Recently, the Chinese Government has strengthened the enforcement of bankruptcy laws to protect creditors’ rights. This study shed light on the effect of creditor protection on asset-debt maturity mismatch by employing a quasi-natural experiment in China. The results show that creditor protection mitigates maturity mismatch, and the effect is more pronounced among financially constrained firms. Results remain robust after the dynamic effects test, placebo test, propensity score matching approach, entropy balancing method, and controlling for COVID-19 shocks. Mechanism tests show that creditor protection decreases the cost of debt and reduces over-investment. The effect of creditor protection is pronounced in private companies, financially independent companies, and companies with secured loans. Creditor rights can alleviate maturity mismatch in firms with medium ownership concentration and managerial ownership levels. Economic consequences studies suggest that creditor protection reduces corporate default risk. This study reveals the mechanism and effect of creditor protection on asset-debt maturity mismatch in emerging markets, providing recommendations to policymakers for assessing and improving bankruptcy law regimes.

“How does a firm’s bankruptcy affect its regional environment?” is an open empirical question that has received little attention in the literature. We hypothesize that because enterprises provide funds to protect their regional environment, their default risk negatively impacts that environment. We analyze the impact of corporate default risk on environmental deterioration in the international setting to answer this question. Using a firm-level corporate default risk quarterly data from 2013q1 to 2020q4, we find that corporate default risk is positively associated with CO2 emissions and decomposed components. These findings are reliable in low-income and highly uncertain countries but weak in countries having more market competition. We also find that the negative impact of corporate default risk on the environment is more robust in countries with more population density and fewer forest area thresholds. Finally, using the instrumental variable approach, we provide preliminary evidence that firm-level political risk (for US and Canadian firms only) increases corporate default risk, leading to a degrading environment. Our findings are robust to alternative measurements of a firm’s default risk and environmental deterioration. Our research will help environmental authorities to consider corporate default risk as a determinant when formulating environmental-related strategies.

This study examines how firm-level exposure to the COVID-19 pandemic affects the speed of leverage adjustment among 3260 US-listed firms from 2019q1 to 2022q1. Using a novel measure of COVID-19 exposure, we find that higher exposure significantly reduces the speed at which firms adjust their leverage towards target levels. This effect is more pronounced for financially constrained firms and those operating in competitive markets. We further show that COVID-19 exposure adversely impacts corporate liquidity, default risk, and financial flexibility. Our findings highlight the role of exogenous shocks in shaping corporate financing decisions.

The level of corporate risk-taking impacts debt default as a crucial investment decision. Hence, this must be examined considering resource allocation. This study uses A-share listed companies from 2007 to 2021 as samples to empirically explore the impact and mechanism of corporate risk-taking level on debt default risk. The results show that corporate risk-taking can significantly inhibit debt default and the risk of debt default by promoting total factor productivity. Further, the higher the level of enterprise financialization of the firm, the higher the stock liquidity, and the higher the level of managerial confidence, the stronger the inhibitory effect of corporate risktaking on debt default. The heterogeneity analysis reveals that the inhibitory effect of corporate risk-taking on debt default is more significant in large-scale enterprises, enterprises with lower regulatory shareholdings, and enterprises with standard unqualified audit opinions. The study provides guidance for enterprises to improve the level of risk-taking and resource allocation efficiency effectively. Moreover, it provides empirical support for regulators to effectively prevent "waves of defaults" and even "waves of bankruptcies" in the real economy.

This paper creates default-probability-(PD)-implied credit ratings for Chinese firms following the S&P global rating standard. The domestic credit rating agency (DCRA) ratings are higher than the PD-implied ratings by ten notches on average for the identical level of default risk, implying that the domestic ratings are significantly inflated. The PD-implied ratings outperform the DCRA ratings in detecting defaults and complement the latter in predicting yield spreads. The PD-implied ratings draw information from operating efficiency-related variables; in contrast, the DCRA ratings pay attention to scale-based firm characteristics in credit risk assessment.

