An agent-based multiattribute reverse auction approach for online secondhand commodities

Due to the price elasticity of demand for secondhand commodities, it is difficult to establish a quantitative model for the auction. This paper proposes an agent-based multiattribute reverse auction model to support multicommodity combinatorial auction. First, this paper establishes an agent-based reverse auction model and introduces the framework, procedures, and protocols of the model in detail. Second, in light of the multicommodity environment, the targets, protocols, auction strategies, and approaches are identified. Finally, by using the proposed agent-based auction model, both buyers and sellers will reach simultaneous agreements on the details of the commodities to complete the auction.     

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。     

A Machine Learning Analysis of the Recent Environmental and Resource Economics Literature

We use topic modeling to study research articles in environmental and resource economics journals in the period 2000–2019. Topic modeling based on machine learning allows us to identify and track latent topics in the literature over time and across journals, and further to study the role of different journals in different topics and the changing emphasis on topics in different journals. The most prevalent topics in environmental and resource economics research in this period are growth and sustainable development and theory and methodology. Topics on climate change and energy economics have emerged with the strongest upward trends. When we look at our results across journals, we see that journals have different topical profiles and that many topics mainly appear in one or a few selected journals. Further investigation reveal latent semantic structures across research themes that only the insider would be aware.

     

技术创业型企业孵化资本投入的风险管控——来自多案例对比

待孵化的技术创业型企业同时具有概念性技术向差异化产品转化的高风险与产品异质性被认同后溢价评估的高收益特点，导致其投资者多处于隔岸观火却欲罢不能的的孵化投资矛盾中。对孵化资本实施有效的风险管控，成为吸引外部资本投入的关键。基于此，选择在可创概念选育与技术创业孵化领域探索出高成功率路径的概念证明中心、YCombinator和创新工场为研究案例，分析其在创业项目筛选、孵化资金运营等关键环节的风险管控方式，以期完善我国孵化资本管控理论、助力我国商业孵化器提高资金风险管控能力、促进外部资本投入。     

Can Shareholders Be at Rest after Adopting Clawback Provisions? Evidence from Stock Price Crash Risk

Using a propensity score matched sample and a difference‐in‐differences research design, we find that stock price crash risk increases after a firm voluntarily incorporates clawback provisions in executive officers' compensation contracts. This heightened crash risk is concentrated in adopters that increase upward real activities‐based earnings management and those that reduce the readability of 10‐K reports. Based on cross‐sectional analyses, we also find that the increased crash risk is more pronounced for adopters with high ex ante fraud risk, low‐ability managers, high CEO equity incentives, and low dedicated institutional ownership. Collectively, our results suggest that the clawback adoption per se does not curb managerial opportunism but rather induces managers to use alternative channels for concealing bad news, which may contribute to a greater stock price crash risk; and the increase in crash risk is more likely in cases where incentives are strong or monitoring is weak. Our results should be of interest to regulators and policymakers considering the effects of clawback adoption on the investing public.     

两家单位成功创建“全国为侨公共服务体系示范单位”

正市政府外事侨务办组织市、区两级验收组,对沙坪坝区渝碚路街道和大渡口区春晖路街道阳光社区创建2017年度"全国为侨公共服务体系示范单位"进行验收并组织授牌,最终两家单位以优异成绩荣获此项"国字号"荣誉。市政府外事侨务办副主任杨大庆出席有关活动。国务院侨办2017年首次设立"全国为侨公共服务体系示范单位"创建活动,得到市政府外事侨务办积极响应,通过完善各项工作步骤,确保创建对象工作基础扎实、侨务资源集中、     

中国农药施用与农业经济增长脱钩状态：时空特征与影响因素

[目的]明确农药施用与农业经济增长关联状态及其影响因素,为实现"控药减害增收"的目标提供借鉴。[方法]基于2005—2015年数据利用脱钩理论和对数平均分解指数法分解进行分析。[结果]中国农业经济增长伴生大量农药施用,仅少数省域表现出农药施用和农业经济增长扩张绝对脱钩的理想状态,东北西北部分省域农业经济增长则以更大幅度的农药投入增长为代价。中西部地区劳动力规模和技术进步效应是推动农药施用与农业经济增长脱钩的因素;东部地区种植规模变化、劳动力规模和技术进步因素均是推动农药施用和农业经济增长脱钩的因素;东北地区仅劳动力规模效应成为推动脱钩的力量。[结论]推动农药施用与农业经济增长脱钩需要强化农业科技的创新与普及,完善农业生产过程中的技术支撑,推动农业病虫害监测预警,加大对环境友好型低污染农药和肥料的推广度;构建农户施药的多重约束机制,完善农业病虫灾害保险减少农户对生产过程的风险感知,发挥农业合作社对农户施药行为的规制作用,完善产品分级认证和安全准入制度;通过农地合理流转和农业机械化等方式集约利用农业生产资源;因地制宜推动农药施用与农业经济增长脱钩,结合区域资源优势和农业发展阶段有针对性地设计对策措施。     

一览

正中意投资促进中心项目在两江新区正式启动3月28日,由意大利驻重庆总领事馆、两江新区管委会和中国意大利商会,三方共同组建的中意投资促进中心项目在重庆正式启动,举行了签约仪式。这是意大利和重庆两江新区的首个联合项目。中国意大利商会主席大卫·古奇诺、意大利驻重庆总领事倪飞、市政府外事侨务办副     

Do Cryptocurrencies Increase the Systemic Risk of the Global Financial Market?

The advance of cryptocurrencies has sparked wide concern over their interplay with the existing global financial market. This paper analyzes the risk spillover relation between cryptocurrencies and major financial assets, and unravels how cryptocurrencies could influence global financial systemic risk. We find that cryptocurrencies function as a separate risk source from traditional assets. Major legislative, financial and technological events in the cryptocurrency market may affect risk spillover dynamics. Although the overall penetration of cryptocurrencies is not yet deep, introducing cryptocurrency can significantly increase the systemic risk to traditional markets during low risk level episodes.     

Improving forecasting performance using covariate-dependent copula models

Copulas provide an attractive approach to the construction of multivariate distributions with flexible marginal distributions and different forms of dependences. Of particular importance in many areas is the possibility of forecasting the tail-dependences explicitly. Most of the available approaches are only able to estimate tail-dependences and correlations via nuisance parameters, and cannot be used for either interpretation or forecasting. We propose a general Bayesian approach for modeling and forecasting tail-dependences and correlations as explicit functions of covariates, with the aim of improving the copula forecasting performance. The proposed covariate-dependent copula model also allows for Bayesian variable selection from among the covariates of the marginal models, as well as the copula density. The copulas that we study include the Joe-Clayton copula, the Clayton copula, the Gumbel copula and the Student’s $t$-copula. Posterior inference is carried out using an efficient MCMC simulation method. Our approach is applied to both simulated data and the S&P 100 and S&P 600 stock indices. The forecasting performance of the proposed approach is compared with those of other modeling strategies based on log predictive scores. A value-at-risk evaluation is also performed for the model comparisons.