国有风险资本与企业融资约束: 如愿以偿还是事与愿违?

我国国有风险资本是否实现了设立之初的目标,即是否纾解了企业融资困难呢?文章基于上市企业微观数据和手动采集的国有风险资本数据对此进行了系统研究.实证结果稳健地显示,国有风险资本可有效缓解企业后续融资约束,我国政府参与风险投资活动是有效的.进一步地,高持股比例、多联合投资、高政治层级的国有风险资本对受资助企业融资约束的缓解作用更强;且国有风险资本对经济欠发达、低制度质量环境下的企业、面临高环境不确定性和高竞争程度企业、民营企业、成长期与动荡期企业能产生更大的影响.机制检验表明,国有风险资本既能通过认证作用显著降低企业信息不对称程度,又能发挥政治关联的资源效应,包括显著促进银企关系和企业的商业信贷获取能力,并提升企业获得政府补贴的水平,从而减轻企业资金负担,缓解其融资约束.经济后果分析表明,国有风险资本能显著降低企业外部融资的股权资金成本和债务资金成本,帮助改善企业融资贵的难题,而且国有风险资本有助于企业在创新和经营方面的良性发展.但国有风险资本并未起到有效监督作用,不能缓解企业代理问题,尤其是会导致第一类代理成本的明显提高,而高管薪酬提升是其中的重要原因.据此,文章认为在未来的国有风险资本发展中,要把握"政府角色"介入的尺度,完善国有风险资本对企业的监督管理机制.同时适当兼顾各地区发展不平衡的情况,对中西部地区的国有风险资本发展提供适当且必要的帮助,以促进国有风险资本在新时期的长足发展.     

基于Python平台通过单因子指标法进行地下水质量评价

水质评价关系到水质质量,常见的评价方法有层次分析法、综合评价法等,这些方法评价过程非常复杂,单因子评价方法相比具有操作容易.实际中单因子进行评价时存在概念理解难、计算容易出错等问题.为解决单因子计算问题,本文提出采用Python编程语言进行单因子评价.本文详细分析了Python进行单因子评价流程,从数据采集、数据清洗、数据处理、系统实现进行分析.应用结果表明基于Python编程的单因子评价方法具有评价效率高、准确度高优点.     

经济带:新发展阶段的新愿景

经济带已成为承东启西、连南贯北的"经济主骨架",在国民经济整体格局中的战略地位日益凸显,对我国经济发展具有重大战略意义.经济带的形成有其深刻的理论基础和现实条件,我国"两横"——长江经济带和陇海兰新经济带,以及"三纵"——沿海经济带、京广京哈经济带、包昆经济带五条经济带,需要进一步集聚经济要素,破除要素流动壁垒,提升节点城市能级,推动区域经济合作,以经济带建设推动我国经济高质量发展.     

Monitoring the foreign exchange rate benchmark fix

ABSTRACT

We develop a Manipulation Index (ManIx) that captures the potential manipulation intention of dealers during the World Markets/Reuters (WMR) benchmark (London Close) period at 4 pm London time through a unique algorithm and simulation. The application of this model (using a dataset with dealers’ identities) can identify banks that are prone to potential manipulative behavior. The results concerning the identified banks are validated by the regulatory investigations. Implementation of this algorithm allows regulators better direct their limited resources towards more targeted in-depth investigation.     

中国高端装备制造业自主技术创新效率稳定性及影响因素研究

在全面实施创新驱动发展战略的时代背景下，揭示中国高端装备制造业自主技术创新效率稳定性，测度相关因素的影响强度与方向，对揭示中国高端装备制造业自主技术创新规律，制定其发展策略具有重要指导意义。聚焦中国高端装备制造业自主技术创新效率稳定性及影响因素，采用DEA-Malmquist指数方法和Tobit回归模型进行实证研究，结果表明，中国高端装备制造业自主技术创新效率存在一定波动性，且各细分行业技术创新效率内部稳定性较差，产业自主技术创新效率整体稳定性不高；自主技术创新投入因素和环境影响因素对产业自主技术创新效率的影响具有较高的异质性，其中创新资金投入和人力资源投入对自主技术创新综合效率、纯技术效率及规模效率具有正向影响，而新产品开发投入和企业规模对自主技术创新综合效率、纯技术效率和规模效率的影响具有异质性，政策因素与市场因素分别具有显著和非显著负向影响，外源性创新因素具有显著正向影响，且影响强度较大。在此基础上，提出调整政府对高端装备制造业创新支持模式、加强外源性创新与智力引进等策略建议。     

Abuse of Market Dominance Under China’s Anti-Monopoly Law: The Case of Tetra Pak

Review of Industrial Organization - In this paper, we analyze a recent antitrust case of abuse of dominance that was decided by a Chinese administrative enforcement agency under China’s...     

INTERNATIONAL RESERVE MANAGEMENT: A DRIFT‐SWITCHING REFLECTED JUMP‐DIFFUSION MODEL

We study the cost of shocks, that is, jump risk, with respect to reserve management when the reserve process is formulated as a drift‐switching jump diffusion with a reflecting barrier at 0. Inspired by the Brownian drift switching model, our model results in a more realistic dynamic behavior of international reserves than the buffer stock model. The new model can capture both the jump behavior in reserve dynamics and the leptokurtic feature of the increment distribution which has a higher peak and two asymmetric heavier tails than the normal distribution. Through the selection of an initial distribution that reflects certain steady state behaviors, the reserve process becomes a regenerative process. This selection enables us to derive a closed‐form expression for the total expected discounted cost of managing reserves, thus helping us to numerically find management strategies that minimize costs. The numerical results show that shocks at the reserve level have a significant effect on reserve management strategies and that model misspecification can result in nonnegligible additional costs.     

社会地位来源对欺骗行为的影响——来自实验室实验的证据

如何减少欺骗是当前中国社会普遍面临的问题。文章结合社会地位理论和自我概念理论，研究了减少欺骗行为的机制。我们利用实验室实验，区分先赋性和自致性两种地位获取方式，用欺骗博弈来检验不同社会地位来源对欺骗决策的影响。结果发现，个人通过真实劳动获得的自致性社会地位可以显著减少欺骗行为；由于幸运得到的先赋性社会地位不能减少欺骗行为。同时，非物质收益的社会地位比赋予物质收益的社会地位更有效减少欺骗行为，说明物质收益是对市场化自我概念的提醒，从而无助于降低欺骗。研究结果在剔除策略性行为后依然稳健。研究有效验证了Mazar et al.（2008）关于影响欺骗行为的自我概念内在决定机制，并对各类组织提升诚信管理具有重要借鉴意义。     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

The Short-Selling Hypothesis of Weekend Effect and T + 1 Trading Mechanism

Asia-Pacific Financial Markets - Utilizing a difference-in-difference regression model, we conduct cross-sectional and time-series analysis to explore effect of short sales on the weekend effect in...