Chief Audit Executive as Supervisory Board Member and Executive Compensation Contracts

This paper studies a unique phenomenon in China's corporate governance—that chief audit executives (CAEs) sit on supervisory boards (CAE duality)—and examines its effects on executive compensation contracts. Using a sample of listed firms between 2010 and 2018, we find a significant positive relation between CAE duality and pay-for-performance sensitivity, which suggests that the dual position helps integrate monitoring resources and reduces agency costs. This positive relation is more pronounced when companies face a stricter monitoring environment and in non-state-owned enterprises (non-SOEs) than in SOEs. In addition, we find that the recent reforms on compensation strengthen the role of CAE duality in SOEs. Further analysis identifies the reliability of performance information (i.e., earnings quality) and reduced executive self-interested behaviours (i.e., perquisite consumption) as the influencing mechanisms that increase the demand for performance-based compensation and thus improve pay-for-performance sensitivity.     

The Benefit of Frequent Corporate Philanthropy

Applying behavioural economic theory, we argue that the frequency of philanthropic activity is important in determining corporate philanthropy's economic outcome. Using Chinese data from 2003 to 2016, we find that firms with more frequent philanthropic activities obtain more government subsidies than firms that only engage in one-off charitable donations. Firms with better corporate governance, such as higher management ownership and more independent directors, are more likely to adopt a strategy of frequent donation. Furthermore, firms are more likely to be frequent donors when management or local government officers have a long tenure. Our findings provide insight into the giving process and suggest that firms can maximize the benefit of corporate philanthropy if they strategically consider the donation frequency and donation amount simultaneously.     

我国大麦价格波动特征及其影响因素分析

[目的]大麦价格剧烈波动会直接影响大麦种植户的生产积极性和大麦产业的平稳发展,研究大麦价格波动特征及其影响因素,有助于提升大麦产业链相关主体识别和应对市场风险的能力,促进大麦产业的健康发展。[方法]文章先采用HP滤波法和ARCH类模型分析了2011年4月至2017年2月我国大麦价格波动特征,然后采用脉冲响应函数分析了我国大麦价格波动影响因素。[结果]我国大麦价格波动存在明显的季节性和周期性,样本期内总体上呈现逐渐下降趋势;我国大麦价格具有显著的波动集聚性,我国大麦价格具有显著的不对称性;在该文选择的影响因素中,大麦进口量和国际大麦价格是影响我国大麦价格波动的主要因素。[结论]该文提出必须保障并提高国内大麦合理产能、完善大麦价格监测预警体系、加强国内大麦进口企业整合和推动大麦进口来源多元化的政策建议。     

Move fast,travel slow: the influence of high-speed rail on tourism in Taiwan

High-speed rail (HSR) and tourism are closely related economic activities because improved mobility is perceived to facilitate tourist behavioral changes. This study examines the influence of HSR on the travel patterns of individual tourists in Taiwan in relation to time, space and carbon emissions. A framework is first provided to discuss how changes in the speed of intercity transportation will affect visitors’ choice of the journey, behavior at destinations and trip quality. In addition, HSR is expected to influence five general aspects of travel decisions relating to mobility and trip emissions, including mode selection, travel distance, length of stay per trip, annual travel frequency and total travel days. In the example of Taiwan, information by onsite sampling of 400 domestic travelers found that HSR had a weak influence on travel distance and length of stay per trip, but was observed to facilitate extended time at each stop, a deeper engagement with the locality, and an approximate 10% reduction in transport carbon emissions through intermodal substitution. These phenomena are in line with the slow travel concept of sustainable tourism consumption.     

Predicting credit card delinquencies: An application of deep neural networks

The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus.     

