管理层权力制衡强度、债务约束与企业创新投资

企业创新是国家经济可持续增长的关键，受到管理层意愿的影响，因而需要对内部经营者的权力进行制衡。以2010-2018年我国A股上市公司为研究样本，实证检验管理层权力制衡强度对企业创新投资的影响，以及不同债务约束情境下高商业信用配置、高负债水平的调节效应，此外，还考察了产权性质的差异化影响。研究表明，管理层权力制衡强度越大，企业创新投资水平越高；高商业信用强化了该促进作用，而高负债水平弱化了该促进作用。进一步研究发现，管理层权力制衡强度与企业创新投资的关系在民企中更显著；国企能够更好地获得和运用商业信用，使其高商业信用对该关系的强化效应更显著；民企具有更强的债务约束，其高负债水平对该关系的弱化效应更明显。     

The effects of credit default swaps on corporate investment

ABSTRACT

This paper examines how credit default swaps (CDS) affect the corporate investment of the referenced entities. We document a significant reduction in corporate investment after CDS trading, a result that is robust to alternative model specifications and a set of endogeneity tests. Our findings of the increased firm risk and cost of capital support the costly external capital channel. The cross-sectional variations in CDS effects demonstrate that both reduced monitoring and the empty creditor problem might be the underlying forces driving the costly external capital channel. Our additional analysis implies that CDS trading is associated with an enhancement in investment efficiency for firms that are prone to overinvestment.     

Do significant risk warnings in annual reports increase corporate bond credit spreads? Evidence from China

Based on listed companies issuing bonds on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2017, this study analyzes the relationship between significant risk warnings in Chinese companies’ annual reports and corporate bond credit spreads. The main findings are as follows. First, in the Chinese market, “substantial warnings of significant risks” can significantly improve corporate bond credit spreads, reflecting the risk-warning effect; second, state-owned property rights weaken this effect, which only pertains to listed companies with poor risk management and low information quality; third, significant risk warnings increase investors’ heterogeneous beliefs, also affecting credit spreads; and fourth, through textual analysis, it is found that the corporate bond credit spread is greater when the disclosed risk factors are more pessimistic and less similar to those of the previous year. The findings of this paper help to enrich the literature on credit spreads and risk disclosure.     

On credit and output: Is the supply of credit relevant?

The consensus that changes in the supply of credit were irrelevant to making monetary policy decisions existed among macroeconomists during the second half of the twentieth century. Transmission of shocks to the real economy through changes in the supply of credit, however, played an important role in the recent U.S. financial crisis. This paper explores the extent to which policymakers should consider changes in the supply of credit when making forecasts and monetary policy decisions. More specifically, it considers whether a measure of real credit balances offers consistent and stable information, beyond that of a real interest rate and real money balances, about future output gaps during the U.S. post-war era. Results yield evidence that changes in real credit balances are the only variable, among those considered, to provide consistent and stable information about future output gaps over the entire sample period. Each information variable, however, provides relatively little value added for forecasting future output gaps, beyond a simple autoregressive model. To improve upon forecasts and monetary policy decisions, policymakers therefore should consider a broader range of information variables and occasionally reassess the relative weightings assigned to each.     

A Multicriteria Approach for Modeling Small Enterprise Credit Rating: Evidence from China

ABSTRACT

As the engine of China’s economy, small enterprises have been the central to the country’s economic development. However, given the characteristics of the small enterprises loan (i.e., short borrowing period, large volume, small amount and incomplete information), it is extremely challenging for financial institutions to assess their creditworthiness. Thus, it seriously delays and restricts the financing access for small enterprises. In an attempt to relieve the financing difficulty of small enterprises, this article makes use of 687 small wholesale and retail enterprises in a regional commercial bank in China, to establish a credit rating indicator system composed of 17 indicators by using both partial correlation analysis and probit regression. It then utilizes TOPSIS together with fuzzy C-means to score the credit ratings of our sample of small enterprises. With the dual test of default discrimination and ROC curve, the prediction accuracy of the established indicator system has reached 80.10% and 0.917, respectively, indicating the robustness and validity of our credit rating system.     

Non-rating revenue and conflicts of interest

Rating agencies produce ratings used by investors, but obtain most of their revenue from issuers, leading to a conflict of interest. We employ a unique data set on the use of non-rating services, and the associated payments, in India, to test if this conflict affects ratings quality. Agencies rate issuers that pay them for non-rating services higher (than agencies not hired for such services). Such issuers also have higher default rates. Both effects are increasing in the amount paid. These results suggest that issuers which hire agencies for non-rating services receive higher ratings despite having higher default risk.     

Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

“投资人付费”vs.“发行人付费”:谁的信用评级质量更高？

本文选择2011-2015年被中债资信覆盖的发债A股上市公司作为主要研究对象,比较了“投资人付费”与“发行人付费”模式下的评级质量高低。研究发现:(1)与“发行人付费”评级相比,采用“投资人付费”模式的中债资信所作评级显著更低。(2)与“发行人付费”评级相比,当采用“投资人付费”模式的中债资信所作评级越低时,发行人未来盈利能力越差、预期违约风险越高,投资者要求的风险补偿也越高,这表明“投资人付费”模式下的信用评级质量更高。(3)“发行人付费”模式的评级结果可以在一定程度上反映公司的内部私有信息,但由于同时存在独立性缺失问题,“发行人付费”模式的信用评级质量仍然不如“投资人付费”模式的信用评级质量,这说明独立性对于评级机构尤其重要。     

News sentiment,credit spreads,and information asymmetry

This paper examines how the sentiment of firm-specific news affects CDS spreads conditional on the degree of information asymmetry. Using a large set of news releases, we document a strong negative relationship between the sentiment of firm-specific news and CDS spreads. More importantly, consistent with the role of public news in reducing information asymmetry, we find evidence that the relation between news sentiment and CDS spreads is stronger for firms with higher information asymmetry. Furthermore, the relation is stronger for news with negative sentiment and during the 2008 financial crisis. Our results are robust to alternative sentiment measures.