基于最新统计分类标准的数字经济发展水平测度

随着信息技术的发展,数字经济已经成为经济增长的"新引擎"。但由于缺乏权威的产业统计分类标准,学者们一直面临"数字经济研究缺乏数字依据"的尴尬境地。文章基于国家统计局公布并实施的《数字经济及其核心产业统计分类(2021)》中的分类标准,对各省份统计年鉴的数据进行重新整理,利用熵权法构建数字经济发展指数,测度了我国30个省份的数字经济发展水平,分析了各省份数字经济发展的差异以及时空特征。研究发现,2009—2019年我国数字经济产业发展迅猛,各项子产业都取得了长足的进步。相比较而言,数字要素驱动业发展速度略低于其他三个子产业;数字经济发展存在着明显的区域不平衡。东中部地区的数字经济发展状况明显优于西部地区,南方优于北方,而且区域不平衡有持续扩大趋势。     

Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

The value of being precise

This study investigates how individuals assess imprecise information. We focus on two essential dimensions of decision under uncertainty, outcomes and probabilities, and their respective precision. We believe the precision of information is highly relevant in the investment setting, as reflected in the well-known “home (familiarity) bias”, and the outcome and probability dimensions, separately or jointly, may affect investors’ knowledge of uncertainty and perceived risk of the investment options, and subsequently affect investors’ choices. To test this conjecture, we conducted three experiments. Our results show that 1) participants demonstrate a pattern of preference for precision and aversion of extreme vagueness and associate vagueness with higher perceived risk and lower investment (experiments one and two); 2) participants prefer vague outcome information to vague probability information (experiment two); 3) familiarity indeed positively affects the precision of estimated values, but this association is stronger for the outcome dimension than for probabilities (experiment three). Our results confirm that precision in information, especially in the outcome dimension has an impact on investors’ resource allocation choices.     

Price bias and common practice in option pricing

Generally, the semiclosed-form option pricing formula for complex financial models depends on unobservable factors such as stochastic volatility and jump intensity. A popular practice is to use an estimate of these latent factors to compute the option price. However, in many situations this plug-and-play approximation does not yield the appropriate price. This article examines this bias and quantifies its impacts. We decompose the bias into terms that are related to the bias on the unobservable factors and to the precision of their point estimators. The approximated price is found to be highly biased when only the history of the stock price is used to recover the latent states. This bias is corrected when option prices are added to the sample used to recover the states' best estimate. We also show numerically that such a bias is propagated on calibrated parameters, leading to erroneous values. The Canadian Journal of Statistics 48: 8–35; 2020 © 2019 Statistical Society of Canada     

Heteroscedastic Global Tests that the Regression Parameters for Two or More Independent Groups are Identical

Simulation results are reported on methods that allow both within group and between group heteroscedasticity when testing the hypothesis that independent groups have identical regression parameters. The methods are based on a combination of extant techniques, but their finite-sample properties have not been studied. Included are results on the impact of removing all leverage points or just bad leverage points. The method used to identify leverage points can be important and can improve control over the Type I error probability. Results are illustrated using data from the Well Elderly II study.     

Applying kaizen to the schedule in a concurrent environment

Not only ETO (Engineering to Order), but even serial production industry should know how to deal with projects and their schedule: plant commissioning, shutdown, introducing new products and similar circumstances should be managed with adequate planning and resource allocation techniques to create a schedule useful in decision making during the execution. The current complex reality, with evolving technologies and fierce pressure to reach the market as soon as possible, pushes the project managers to use more advanced techniques than waterfall planning, such as agile or lean. It also requires them to take a holistic view and manage concurrent tasks in complex projects. The contributions of this paper are two: the proposal to control specific parallel groups of waterfall activities under uncertain environments, which can lead to iterations and reworks, as a single concurrent Activity Managed by Kanban Methods (AMKM). This activity can be subsequently embedded into traditional scheduling approaches as CPM-PERT. The second contribution is the feasibility of its application in industrial environments due to the affordability of simulation software. Two use cases are shown as evidence. It is not a disruptive proposal, but a kaizen action based on very mature technologies. Finally, it is suggested some improvements to be implemented in Project Management Software due to this ‘kaizen’ proposal.     

双波长比值法测定水杨酸、间苯二酚、对氨基苯甲酸的含量

依据水杨酸、间苯二酚、对氨基苯甲酸三组分的比值光谱特征,以对氨基苯甲酸为干扰组分,选择241nm、278nm作为测定水杨酸的波长;以水杨酸作为干扰组分,选择214nm、240nm作为测定间苯二酚的波长;以间苯二酚作为干扰组分,选择222nm、279nm作为测定对氨基苯甲酸的波长.结果显示,水杨酸浓度在1~80mg/L,基本二酚浓度在0.8~40mg/L,对氨基苯甲酸浓度在0.4~40mg/L范围内具有良好的线性关系.本方法具有测定波长少,光谱分离能力强、计算简单、能在低档分光光度计上实现、易于推广等特点.     

Visualization of generalized mean estimators using auxiliary information in survey sampling

Abstract

The mean estimators with ratio depend on multiple auxiliary variables and unknown parameters in a finite population setting. We propose a new generalized approach with matrices for modeling the mutivariate mean estimators with two auxiliary variables. Our approach brings naturally a graphical analysis for comparing mean estimators.     

市场分割、政企关系与异地市场拓展

中国的市场仍旧存在某种程度的分割，如何突破这种市场分割到异地拓展市场是企业要考虑的现实问题。以前的研究主要是从省级层面或国家层面进行宏观分析。文章创新地从政企关系视角入手来考察市场分割情形下微观层面的企业异地市场拓展，也是首先把市场分割（和异地市场）分为省内（本市外）市场、省外市场和海外市场三个不同层面来研究的论文。用世界银行的调查数据从微观企业个体层面检验了企业异地市场拓展的可能。实证研究结果发现，市场分割确实阻碍了企业异地市场拓展，但这仅限于省内市场而不是省外市场。此外，市场分割是有方向性的，从地方保护主义严重的市场里走出来的企业更容易拓展异地市场，但此结论仅适用于国内市场拓展而不适用于海外市场拓展。良好的政企关系是有利于企业异地市场拓展的，但仅限于省外市场，对省内市场以及海外市场是无效的。文章解释了其中的原因，并分析了对于企业实践的启示。