, and monetary policy thus began to show structural features. Thus, making the optimal choice between tradition-oriented and structure-oriented monetary policy instruments, and exerting the structural adjustment effect of the structural monetary policy, have become important variables that must be considered when resolving the policy of structural leverage. Existing studies analyze the leverage problem and monetary policy responses from various perspectives, and many ideas and methods are proposed. However, the assumptions, leverage characteristics, and policy operation modes of foreign markets are quite different from those of China. Most Chinese studies focus on quantitative descriptive and qualitative analyses, while policy analysis is limited to the responses of the traditional monetary policy. To accurately identify the causes of structural leverage and to understand the effects and mechanisms of different choices of monetary policy instruments on resolving structural leverage, we systematically study this issue from two perspectives: empirical analysis and theoretical analysis. In our empirical analysis, we identify the relationship among different economic cycles, credit allocation bias, and changes in the leverage structure of enterprises, and examine the effect of traditional monetary policy using a panel regression model based on the annual data of China's 34 industrial sectors. The results indicate that the existence of credit allocation bias leads to heterogeneity in the leverage of enterprises with different property rights, which causes the structural leverage phenomenon to vary in the different stages of the economic cycle, and traditional monetary policy tools cannot easily solve the structural leverage problem. In the theoretical analysis, we combine the asymmetric investment and leverage change effects due to credit allocation bias in our DSGE model to identify the generation mechanism of these effects, and the optimal selection of monetary policy instruments in structural deleveraging. We find that tradition-quantity instrument is a better choice when addressing the structural leverage problem under the shock of technology, and that an appropriate combination of tradition-oriented and structure-oriented instruments is a better choice when addressing structural leverage under a price shock. In addition, if the economy is faced with the co-existence of structural leverage and an economic downturn under the shock of economic risk, structure quantity instruments are necessary to reduce the loans of state-owned enterprises, and structure price instruments are necessary to reduce the loan costs for private enterprises.
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Received: 10 June 2019
Published: 02 July 2020
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Cite this article: |
YIN Xingshan,YI Zhenhua,XIANG Yanbiao. The Selection and Co-location of Traditional and Structure Monetary Policy Instruments: An Analysis from the Perspective of Structural Leverage Resolving[J]. Journal of Financial Research,
2020, 480(6): 60-77.
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URL: |
http://www.jryj.org.cn/EN/ OR http://www.jryj.org.cn/EN/Y2020/V480/I6/60 |
[1] |
韩国高、高铁梅、王立国、齐鹰飞和王晓姝,2011,《中国制造业产能过剩的测度、波动及成因研究》,《经济研究》第12期,第18~31页。
|
[2] |
胡志鹏,2014,《“稳增长”与“控杠杆”双重目标下的货币当局最优政策设定》,《经济研究》第12期,第60~71+184页。
|
[3] |
何青、钱宗鑫和郭俊杰,2015,《房地产驱动了中国经济周期吗》,《经济研究》第12期,第41~53页。
|
[4] |
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11~25页。
|
[5] |
纪洋、王旭、谭语嫣和黄益平,2018,《经济政策不确定性,政府隐性担保与企业杠杆率分化》,《经济学(季刊)》第17卷第2期,第449~470页。
|
[6] |
栗亮和刘元春,2014,《经济波动的变异与中国宏观经济政策框架的重构》,《管理世界》第12期,第38~50+187页。
|
[7] |
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。
|
[8] |
马贱阳,2011,《结构性货币政策:一般理论和国际经验》,《金融理论与实践》第4期,第111~115页。
|
[9] |
马文涛和魏福成,2011,《基于新凯恩斯动态随机一般均衡模型的季度产出缺口测度》,《管理世界》第5期,第39~65页。
|
[10] |
马建堂、董小君、时红秀、徐杰和马小芳,2016,《中国的杠杆率与系统性金融风险防范》,《财贸经济》第1期,第5~21页。
|
[11] |
马家进,2018,《金融摩擦、企业异质性和中国经济波动——基于DSGE模型的分析》,博士学位论文,浙江大学。
|
[12] |
欧阳志刚和薛龙,2017,《新常态下多种货币政策工具对特征企业的定向调节效应》,《管理世界》第2期,第53~66页。
|
[13] |
彭俞超和方意,2016,《结构性货币政策、产业结构升级与经济稳定》,《经济研究》第7期,第29~42页。
|
[14] |
吴盼文、张华强、肖毅、何志强、陈国权和吴宗书,2017,《隐性补贴、要素市场扭曲与货币政策》,《海南金融》第2期,第4~19页。
|
[15] |
杨振兵和张诚,2015,《中国工业部门产能过剩的测度与影响因素分析》,《南开经济研究》第6期,第92~109页。
|
[16] |
杨小海、刘红忠和王弟海,2017,《中国应加速推进资本账户开放吗?——基于DSGE的政策模拟研究》,《经济研究》第8期,第49~64页。
|
[17] |
周逢民,2004,《论货币政策的结构调整职能》,《金融研究》第7期,第51~56页。
|
[18] |
中国人民银行营业管理部课题组,2017,《预算软约束、融资溢价与杠杆率——供给侧结构性改革的微观机理与经济效应研究》,《经济研究》第10期,第53~66页。
|
[19] |
张斌、何晓贝和邓欢,2018,《不一样的杠杆:从国际比较看杠杆上升的现象、原因与影响》,《金融研究》第2期,第15~29页。
|
[20] |
中国社会科学院国家资产负债表研究中心,2018,《中国去杠杆进程报告(2017)》。
|
[21] |
中国人民银行金融稳定分析小组,2018,《中国金融稳定报告2018》,中国金融出版社。
|
[22] |
中国人民大学中国宏观经济分析与预测课题组,2018,《结构性去杠杆下的中国宏观经济——2018年中期中国宏观经济分析与预测》,《经济理论与经济管理》第8期,第5~19页。
|
[23] |
Abel. A., and J. Eberly, 1999. “Investment and q with Fixed Costs: An Empirical Analysis”, working paper, Wharton school,University of Pennsylvania.
|
[24] |
Bernanke B. S., and M. Gertler., 1995. “Inside the Black Box:The Credit Channel of Monetary Policy Transmission”, The Journal of Economic Perspectives,9(4): 27~48.
|
[25] |
Calvo G. A., 1983. “Staggered Prices In a Utility-Maximizing Framework”, Journal of Monetary Economics, 12: 383~398.
|
[26] |
Cecchetti, S.G., M. S. Mohanty, and F. Zampolli., 2011. “The Real Effects of Debt”, Working Paper, BIS.
|
[27] |
Elekdag, S. and Y. Wu., 2011. “Rapid Credit Growth: Boon or Boom~Bust?” Working Paper, IMF.
|
[28] |
Fagnart, J. F., O. Licandro,and F. Portier., 1999. “Firm Heterogeneity, Capacity Utilization, and the Business Cycle”, Review of Economic Dynamics,2(2):433-455.
|
[29] |
International Monetary Fund. 2015. “Vulnerabilities, Legacies, and Policy Challenges Risks Rotating to Emerging Markets,” Global Financial Stability Report, IMF.
|
[30] |
Mendoza, E. and M. Terrones., 2008. “An Anatomy of Credit Booms: Evidence from Macro Aggregates and Micro Data”, Working Paper,NBER.
|
[31] |
Schularick, M. and A. M. Taylor., 2012. “Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870~2008”, American Economic Review, 102(2):1029~1061.
|
|
|
|