放松利率管制、过度负债与债务期限结构

放松利率管制不仅消除了信贷市场摩擦,而且可以通过调整贷款利率水平以实现信贷风险与资金成本之间的匹配,从而对企业资本结构选择产生影响。本文以2000-2015年我国A股非金融类上市公司为研究样本,从企业杠杆选择和债务期限结构两个方面来实证检验放松利率管制如何影响企业资本结构。检验结果发现:放松利率管制不仅显著抑制企业过度负债,加快资本结构调整速度,而且延长企业债务期限。进一步检验还发现,放松利率管制显著抑制企业短贷长投行为,降低企业现金与现金流之间的敏感性。以上问题的研究不仅在理论上证实了放松利率管制影响企业杠杆选择以及资本错配的具体作用机理,而且在实践方面对于我们进一步推进利率市场化进程,完善市场在资源配置中的决定性作用具有重要的政策启示意义。     

货币政策与异质性企业杠杆率——基于纵向产业结构的视角

当前,高杠杆已成为我国金融风险的重要源头,围绕结构性去杠杆来防范化解金融风险的基本思路,各方提出了一系列去杠杆措施。在此背景下,本文建立了一个包含“金融摩擦”与“资产负债表衰退”双重机制的动态随机一般均衡(DSGE)模型,探讨了中央银行紧缩性货币政策对国有企业与民营企业杠杆率的影响机制。本文研究认为,第一,中央银行提高政策利率会降低国有企业杠杆率,但会以民营企业杠杆率上升与总产出略微下降为代价;第二,伴随着政策利率上升,纵向产业联结度下降将会扩大国有企业与非金融企业整体杠杆率下降幅度,并减小民营企业杠杆率上升幅度;第三,货币政策对非金融企业杠杆率进行响应有助于提高社会福利,但效果并不显著。由此,本文研究认为,推动经济去杠杆需要在管住“货币”的同时,深入研究财政政策、宏观审慎等其他政策选项的可行性。在推动去杠杆的总过程中,货币政策要管住货币“总闸门”,宏观审慎政策要把住风险“总关口”。     

Forecasting volatility with time-varying leverage and volatility of volatility effects

Predicting volatility is of primary importance for business applications in risk management, asset allocation, and the pricing of derivative instruments. This paper proposes a measurement model that considers the possibly time-varying interaction of realized volatility and asset returns according to a bivariate model to capture its major characteristics: (i) the long-term memory of the volatility process, (ii) the heavy-tailedness of the distribution of returns, and (iii) the negative dependence of volatility and daily market returns. We assess the relevance of the effects of “the volatility of volatility” and time-varying “leverage” to the out-of-sample forecasting performance of the model, and evaluate the density of forecasts of market volatility. Empirical results show that our specification can outperform the benchmark HAR–GARCH model in terms of both point and density forecasts.     

企业创新与杠杆率动态调整关系实证研究——创新效率视角

基于沪、深证券市场2008-2017年上市公司非平衡面板数据，从研发效率和专利产出两个维度综合分析企业创新效率与杠杆率调整的动态关系。结果表明：在调整效应上，高研发效率与高专利产出有利于企业向下调整杠杆率，企业所有权异质性不会改变这种杠杆调整效应，但具有明显的非对称性，即国有企业调整效应更为显著；在加速效应上，随着研发效率提高、专利产出增加，杠杆率下降速度加快，国有企业对研发效率加速效应更敏感，而非国有企业对专利产出加速效应更敏感。     

经济政策不确定性与企业杠杆率

本文从政策不确定性的视角探讨中国经济转型过程中企业杠杆率变动背后的逻辑。在基于2002—2016年A股上市公司的季度数据描述企业杠杆率结构性变化的经验事实以及理论分析的基础上,运用Baker et al. (2016) 构建的经济政策不确定性指数实证分析政策不确定性与企业杠杆率之间的关系。结果表明,经济政策不确定性对企业杠杆率具有显著的负向影响;这一负向效应在短期负债率、民营、小规模和制造业企业更为明显。进一步考虑经济转型的扩展分析发现,政策不确定性对企业杠杆率的负向影响会随着地区市场化水平的提高、民营化改革的推进和对外开放度的扩大而显著降低。本文的研究对深入理解企业杠杆率变化背后的逻辑以及科学地制定供给侧结构性改革相关政策具有现实意义。     

Quantity of finance and financial crisis: A non-monotonic investigation☆

Whether finance is beneficial to economic development remains ambiguous. There are studies arguing that finance can facilitate growth and increase stability. However, the recent global financial crisis has led some to argue that finance can decrease stability and lead to more crises. This paper constructs a non-monotonic framework of quantity of finance (measured by leverage) and financial crisis and decomposes leverage into fundamental and excess components. Using cross-country level data, the empirical results confirms that it is excess leverage, rather than fundamental leverage, that results in the increase of probability of financial crisis. Further empirical results show that excess leverage leads to a higher probability of currency crisis, asset price collapse, and banking crisis, while fundamental leverage helps alleviates the crises. This paper reconciles the two contrasting views of the relationship between finance and economic development and provides strong policy implication to pay special attention to the sudden increase of leverage, which is probably excessive, rather than fundamental leverage.     