Over the last decade, China’s P2P lending industry has been seen as an important credit source but it has recently suffered from a wave of bankruptcies. Using 126,090 P2P loan deals from RenRen Dai, one of the biggest online P2P websites in China, this paper attempts to predict credit default probabilities for P2P lending by implementing machine-learning techniques. More specifically, thisstudy proposes a stacking ensemble machine-learning model to assess credit default risk for P2P lending platforms. A Max-Relevance and Min-Redundancy (MRMR) method is used for feature selection and then irrelevant features are eliminated by using k-means clustering method. Finally, the stacking ensemble model is performed to produce accurate and stable predictions in the feature subset. Experimental results show that stacking ensemble model yields high performance, not only in prediction accuracy but also in precision and recall. In comparison to single classifiers, the stacking ensemble machine-learning model has a minimum error rate and provides more accurate credit default risk prediction. The results also confirm the efficiency of the proposed stacking ensemble model through the area under the ROC curve.

Using the staggered introduction of regional specialized debt recovery courts as a quasi-natural experiment, we estimate the causal effect of law enforcement on financing cost of corporate bonds in China. With primary market issuing data, we show that the introduction of specialized courts reduces issuers’bond financing cost by 15%. The analysis of secondary market trading data confirms the results that the yield spreads of existing bonds reduce significantly. Exploring regional-, firm- and bond-level heterogeneity, we find the effects to be much stronger when ex-ante default risk is high. Our case-level analyses further support that enforcement cost reduction in debt dispute resolution is a channel for the reduction of cost of bond. Our paper has important policy implications in light of the recent bond default wave in China, suggesting that creditors protection through highly efficient law enforcement is important for bond market development and will eventually benefit bond issuers as well.

We investigate the impact of the geographic proximity of underwriters on bond characteristics by using corporate and enterprise bonds issued in China from 2009 to 2019. We find bonds underwritten by underwriters in close geographic proximity are associated with lower financing costs, longer maturity in high and medium credit rating firms, shorter maturity in low credit rating firms, and lower default risk. Further, we find substitution effects between the geographic proximity of underwriter and underwriter reputation, and also between the geographic proximity of underwriter and firm transparency on reducing the costs of bond financing; i.e., a better reputation of the underwriter or higher transparency of the firm will weaken geographical proximate underwriters’ effects. Our results are robust in subsamples when firms have different degrees of local government connections.

Although implicit guarantees are widely used in the shadow banking system, we know very little about its qualitative and quantitative properties. In this paper, we use a micro-level data set on China's shadow bank products to quantify the risk of implicit guarantees. We find a robust empirical fact that banks extend more implicit guarantees to their shadow bank debt (i.e., wealth management products) when their own default risks increase. Our result shows that this effect is particularly stronger when riskier banks plan to issue certificates of deposits in the interbank market. A simple model that is based on a signaling game is proposed to rationalize this fact. The key mechanism of the model is that as a bank's reputation becomes worse, it has stronger incentives to send positive signals to the market, i.e., to boost the realized returns of its shadow bank obligations, although it has no obligation to do so. Our findings show that implicit guarantees have nonlinear negative effects on bank fundamentals and the risk-weight of off-balance-sheet exposure should be increasing in banks' default risks.

We identify both dynamic and long-run relationships between each of the level, slope and curvature factors of the Treasury and corporate bond markets yield curve in China. We aim at determining which market plays a leading role in the discovery of each factor of the yield curve. We obtain three main results. First, we document for the first time the presence of a long-run relationship between the corporate and Treasury bond markets in China both for the level and the slope of their yield curve. Second, such a long-run relationship appears to be stable between the slopes over the full sample 2006-2017, but shows a break for the level factor in 2012. Third, the source market for price discovery varies with the parameters of the yield curve. While the corporate bond market is the source of price discovery for the level factor, this function is fulfilled by the government bond market for the slope parameter. The finding that the Treasury bond market is not fully dominant in level bond-pricing may not come as a surprise. Although China’s corporate bond market has developed rapidly in the past fifteen years, there were few default cases during that period. It is believed investors treat the default risk of corporate bonds as similar to that of Treasury bonds, and benefit from the high corporate spread. Our results for the slope parameter imply that market-oriented reform has progressed enough for the Treasury bond market to already provide a benchmark slope for the yield curve of corporate bonds. When the reform progresses further, we would expect corporate bonds to be priced according to their risk profile which should make the Treasury market lead in price discovery also for the level of the yield curve.