20世纪90年代我国婚育模式的初步分析

20世纪90年代以来,中国女性人口的平均初婚年龄平稳缓慢上升,育龄妇女平均初育年龄在波动中小幅度上升,已婚育龄妇女的平均初婚初育间隔呈波动式扩大。     

基于平均余命的中国养老金个人账户缴费率研究

平均余命是影响个人账户缴费率的重要因素之一。在退休人口平均余命逐步延长的趋势下,现行缴费率下的个人账户养老金积累额不能满足退休人口平均余命期间的支付需求,不能保障基本生活需要。如果不能及时依据平均余命适当调整个人账户缴费率,退休人口将面临因长寿风险而陷入生活贫困的境遇。本文测算了平均余命提高条件下中国2000~2050年个人账户缴费率的上限值与下限值范围,分析了职工个人缴纳养老保险费的经济承受能力,并提出了若干建议。     

关于弱化缓冲算子的研究

通过对缓冲算子的研究,构造了几何平均弱化缓冲算子GAWBO、加权平均弱化缓冲算子WAWBO、加权几何平均弱化缓冲算子WGAWBO等若干个具有普遍意义的实用弱化算子,并研究了其特性及各种弱化缓冲算子之间的内在关系,从而使序列前一部分增长(衰减)速度过快,而后一部分增长(衰减)速度过缓的冲击扰动系统数据序列在建模预测过程中常常出现的定量预测结果与定性分析结论不符的问题得到有效解决。     

物流金融中季节性存货质押融资质押率决策

物流金融创新模式下的存货质押融资业务能有效解决供应链上的资金瓶颈,具有很大发展空间,但风险控制水平的滞后严重制约了业务的成长.本文针对基于统一授信的物流金融创新模式中季节性存货质押融资业务的核心风险控制指标——质押率展开研究,首先考虑统一授信模式的特征及成本收益结构,借鉴贸易融资中“主体+债项”的风险评估思路,构建融资...     

投资者情绪、平均相关性与股市收益

Pollet和Wilson的研究认为,股市平均相关性-收益关系比股市波动-收益关系能够更好的阐述总体风险-收益关系。本文研究了投资者情绪对股市平均相关性-收益关系的影响。实证结果表明,相比于股市波动,平均相关性对股市预期收益的解释能力明显增强,并且在低情绪期,平均相关性-收益之间的关系并不显著,而在高情绪期,平均相关性-收益关系被削弱为显著的负相关关系,这表明高情绪会削弱总体风险-收益关系。这一结论在随后的稳健性检验中被证明是稳健的。     

Program Evaluation and Causal Inference With High‐Dimensional Data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data‐rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function‐valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced‐form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post‐regularization and post‐selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced‐form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment‐condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function‐valued) parameters within this general framework where any high‐quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high‐dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity‐based estimation of regression functions for function‐valued outcomes.     

A Framework to Understand Extreme Space Weather Event Probability

An extreme space weather event has the potential to disrupt or damage infrastructure systems and technologies that many societies rely on for economic and social well‐being. Space weather events occur regularly, but extreme events are less frequent, with a small number of historical examples over the last 160 years. During the past decade, published works have (1) examined the physical characteristics of the extreme historical events and (2) discussed the probability or return rate of select extreme geomagnetic disturbances, including the 1859 Carrington event. Here we present initial findings on a unified framework approach to visualize space weather event probability, using a Bayesian model average, in the context of historical extreme events. We present disturbance storm time (Dst ) probability (a proxy for geomagnetic disturbance intensity) across multiple return periods and discuss parameters of interest to policymakers and planners in the context of past extreme space weather events. We discuss the current state of these analyses, their utility to policymakers and planners, the current limitations when compared to other hazards, and several gaps that need to be filled to enhance space weather risk assessments.     

学习迁移的系统理论:PPEE理论模型的建构和意义

学习是人类社会永恒的主题。为了更好地利用过去的经验,增强学习效果,个人和组织进行学习迁移具有重要意义。学习迁移是指将在以往通过学习或解决问题所获得的经验,用于解决之后所遇到的问题。本文力图建立系统的学习迁移理论,研究人、问题、环境的因素对于学习迁移的影响。本文采用理论推导的研究方法,在前人研究的基础上,提出相应的理论模型。本文运用系统的观点,构建了学习迁移的PPEE理论模型,认为人的因素、问题的因素、人和问题的交互作用、以及环境的调节作用,会共同影响学习迁移的效果。本理论主要从五个方面论述学习迁移的机制。首先,将人的因素按照不同层面划分为后端基本能力、中端心理过程、前端知识结构,讨论了其各自对学习迁移效果的直接影响。其次,将问题的因素划分为形象相似性和抽象相似性,并根据这两个维度构建了四种问题间关系类型,并探究了其与学习迁移效果之间的关系。第三,同时考虑人的因素和问题的因素,研究了二者之间的互动对于学习迁移效果的影响。第四,将环境因素划分为时间紧迫性和空间重要性两个维度,探讨了人和环境,以及问题和环境之间的互动对学习迁移效果的影响。第五,基于系统整体的方面,研究人、问题、环境三者之间的互动对学习迁移效果的交互影响。本文还认为,该模型不仅适用于个人,也同样适用于团队、组织、地区、甚至国家和社会等各个层面,影响各个层面主体的学习迁移。本文最后总结了研究的理论和实践贡献,并提出了未来研究课题。本文对丰富学习理论、特别是学习迁移理论,以及推动教育和管理实践的发展进步具有重要的意义。     

通信原理中调制技术的四维思维空间

本文首先分析了通信原理课程中调制技术的特点,然后讨论了如何在教学实践中运用四维思维空间法。     

信息共享空间的构建与创新服务——以河北工程大学图书馆为例

信息共享空间是近几年发展起来的一种新生事物，给传统的图书馆服务模式带来了严峻的挑战，以河北工程大学图书馆信息共享空间建设为例，分析了实体层和虚拟层两个层面建设的内容，介绍了信息共享空间的创新服务，并就信息共享空间的深层次服务提出了对策建议。