互联网普及如何影响中国家庭债务杠杆率

互联网技术的普及推动了数字金融、移动支付、金融科技等一系列金融创新的发展，基于此，文章利用中国家庭金融调查（CHFS）2017年的数据，细致探讨了互联网这一最基础的技术普及与家庭债务杠杆率的关系及内在作用机理。结果发现：（1）互联网的使用将显著推高家庭的债务杠杆率。在使用工具变量回归、处理效应模型与PSM匹配纠正内生性问题后，这一结论依然成立。（2）除通过促进电子支付、增加金融可及性外，互联网的使用还将通过提高信息搜寻与增强社会互动这两种渠道而带来家庭债务杠杆率的累积。（3）互联网的使用与家庭债务杠杆率间存在显著的非线性关系，即意味着只有当对互联网的使用达到一定程度后，其才会带来家庭债务风险。（4）对于受需求型信贷约束、低收入与中老年群体，互联网使用对这类群体债务杠杆率的影响程度更大。进一步地，除网络平台借款将推高家庭债务杠杆外，文章还考察了互联网的使用对民间借贷的影响，并发现其对家庭非正规借贷杠杆率的影响更为突出。而对于金融知识欠缺的家庭，其债务杠杆率更高。这说明，在鼓励使用互联网推动家庭参与金融市场的同时，也要注意防范过度使用互联网所带来的金融风险，而其中一种有效的途径便是普及金融知识教育，提高居民的金融素养。     

经营风险与企业杠杆率

本文从理论和实证两方面考察企业经营风险将如何影响其杠杆率。其中,企业面临的经营风险被定义为在企业所属“年份×城市×二位行业”层面内除自身外其他所有企业资产收益率(ROA)的分布标准差。整体而言,当企业经营风险上升时,其投资和负债决策将更加保守,表现为资产负债表收缩和杠杆率下降。分债务期限来看,杠杆率的变化又可分为“规模效应”和“结构效应”,前者指向投资、负债决策的整体收缩,后者指向债务结构中短期负债占比的下降。经营风险上升时,杠杆率下降主要体现为短期债务的缩减;分所有制来看,非国有企业对经营风险的敏感度较强,国有企业对经营风险的敏感度较小,这与两类企业的融资难易程度相符。     

How to make regulators and shareholders happy under Basel III

In addition to the Basel II capital ratio, Basel III requires banks to respect additional ratios, such as leverage ratio, liquidity coverage ratio and net stable funding ratio. Banks are required to be compliant with all four constraints simultaneously. Our article provides a framework for banks to help their search for an optimal transition from Basel II to Basel III. Recognizing that banks’ return and the four constraints are of linear type, this search can be formulated as a linear program and solved by standard software. Incorporating uncertainty on future defaults, risk weights and withdrawals and formulating the problem as a Chance constrained model does not only yield optimal transition strategies but also determines the internal thresholds for the Basel III-ratios. Our approach needs two standard inputs from controlling: profit margins per product and non-financial adjustment costs to expand or cut back business. The adjustment cost can be used to calibrate the model to the current business mix. This calibration can be done by bank outsiders and allows the model to be used in impact studies to replace ad hoc strategies. To highlight its practicality, we apply our model to a typical German bank with a business mix that complies with Basel II, but not with the Basel III-, capital-, leverage- and net stable funding-ratio. Assuming that its business model is optimal under Basel II, we find that this bank would achieve compliance restructuring its funding side by replacing interbank funding by capital and retail deposits. Additional uncertainty would amplify the magnitude of the changes, but would still affect the same positions. These findings are robust against alternative margin definitions and adjustment cost levels.     

Leverage-induced systemic risk under Basle II and other credit risk policies

We use a simple agent based model of value investors in financial markets to test three credit regulation policies. The first is the unregulated case, which only imposes limits on maximum leverage. The second is Basle II and the third is a hypothetical alternative in which banks perfectly hedge all of their leverage-induced risk with options. When compared to the unregulated case both Basle II and the perfect hedge policy reduce the risk of default when leverage is low but increase it when leverage is high. This is because both regulation policies increase the amount of synchronized buying and selling needed to achieve deleveraging, which can destabilize the market. None of these policies are optimal for everyone: risk neutral investors prefer the unregulated case with low maximum leverage, banks prefer the perfect hedge policy, and fund managers prefer the unregulated case with high maximum leverage. No one prefers Basle II.