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.     

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.     

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.     

The Impact of Farmland Transfers on Agricultural Investment in China: A Perspective of Transaction Cost Economics

There is growing concern that farmland transfers lead to less agricultural investment, which may adversely affect agricultural productivity growth in China. Prior research has primarily focused on the differences between owned cultivated land and rented plots, but little is known about how farmland transfers between relatives, which are popular in rural China, specifically affect agricultural investment. In this paper, we present a conceptual framework of transaction cost economics to compare different contracting strategies in China's farmland rental markets. As farmland rental markets in China are immature, land transfer between relatives establishes bilateral governance, which has the advantage of addressing the opportunistic activities of both parties and can ultimately increase investment by tenants. Based on data from two waves of household surveys, we empirically examine the impact of bilateral governance on the application of organic fertilizer, an indicator for agricultural investment. Our findings show that apart from economic factors, kinship is important to the functioning of farmland rental markets in rural areas.     

高铁时代的小城市发展——基于人口空心化的研究

高铁快速发展带来整体经济的突飞猛进,也带来小城发展变化.文章通过选取2010至2018年881个小城市的面板数据,研究高铁建设对小城发展的影响.研究发现:高铁开通可能引致部分小城人口的外流,或许加剧了部分小城人口的空心化程度.作用机制甄别结果表明,高铁通过引致消费需求外流、滞后产业结构升级和助推房价攀升途径予以实现,其中滞后产业结构升级是更为重要的传导途径.异质性分析结果表明,对不同规模的小城市而言,高铁开通可能造成人口流失的程度具有明显差异性,城区人口规模在0-20万的小城市,人口流失程度要明显低于城区人口规模在20-50万的小城市.进一步研究发现,高铁建设并未形成开通高铁小城和未通高铁小城间的经济增长差距;同时,对于开通高铁小城间的内部经济增长差距,也未得到有效验证.总之,小城应充分考虑自身区位劣势、资源禀赋和产业布局等条件,在符合高质量发展的要求下发展高铁经济.     

智能制造有利于增加企业技术创新投入吗——基于智能制造试点的准自然实验

智能制造是我国制造业转型升级的主攻方向,而如何准确客观评价智能制造的实施效果成为亟待解决的问题.从技术创新投入视角,将智能制造试点政策实施视为一次准自然实验,采用2011-2019年制造业上市企业面板数据,通过PSM-DID方法研究智能制造对企业技术创新投入的影响.研究结果表明,智能制造显著影响企业技术创新投入,即通过提升客户集成度、供应商集成度进而提高企业技术创新投入,且促进作用仅发生在民营企业和非高新技术行业中.该发现扩展了现有研究外延,同时,为解决当前国际困局和促进智能制造的持续推广提供了重要实践价值.