金融学院知识库

2008年全球金融危机爆发后，各国政府相继采取相关措施以刺激经济恢复。我国发布了“四万亿经济计划”，使得我国的经济得到快速复苏，但同时也遗留了一些问题，总体及各部门债务规模不断扩大，杠杆率水平迅速上升，尤其是非金融企业杠杆率提升幅度在各部门中处于首位。近年来，我国早已认识到企业高杠杆的严重性，提出了“去杠杆”和“结构性去杠杆”等一系列措施，企业在降杠杆方面取得了一定的成效。但是，企业杠杆率仍处于较高水平。而在新冠肺炎疫情爆发后，货币当局实施宽松的货币政策，增加货币供给的同时，非金融企业杠杆率再次呈现上升趋势，导致我国面临的经济金融环境趋于复杂，从而可能使得金融风险在各个主体及部门之间进一步累积及转移，引发经济与金融的动荡不安，最终导致系统性金融风险的爆发。在此背景下，开展非金融企业杠杆率对系统性金融风险的影响研究将具有重要意义，可以为如何降低系统性金融风险以及促进经济平稳发展提供一定的借鉴。

本文主要采用文献分析、理论分析和实证分析的研究方法，探析非金融企业杠杆率对系统性金融风险的影响。在文献分析部分，本文主要通过杠杆率的定义与测度、系统性金融风险的概念与度量以及非金融企业杠杆率对系统性金融风险的影响三个角度，对已有研究进行了梳理，概括总结了现有的研究现状并进行了相关评述。在理论分析部分，对债务-通缩理论、金融脆弱性理论、金融周期理论和资产价格泡沫理论进行了基本的阐述，并以此为基础，探究了非金融企业杠杆率对系统性金融风险的机理作用。在实证分析部分，以2005-2021年我国部分A股上市公司数据为基础，测度衡量各省份非金融企业杠杆率水平；基于数据可得性，选取2005年-2021年我国30个省份的相关数据为研究样本，采用综合指数法和熵值法构建了系统性金融风险指标。基于以上数据形成面板数据，并采用固定效应模型实证研究非金融企业杠杆率对系统性金融风险的影响。本文得到如下结论：第一，从非金融企业杠杆率角度，我国非金融企业杠杆率水平整体偏高，东中西部地区、不同性质企业、不同状态企业等方面杠杆率存在不同。第二，从系统性金融风险角度，我国区域系统性金融风险总体呈U型波动，东部地区系统性金融风险相对于中西部较低。第三，从非金融企业杠杆率对系统性金融风险的影响角度，研究发现：非金融企业杠杆率与系统性金融风险存在非线性关系，呈现“U”型；东西部非金融企业杠杆率与系统性金融风险同样呈现“U”型，但各自拐点存在不同，而中部非金融企业杠杆率对系统性金融风险的影响存在线性关系；地方国有企业杠杆率与系统性金融风险呈非线性关系，但中央企业和民营企业与系统性金融风险可能不存在非线性关系；企业自身发展情况对系统性金融风险的影响存在不同，正常企业杠杆率水平与系统性金融风险存在U型的非线性关系，而异常企业杠杆率与系统性金融风险呈正相关关系，即问题企业的杠杆率水平上升会显著增加系统性金融风险。基于本文研究结果，提出建立系统性金融风险的测度机制；实行有差别的金融防控政策；优化企业资产和融资结构的建议。

After the outbreak of the global financial crisis in 2008, governments around the world have taken relevant measures to stimulate economic recovery. China issued the "Four trillion economic Plan", which led to a rapid recovery of our economy, but at the same time left some problems, the overall and various sectors of the debt scale is constantly expanding, the leverage ratio is rising rapidly, especially non-financial enterprises in the leverage ratio of the first increase in all sectors. In recent years, China has already recognized the seriousness of high corporate leverage and put forward a series of measures, such as "deleveraging" and "structural deleveraging", and enterprises have achieved certain results in reducing leverage. However, corporate leverage remains at a high level. However, after the outbreak of the novel coronavirus pneumonia, the monetary authorities implemented loose monetary policies and increased the money supply, while the leverage ratio of non-financial enterprises showed a rising trend again, which led to a complicated economic and financial environment, which may further accumulate and transfer financial risks among various subjects and departments, leading to economic and financial turmoil. Eventually, systemic financial risks broke out. In this context, it will be of great significance to study the impact of leverage ratio of non-financial enterprises on systemic financial risks, which can provide certain references for how to reduce systemic financial risks and promote stable economic development.

This paper mainly adopts the research methods of literature analysis, theoretical analysis and empirical analysis to explore the influence of leverage ratio of non-financial enterprises on systemic financial risk. In the literature analysis part, this paper mainly combs the existing researches from three perspectives: the definition and measurement of leverage ratio, the concept and measurement of systemic financial risk, and the influence of non-financial enterprise leverage ratio on systemic financial risk, summarizes the existing research status and makes relevant comments. In the part of theoretical analysis, the debt-deflation theory, financial vulnerability theory, financial cycle theory and asset price bubble theory are basically elaborated, and on this basis, the mechanism effect of non-financial enterprise leverage ratio on systemic financial risk is explored. In the empirical analysis part, based on the data of some Chinese A-share listed companies from 2005 to 2021, the leverage ratio of non-financial enterprises in each province is measured. The relevant data of 30 provinces from 2005 to 2021 are selected as research samples, and the comprehensive index method and entropy method are used to construct the systematic financial risk index. Based on the above data, panel data is formed, and the fixed-effect model is adopted to empirically study the influence of leverage ratio of non-financial enterprises on systemic financial risks. This paper draws the following conclusions: First, from the perspective of leverage ratio of non-financial enterprises, the leverage ratio of Chinese non-financial enterprises is on the high side on the whole, and there are different leverage ratios in eastern, central and western regions, enterprises of different nature and enterprises in different states. Second, from the perspective of systemic financial risk, China's regional systemic financial risk generally presents U-shaped fluctuations, and the systemic financial risk in eastern China is lower than that in central and western China. Thirdly, from the perspective of the influence of leverage ratio of non-financial enterprises on systemic financial risks, the research finds that there is a nonlinear relationship between leverage ratio of non-financial enterprises and systemic financial risks, showing a "U" shape. The leverage ratio of non-financial enterprises in eastern and western China also presents a "U" shape with different inflection points, while the influence of leverage ratio of non-financial enterprises in central China on systemic financial risks has a linear relationship. There is a nonlinear relationship between the leverage ratio of local state-owned enterprises and systemic financial risks, but there may be no nonlinear relationship between central enterprises and private enterprises and systemic financial risks. There is a U-shaped nonlinear relationship between the leverage ratio of normal enterprises and systemic financial risk, while the leverage ratio of problem enterprises is positively correlated with systemic financial risk, that is, the increase of the leverage ratio of problem enterprises will significantly increase the systemic financial risk. Based on the research results of this paper, it is proposed to establish the measurement mechanism of systemic financial risk. Implement differentiated financial prevention and control policies. Suggestions for optimizing corporate assets and financing structure.