水源地突发水污染政府应急预留水量需求预测

近年来,随着工业化和产业化的快速发展,水源地突发水污染事件频发。为应对紧急情况下的水资源非常规需求,保障经济社会稳定发展,政府需要安排一部分应急预留水量。如何合理预测政府应急预留水量的规模是一个值得探讨的课题。提出了一种基于案例推理技术的政府应急预留水量需求预测方法,具体思路是:借助于案例库,利用主成分分析法从众多影响水源地突发水污染事件的因素中提取出两两不相关的因子,以此作为案例的特征属性,基于加权曼哈顿距离测算相似度,依此得到匹配案例,进而测算政府应急预留水量。以太湖流域常州地区水源地为例,进行政府预留水量需求量的预测与分析。该方法可以为政府应急预留水量的配置、储备等提供相关理论知识。     

Strategic entry or strategic exit? International presence by emerging economy enterprises

By proposing an integrated strategic choice framework, we theorize the distinctive dynamics of international expansion by emerging economy enterprises. Specifically, we explicate how these firms build international presence based on combined strategic entry (i.e., prompted by internal capabilities such as innovation and diversification) and strategic exit (i.e., pushed out by external handicaps at home such as institutional obstacles and market competition). Further, a firm’s cooperative ties with foreign multinationals in the former’s home country fortify the strategic entry intent, while ties with home government institutions weaken the strategic exit intent. We also demonstrate that building international presence helps bolster firm performance, highlighting the economic catch-up consequence of international expansion. Analyses of a two-year imbalanced panel data of 2136 firms statistically support our hypotheses.     

我国牧区草原生态补偿机制构建研究

［目的］通过构建一套科学、合理的牧区草原生态补偿机制，解决牧区近10年来主要实施的一系列生态治理项目和措施中存在的草原生态补偿标准普遍偏低、政策缺少灵活性、监管体系不够完善、缺乏相应保障机制等问题。［方法］通过对国内有关草原生态补偿机制相关文献分类梳理，基于我国牧区草原生态环境现状，对比分析国内外实践，总结国外成功经验，定性分析补偿机制要素，对草原生态补偿机制进行全面、系统地分析论述。［结果］我国牧区草原生态补偿主体应以各级政府为主； 补偿对象应包括牧区牧民、草原生态环境保护的投资者和建设者以及牧区地方政府； 因保护草原生态环境而导致牧区和牧民的发展权受限由此产生的机会成本作为草原生态补偿标准； 补偿方式以中央财政纵向转移支付为主，以市场补偿为辅的组合模式。保障机制需完善法律法规、公众参与、监督管理、绩效评估等方面建设。［结论］我国牧区草原生态补偿机制的构建须对补偿责任主体、补偿范围、补偿标准、补偿方式及补偿保障机制等各要素要进行整体性、系统性深入分析，才能确保草原生态补偿机制能够满足牧区实际需求，提供有力保障。     

我国省级区域金融发展对经常项目的影响研究——基于货物贸易视角的分析

本文选取我国大陆31个省(市、自治区)2007年-2018年的面板数据,综合运用系统GMM和差分GMM估计方法,实证检验了沿海与内陆、沿边与非沿边、享受优惠政策高与低、金融控制强与弱等4类不同省区金融发展对经常项目余额的影响。研究结果表明:使用全部样本估计时,金融发展显著负向影响经常项目余额,这一结论经稳健性检验后依然成立。使用不同区域的子样本估计时,金融发展对沿海省区、非沿边省区、享受优惠政策高以及金融控制弱省区的经常项目余额的抑制作用较大,而在其他省区作用较小。因此,各地区应充分利用金融手段来调整进出口余额,以保证经常项目的持续平衡。     

The optimal level of corporate social responsibility based on the duopoly model

This paper constructs a duopoly model considering corporate social responsibility (CSR) and market's sensitivity to CSR (e) and analyzes the equilibrium results, the condition of CSR implementation and the optimal CSR level (β^* ) of Model CC (two enterprises implement CSR) and Model CN (only one enterprise implements CSR). The results show that β^* is affected by competitors and e. e, marginal cost (c) and cost difference affect the equilibrium results and the comparative results. Reducing c and improving e can promote social welfare. Consumer surplus under Model CC is highest. CSR has a negative effect on social welfare under certain conditions.