The finance-growth nexus: The role of banks

We contribute to the finance-growth nexus literature by showing that credit origin, bank ownership, type of credit, and bank type matter in economic growth. We use a unique dataset covering 5555 cities in Brazil, with granular information on credit characteristics. We find that non-earmarked credit to the corporate sector is associated with municipal economic growth more strongly than earmarked credit, despite the increase in the relevance of the latter after the global financial crisis. We also find that the type of credit—whether the loans are general purpose or for a specific purpose—is associated with economic growth in different ways. Overall, credit provided to the corporate sector by domestic private banks is correlated with higher economic growth rates. In contrast, the relationship between credit from state-owned banks and economic growth becomes statistically significant only after the crisis. Although we follow the finance-growth literature in our empirical exercises using internal instruments in generalized method of moments (GMM) estimations, we also conduct robustness tests using two additional external instruments: the number of complaints filed against each bank and local credit accessibility. Our findings with external instruments are the same with respect to the use of traditional internal instruments in GMM estimations.     

金融资产配置与违约风险:蓄水池效应,还是逐利效应？

本文以2007—2016年中国A股上市公司为研究对象,检验了企业金融资产配置对违约风险的影响。实证研究发现:金融资产持有量越多,企业的违约风险越低,金融资产配置的“蓄水池效应”显著;在货币政策宽松时期,金融资产配置导致的代理冲突显现,宽松的货币政策会抑制金融资产投资对违约风险的降低作用。政府规制也会有一定的公司治理作用,将产业政策纳入讨论发现:对于产业政策支持的行业来说,企业金融资产配置能够降低违约风险,但是宽松的货币政策会刺激管理层的短视投资行为,抑制政府规制的公司治理作用。进一步地,本文提出会计稳健性的提升是企业金融资产配置降低违约风险的重要路径。本文的研究结论丰富了企业金融资产配置动机和违约风险影响因素的讨论,能够为政府部门防范经济运行中的内在风险提供有益借鉴。     

委托理财导致上市公司脱实向虚吗?——基于企业创新的视角

依据2008-2017年上市公司委托理财与专利数据,本文实证研究了委托理财对企业创新的影响。研究发现随着委托理财规模与理财收益对公司业绩贡献的增加,上市公司总体上创新数量变化不明显,但创新质量却显著下降。对于不同的委托理财而言,上市公司购买银行与非银行委托理财对创新质量的影响均为负面,但对创新数量的影响却正好相反。两种类型委托理财对创新数量的影响可能相互抵消,从而导致总体上委托理财对创新数量的影响不显著。进一步研究发现,购买更多的委托理财导致上市公司更加倾向于进行风险低的开发性创新,减少风险高的探索性创新。购买银行理财的上市公司更倾向于机会主义创新,而购买非银行理财的上市公司更可能消极创新。总之,基于企业创新视角的分析发现大规模和投机性的委托理财会干扰上市公司创新行为,导致其经营"脱实向虚"。     

Real income convergence and the patterns of financial integration in the EU

We analyse real income convergence among the EU28 countries throughout 1995–2017 and the relationship with the convergence patterns of financial systems. We apply the nonlinear latent factor model of Phillips and Sul (2007, 2009) to real incomes and the IMF financial development indices for financial markets and financial institutions (Svirydzenka, 2016), and identify convergence clubs endogenously. We have several results. First, income disparities narrowed significantly over the last twenty years; yet, the growth convergence process lost momentum triggered by the global financial crisis and countries legacies shaped up asymmetries that have crystallised. Second, countries' financial systems exhibit high fragmentation, especially for financial markets, with the new EU member states at a lower financial development, confirming the existence of a two-tier Europe. Overall, the convergence patterns for real incomes and financial development are strongly correlated. Finally, the financial structure matters and market-oriented economies feature higher long-run growth, indicating the need to implement pan-European policy actions that increase the opportunities of risk diversification, enhance capital raising and channel large-scale financing to firms.     

