劳动力转移对城乡居民收入差距的非线性影响研究

借鉴已有相关研究成果,将劳动力转移、农业技术水平与城乡居民收入差距联系起来思考,可以具体地考察劳动力转移对城乡居民收入差距的影响.文章以农业技术水平作为门槛变量,选取2009—2019年中国31个省份的面板数据,利用泰尔指数测定城乡收入差距,以劳动力转移作为核心解释变量构建面板门槛模型,实证得出劳动力转移对城乡居民收入差距的非线性影响.研究发现:劳动力转移可以缩小城乡居民收入差距,且该影响具有单一门槛效应.在农业技术水平较低时,劳动力转移对城乡居民收入差距收敛效应较小;当农业技术水平越过门槛值达到较高水平后,劳动力转移对缩小城乡居民收入差距的效果几乎增加了一倍.此后,通过替换解释变量泰尔指数为城乡人均可支配收入比、替换核心解释变量农业技术水平为农业生产效率重新建立面板门槛模型,发现上述结论仍然成立,其检验结果具有较强的稳健性.文章将农业技术进步、劳动力转移、城乡居民收入差距这三个重要变量纳入同一模型框架中,在加深劳动力流动影响城乡居民收入差距这一视角的研究的同时,对缩小城乡居民收入差距政策的制定提供了重要的参考意义.     

Rényi entropy of m-generalized order statistics

Abstract

Characterizing relations via Rényi entropy of m-generalized order statistics are considered along with examples and related stochastic orderings. Previous results for common order statistics are included.     

Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

Cognitive abilities,self-efficacy,and financial behavior

This paper investigates the effect of cognitive abilities on financial behavior among older adults. Using the U.S. Health and Retirement Study, I find that cognitive abilities significantly affect financial behavior through two channels: ability and self-efficacy. People with higher cognition scores achieve better financial outcomes. This positive association is especially strong in tasks having high demand of cognitive abilities, which confirms the ability channel of the cognitive ability effect. In addition, there is evidence for the self-efficacy channel as a secondary source of cognitive influence. Lower cognitive abilities decrease people’s sense of self-efficacy, which, in turn, significantly decreases financial management efficiency. The findings have important policy implications, specifically that more effort is needed to assist the growing older population through the cognitive aging process and that noncognitive skills, as a secondary source of influence, also warrant attention.     

农村互助型社会养老:中国特色与发展路径

农村互助型社会养老是具有中国特色的社会养老的发展形式，是对农村传统家庭养老的重要补充。它扎根于农村传统的亲邻互助网络，其本质在于经济互助，表现为有组织地发动邻里、志愿等社会力量，充分利用以老年人为主的各类人力资源的闲置时间、资源低成本地相互帮助和服务。社会各界应将其作为重要实施方略，纳入积极应对人口老龄化战略和乡村振兴战略之中。其发展路径可以概括为：以资金互助为基础，以组织动员为抓手，以服务互助为重点，以社区居家养老为主要阵地，创新各类互助养老模式，着力形成稳定多元的资金来源，培育互助队伍，增加互助内容，从无偿到无偿、低偿相结合，探索建立标准规范的服务管理评估制度，机构养老与社区居家养老互联互通，最终尝试建立圈层化、整合化、网络化、制度化的农村互助型社会养老体系。     

Does a universal non-contributory social pension make sense for rural China?

China’s pension reform during the past three decades has allowed a majority of China’s population to be covered by a pension scheme. Of particular note has been the New Rural Pension Scheme (NRPS), a voluntary programme introduced starting in 2009. One goal of our analysis is to assess that pension scheme, using a variety of sources of information including data drawn from recent (2013 and 2015) nationwide China Health and Retirement Longitudinal Surveys (CHARLS). Our analysis involves an exploration of differences between the generosity and structure of the NRPS and other pension schemes currently in place. We also explore the feasibility of reforming the current “quasi-social pension” component of the NRPS by substituting a universal non-contributory social pension pillar. In connection with our assessment of the NRPS, we note the unusually low benefit levels for rural China.     

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp-optimization

The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail L^p-medians encompassing the MS and CTE. For p in (1,2), a tail L^p-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data.     

中国当代人口发展分析

以人为本的科学发展观必然要求我们在一切发展序列中首先关注人口发展,中国人口发展在中国社会发展框架中具有绝对优先的工具价值和目的意义.中国作为发展中国家与作为人口最多的国家两者之间在很大程度上具有互为因果的内在关系,充分认识中国人口发展现状具有多元化的重要意义.中国人口发展状况主要表现为人口数量多、人口质量低和人口结构不合理.中国人口现代化是中国其它现代化的强力引擎,中国人口发展的基本创新路径是城市化发展路径、市场化发展路径、民主化发展路径.     

Ethnicity, migration and health: A population-based study of 338 refugees from Latin America, 396 nonrefugee immigrants from Finland and 161 from southern Europe and 996 age-, sex- and education-matched controls from Sweden

This article shows the influence of being a refugee from Latin America or a nonrefugee immigrant from southern Europe or Finland on self-reported illness, controlling for social factors and lifestyle. The study population consisted of 338 Latin American refugees, a random sample of 396 Finnish and 161 southern European immigrants and 996 age-, sex- and education-matched Swedish controls. The data were analysed unmatched with logistic regression (multivariate analysis) in main effect models. The strongest independent risk indicator for long-term illness was being a Latin American refugee (estimated odds ratio (OR)=2.96, 95% confidence interval (CI)=2.19–3.82). There was a significant association between being a Latin American refugee and period prevalence, ill health and unsatisfied need for care. Being a southern European or Finnish immigrant was a risk indicator of ill health but was not associated with the other dependent factors. Not feeling secure in daily life was a strong risk indicator for long-term illness and ill health (estimated OR=1.89, 95% CI=1.26–2.76 and OR=3.04, 95% CI= 1.97–4.48) respectively). Being a Latin American refugee was equal in importance to traditional risk factors such as overweight and not taking regular exercise for long-term illness and ill health.     

Modelling daily multivariate pollutant data at multiple sites

Summary. This paper considers the spatiotemporal modelling of four pollutants measured daily at eight monitoring sites in London over a 4-year period. Such multiple-pollutant data sets measured over time at multiple sites within a region of interest are typical. Here, the modelling was carried out to provide the exposure for a study investigating the health effects of air pollution. Alternative objectives include the design problem of the positioning of a new monitoring site, or for regulatory purposes to determine whether environmental standards are being met. In general, analyses are hampered by missing data due, for example, to a particular pollutant not being measured at a site, a monitor being inactive by design (e.g. a 6-day monitoring schedule) or because of an unreliable or faulty monitor. Data of this type are modelled here within a dynamic linear modelling framework, in which the dependences across time, space and pollutants are exploited. Throughout the approach is Bayesian, with implementation via Markov chain Monte Carlo sampling.