地方债务治理对银行信贷资金"脱虚向实"的影响——基于国务院"43号文"准自然实验的经验考察

国务院"43号文"的实施,为研究地方债务的治理效果提供了一个准自然实验场景.研究发现:地方债务治理对银行金融资产没有产生影响,但会显著增加银行总贷款、个人贷款和企业贷款,有助于银行信贷资金的"脱虚向实";地方债务治理能显著增加银行实体行业贷款,但不能显著增加银行非实体行业贷款和建筑业贷款.机制检验发现,地方债务治理可以通过降低借款人和借款企业的融资成本,间接性地影响银行信贷资金配置.进一步研究发现,国务院"43号文"实施后,资产质量高的银行倾向于增加企业贷款和实体行业贷款,资产质量低的银行倾向于增加个人贷款;银行规模可以强化地方债务治理对银行贷款增长的促进作用.因此,为促进银行信贷资金的"脱虚向实",应提高地方债务治理水平,强化对银行业务的监管与引导,加强风险管理,保障银行资产质量.     

Asymmetric Loss and the Rationality of Inflation Forecasts: Evidence from South Korea

We examine asymmetry in the loss functions of South Korean consumers' and the Bank of Korea's (BOK) inflation forecasts, and test the rationality of these forecasts under the assumption of a possible asymmetric loss function. Under an asymmetric loss function, we find evidence of asymmetry and support for rationality. We also examine whether the BOK's forecasts incorporate respective forecasts and consensus forecasts efficiently. They broadly use available information efficiently, and their results are robust to inflation‐targeting measures and the recent global financial crisis. However, our results suggest that the information efficiency of the BOK's forecasts for consumers was affected during the period 2007–2008.     

Can investors time their exposure to private equity?

Private equity performance, both for buyouts and venture capital, has been highly cyclical: periods of high fundraising have been followed by periods of low performance. Despite this seemingly predictable variation, we find modest gains, at best, to pursuing realistic, investable strategies that time capital commitments to private equity. This occurs, in part, because investors can only time their commitments to funds; they cannot time when commitments are called or when investments are exited. There is a high degree of time-series correlation in net cash flows even across commitment strategies that allocate capital in a very different manner over time.     

Go beyond tokens: Number and type both matter

Drawing upon token theory and critical mass theory, this study examines whether all female directors are equally considered as tokens. We argue that inside female directors are less likely than outside female directors to be considered as tokens because they are more powerful and influential. Using a 10-year sample of Chinese publicly listed firms on the Shanghai or Shenzhen Stock Exchanges from 2008 to 2017, we find that even one inside female director can make a significant contribution to corporate social responsibility (CSR), while outside female directors do not have a positive effect on CSR until their number reaches the critical mass (i.e., three). The results suggest that the predictions of token theory and critical mass theory vary across female director types. These findings contribute to the current literature by integrating female director typology with their numerical representation to explain their token status.     

江淮汽车成功开拓哈萨克斯坦市场的经验与启示

产能合作是当前和未来促进中哈两国经济协同发展的核心方式,江淮汽车成功进入哈萨克斯坦,对于推进两国制造业产能合作具有重要意义.充分利用国家政策、对接哈萨克斯坦汽车工业发展战略和市场需求、选择恰当国际市场进入模式和营销策略、培植核心竞争力以及积极应对哈萨克斯坦市场的激烈竞争是江淮汽车成功进入哈萨克斯坦市场的关键因素.我国企业应有效对接哈萨克斯坦经济战略,积极参与中哈产能合作;精准目标市场定位,优化产品结构;选择合适的市场进入模式,积极开展本地化生产;不断提升企业的核心竞争力.     

互联网金融规制与市场有效性改善*——来自中国网络借贷行业的证据

中国的互联网金融经历了一个先创新发展后监管规制的过程，本文通过对网络借贷行业的实证研究，分析监管规则的出台实施对新型互联网融资市场有效性的影响。实证结果表明，网络借贷平台资金的银行存管、持有ICP证等强制性规定缓解了投资者、平台企业与借款人之间的信息不对称，对克服早期平台间通过竞相承诺高回报率来吸引投资者导致的“柠檬市场”问题、对解决网贷市场上缺乏平台风险性高低有效信号的问题都起到了正向作用，有助于互联网融资市场的有效性提高。     

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.     

Crowdsourcing-based semantic relation recognition for natural language questions over RDF data

ABSTRACT

Natural language query systems over RDF data need to rely on the semantic relations in query. First, we propose the new crowdsourcing model that used to produce semantic relations dataset. The model not only inherits completeness of the iterative model and accuracy of the parallel model, but also saves human resources. Second, we mine the rules of semantic relation recognition from the correlations between dependency structures and semantic relations. Third, we propose an algorithm of semantic relation recognition for natural language query over RDF data, and experiments demonstrate that it can recognize more semantic relations than existing methods.     

Operational risk quantified with spectral risk measures: a refined closed-form approximation

The quantification of operational risk has become an important issue as a result of the new capital charges required by the Basel Capital Accord (Basel II) to cover the potential losses of this type of risk. In this paper, we investigate second-order approximation of operational risk quantified with spectral risk measures (OpSRMs) within the theory of second-order regular variation (2RV) and second-order subexponentiality. The result shows that asymptotically two cases (the fast convergence case and the slow convergence) arise depending on the range of the second-order parameter. We also show that the second-order approximation under 2RV is asymptotically equivalent to the slow convergence case. A number of Monte Carlo simulations for a range of empirically relevant frequency and severity distributions are employed to illustrate the performance of our second-order results. The simulation results indicate that our second-order approximations tend to reduce the estimation errors to a great degree, especially for the fast convergence case, and are able to capture the sub-extremal behavior of OpSRMs better than the first-order approximation. Our asymptotic results have implications for the regulation of financial institutions, and may provide further insights into the measurement and management of operational risk.