经济开放与货币需求:国际金融风险及持币成本的测度

在中国开放经济体制下的基准货币需求模型中,本文将源于国际金融市场的持币成本设为遗漏潜变量,并构建特定的国际金融综合指数(CIFI)作为该潜变量的测度。借鉴机器学习与测度理论,本文利用对数误差修正模型提出了分步降维的CIFI构造算法,构造了长期CIFI和短期CIFI。结果表明,CIFI构造中的无监督降维步骤有助于减少高维金融数据中的冗余信息。实证分析发现,国际机会成本对中国货币需求具有规律性的前导影响,而在2007至2008年国际金融危机期间,央行的应急措施对长期CIFI所代表的非均衡冲击起到明显的阻截效果,对短期CIFI的影响基本是持续不变的。通过综合指数构造与宏观货币需求模型的算法连接,可以利用CIFI的构成结构从前导时间与影响强度两方面追踪冲击货币需求的国际金融风险的具体来源,这为宏观决策者监测国际金融市场提供了颇有规律的信息。在方法论上,本研究为如何利用模型监测国际金融市场影响宏观经济开辟了一条新路。     

Exploring the links among corporate social responsibility,reputation, and performance from a multi-dimensional perspective

This study examines the links among corporate social responsibility (CSR), reputation, and performance in hotel companies from a multidimensional perspective. Data were collected from 322 hotels in China and partial least squares equation modelling (PLS-SEM) was employed for a causal-predictive analysis. Study results reveal that CSR practices influence hotel reputation as seen from both international and local perspectives. CSR and reputation influence performance dimensions (accounting-based performance, market-based performance, and non-financial performance) differently. The research findings offer specific theoretical and practical implications for hotel managers.     

Data vs. information: Using clustering techniques to enhance stock returns forecasting

This paper explores the use of clustering models of stocks to improve both (a) the prediction of stock prices and (b) the returns of trading algorithms.We cluster stocks using k-means and several alternative distance metrics, using as features quarterly financial ratios, prices and daily returns. Then, for each cluster, we train ARIMA and LSTM forecasting models to predict the daily price of each stock in the cluster. Finally, we employ the clustering-empowered forecasting models to analyze the returns of different trading algorithms.We obtain three key results: (i) LSTM models outperform ARIMA and benchmark models, obtaining positive investment returns in several scenarios; (ii) forecasting is improved by using the additional information provided by the clustering methods, therefore selecting relevant data is an important preprocessing task in the forecasting process; (iii) using information from the whole sample of stocks deteriorates the forecasting ability of LSTM models.These results have been validated using data of 240 companies of the Russell 3000 index spanning 2017 to 2022, training and testing with different subperiods.     

How do valuations impact outcomes of asset sales with heterogeneous bidders?

Differences among bidder type-specific outcomes of asset sales are theoretically related to differences in bidders’ valuations and participation. The lead application to quantify these relations is takeover auctions: bidders are classified into strategic and financial, and bids are available. I structurally estimate valuations from all bids. The positive difference in premiums between strategic and financial acquirers is driven by the difference in dispersions of valuations (e.g., strategic bidders’ synergies are more dispersed) and the set of auction participants. The difference in average valuations is relatively unimportant. My approach can help explain outcomes of asset sales, even in settings with limited bidder data.     

基于经济新常态的长春市水资源开发利用潜力评价

以长春市为研究对象,基于未来经济处于新常态的发展态势,构建包含水资源、社会、经济、生态环境4个子系统的评价指标体系,并确定各指标的评价等级标准;基于模糊数学理论以及层次分析法构建包括目标层、准则层、指标层的3层模糊综合评价模型,以2015年为现状水平年,应用模型对长春市水资源开发利用潜力进行综合评价。结果表明:长春市水资源开发利用程度处于中等偏上水平,各辖区水资源开发利用规模不平衡,可通过产业结构调整提高全市用水效率,为经济持续增长提供保障。     

Is it U.S. GAAP or IFRS? Understanding how R&D costs affect ratio analysis

While financial reporting standards under U.S. GAAP and IFRS are fundamentally similar, differences do exist that may affect our analysis of company financial statements. This is particularly true when comparing a U.S. company following U.S. GAAP to a firm that uses IFRS. To illustrate, we compare research and development (R&D) accounting methods under both sets of standards and illustrate how they affect the analysis of financial results of firms in a specific industry—automotive manufacturers. Our results provide insight into settings in which differences in R&D accounting may have the greatest impact on financial analysis.