Does corporate social responsibility reduce financial distress risk?

This paper examines how corporate social responsibility (CSR) affects the level of financial distress risk (FDR). Using a sample of 1201 US-listed firms during 1991–2012, our results indicate that firms with higher CSR levels have lower FDR, suggesting that a better CSR performance makes firms more creditworthy and have better access to financing, which is rewarded with less financial defaults. This finding is robust to using alternative proxies of FDR, to controlling for potential endogeneity, and is mainly driven by the community, diversity, employee relations, and environmental dimensions of CSR. Moreover, this relationship is more prevalent in firms with strong governance mechanisms and high product market competition. It is also more exacerbated for less distressed firms and during non-crisis periods. Overall, our findings suggest that the adoption of CSR practices comes with less distress and default risks, likely leading to a more attractive corporate environment, better financial stability and more crisis-resilient economies.     

Threshold effect of economic openness on bank risk-taking: Evidence from emerging markets

This paper investigates the non-linear effects of two aspects of economic openness, namely, trade openness and financial openness, on banking system stability. We use a panel of 42 emerging markets from 2000 to 2014 to test whether bank risk-taking behaviour varies with the level of openness. We find that a higher degree of trade openness promotes bank stability linearly. Conversely, the non-linear effect of financial openness on bank risk-taking is evident. When the financial system is not sufficiently open, the impact of financial openness on bank stability is insignificant. However, as the domestic financial market becomes more open, financial openness can help discipline the behaviour of banks, making them more stable. We also find evidence that these effects are transmitted through the market discipline channel. Our findings highlight the importance of strengthening the domestic regulatory framework and transparency as the economy becomes more integrated.     

Do mutual fund flows affect the French corporate bond market?

We study whether investors’ withdrawals from mutual funds affect corporate bond prices. As mutual funds have become major players in the financial markets, they are likely to exert downward pressures on asset prices when facing investors’ redemptions, particularly in the less liquid markets such as corporate bonds. We use a novel dataset on the French bond funds and show that both flows in and out of mutual funds lead to a significant effect on the corporate bond yields. This effect is asymmetric as redemptions provoke a change in yields of greater magnitude than inflows. Moreover, all corporate bonds are not equally affected by investors’ withdrawals from funds: The more a bond is detained by funds, the higher the impact of redemptions on its yield. These three results are robust to various changes in econometric specifications.     

Price connectedness between green bond and financial markets

We study price connectedness between the green bond and financial markets using a structural vector autoregressive (VAR) model that captures direct and indirect transmission of financial shocks across markets. Using heteroskedasticity to identify the structural VAR model parameters, our empirical findings reveal that the green bond market is closely linked to the fixed-income and currency markets, receiving sizeable price spillovers from those markets and transmitting negligible reverse effects. We also show that, in contrast, the green bond market is weakly tied to the stock, energy and high-yield corporate bond markets. These findings have implications in terms of portfolio and risk management decisions for environmentally aware investors holding positions in green bonds.     

Credit constraints and productivity of SMEs: Evidence from Canada

To what extent firms are constrained by external credit is usually unobserved in commonly used firm-level data. We use a survey of financing among Canadian small and medium-sized enterprises to measure the likelihood of a firm being constrained by credit. We find that firm size, current debt-to-asset ratio and cash flow are robust indicators of being financially constrained, while long-term debt to asset ratio is not a significant indicator of credit constraints. We then estimate the firm-level total factor productivity, taking into account the measured credit constraints. Omitting credit constraints leads to an upward bias of productivity estimates, by 4 percent. In addition, we find no strong evidence that suggests credit constraints lead to slower productivity growth. Finally, we confirm that both investment and employment growth are negatively affected by the measured credit constraints.     

盐城市水资源承载状态预警研究

在分析水资源承载状态预警概念的基础上,引入"三类六级"预警思想,采用可变模糊法和层次分析法的思想,构建盐城市水资源承载状态综合预警指标体系,评价盐城市2015年、2020年和2030年的水资源承载状态,并结合各年份承载状态变化趋势,对未来年份进行预警。结果表明:盐城市2015年水资源处于临界超载的状态,但随着"关于做好建立全国水资源承载能力监测预警机制工作的通知"等一系列措施的实施,2020年、2030年承载状态将逐步好转,到2030年将处于可载的状态。     

Financial development,economic growth and convergence clubs

To study the role of financial development in economic growth, we apply an array of convergence tests designed to capture nonlinear transitional dynamics to real outputs per capita. Strong evidence of multiple convergence clubs is observed, implying that the clubs are formed based on the initial level of real output per capita and average growth rate. Our empirical results show that the stage of economic growth of each country plays an important role for the composition of the convergence clubs. Furthermore, financial development emerges to be a significant determinant, albeit plays differently in the economic growth of each convergence club.     

Incorporating textual information in customer churn prediction models based on a convolutional neural network

This study investigates the value added by incorporating textual data into customer churn prediction (CCP) models. It extends the previous literature by benchmarking convolutional neural networks (CNNs) against current best practices for analyzing textual data in CCP, and, using real life data from a European financial services provider, validates a framework that explains how textual data can be incorporated in a predictive model. First, the results confirm previous research showing that the inclusion of textual data in a CCP model improves its predictive performance. Second, CNNs outperform current best practices for text mining in CCP. Third, textual data are an important source of data for CCP, but unstructured textual data alone cannot create churn prediction models that are competitive with models that use traditional structured data. A calculation of the additional profit obtained from a customer retention campaign through the inclusion of textual information can be used by practitioners directly to help them make more informed decisions on whether to invest in text mining.     

Does more finance mean more inequality in times of crisis?

Many recent empirical studies show that both banking crises and financial development (FD) play an important role in understanding the dynamics of income inequality (IncI) over the last decades. However, so far no study has investigated the role of FD in the amplification of IncI following banking crises. This paper seeks to address this issue based on a sample of 69 banking crises in 54 countries over the 1977–2013 period. Our analysis suggests that FD is associated with a significant increase in IncI in the aftermath of banking crises. This result is robust to a broad range of alternative specifications and is unaffected by various potential sources of endogeneity. We also show that the relationship between FD and the redistributive consequences of banking crises is not subject to a threshold effect and is stronger for developing countries.     

三线城市社区商业业态现状及对策研究——以湖州市为例

社区商业以社区内居民为主要服务对象,以满足居民基本生活及多样化消费需求为主要目的。论文以三线城市浙江省湖州市为例,通过现场访谈与问卷调研,明确湖州市中心城区社区商业业态现状与主要存在的问题。借鉴长三角地区典型成功社区商业运营模式和操作流程,从核心理念、业态配比、品牌构建与商圈融合四个方面提出构建科学合理的湖州市社区商业业态的相关建议。