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.     

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。     

Active Ageing Index in Korea – Comparison with China and EU countries

The evidence‐based policymaking relies on the use and robustness of the available data. Many conceptual and operational difficulties restrict this process, not least in making use of evidence to identify policy priorities. The Active Ageing Index (AAI), developed originally for the 28 European Union countries, offers a strong motivation in this respect. This paper reports on the development of the AAI for Korea, a country where speed and level of population aging is among the highest in the world. Drawing on the comparative analysis of the AAI results for Korea, China, and European countries, we find that Korea's AAI (35.3) is higher than the average of the AAI for all EU countries (33.9) but lower than China (37.3). Fitting Korea into the overall ranking with the EU countries and China (ranked 7), Korea is ranked 11, just behind Germany (10). The AAI results in Korea show that the employment domain performs extremely well compared with the EU countries, but other domains, especially “Social participation” and “Independent, healthy and secure living,” are achieving less favorable outcomes. High employment among the current cohorts of older workers in Korea can be attributed largely to the constraints of low pension income status.     

京津冀人口集聚对能源消费的影响

京津冀作为我国重要的人口集聚区,其区域发展面临严重的能源和环境问题。首先,基于STIRPAT模型构建京津冀面板数据模型,研究1990—2017年京津冀人口密度、经济增长、产业结构和环境规制对能源消费的影响。其次,采用SVAR模型通过脉冲响应函数和方差分解,研究京津冀人口密度变动对能源消费的作用机理和动态影响关系。结果显示,京津冀三地的人口密度、人均实际GDP与能源消费之间存在正向影响关系,其中河北省影响系数最大;北京和天津第三产业占比与能源消费之间存在反向影响关系,河北省第三产业占比对能源消费的影响不显著;北京和天津的环境规制对能源消费影响不显著,河北省环境规制对能源消费具有正向影响;京津冀地区和京冀两地人口密度变动对能源消费的影响在短期呈现负向效应,但是在中长期京津冀地区和三地人口密度变动对能源消费的影响均先上升然后缓慢下降,人口集聚具有集约用能效应。相对于能源消费自身影响而言,京津冀人口密度变动对能源消费的贡献相对较小,其影响效应有限。最后,对京津冀人口流动和能源消费一体化协同发展提出对策建议。     

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.     

老年流动人口的就医行为及影响因素研究

近年来,我国老年流动人口的规模持续上升。文章使用2015年全国流动人口动态监测调查数据,从门诊治疗和住院治疗两个方面出发,使用Logit模型和Heckman两步法检验分析老年流动人口的就医行为及其影响因素。结果显示,在患小病时,70岁及以上、以家庭其他成员收入为主要收入来源、家庭人均月收入水平较高、患有高血压或糖尿病的流动老年人选择门诊就医的可能性更高,差异有统计学意义(P<0.05)。在患需要住院治疗的疾病时,以离退休金/养老金为主要收入来源、自评身体健康的老年流动人口更有可能选择住院治疗。参加医疗保险的类型也对老年流动人口的就医行为存在着显著的影响。此外,外出务工、依靠子女和退休养老三类老年流动人口在门诊就医行为及其影响因素方面也存在显著差异。     

Young adult poverty in historical perspective: The role of policy supports and early labor market experiences

Recent research using an improved measure of poverty finds that poverty has fallen by nearly forty percent since the 1960s in the United States. But past research has not examined whether this finding holds across detailed demographic groups who might be more or less vulnerable to poverty. This paper helps fill that gap, focusing on one such vulnerable subgroup: young adults. Using the Current Population Survey, this paper examines long-term trends in young adult poverty in comparison to other groups. In contrast to almost all other groups, young adults have seen no decrease in poverty since the 1960s. We explore potential reasons for this fact, finding that young adults lack access to benefits from government programs, and are increasingly unmarried, living alone, and disconnected from the labor market, factors that leave young adults more vulnerable than other groups to poverty. The findings have implications for how antipoverty policies might assist this vulnerable group.     

Robust Bayesian prediction under a general linear-exponential posterior risk function and its application in finite population

We consider robust Bayesian prediction of a function of unobserved data based on observed data under an asymmetric loss function. Under a general linear-exponential posterior risk function, the posterior regret gamma-minimax (PRGM), conditional gamma-minimax (CGM), and most stable (MS) predictors are obtained when the prior distribution belongs to a general class of prior distributions. We use this general form to find the PRGM, CGM, and MS predictors of a general linear combination of the finite population values under LINEX loss function on the basis of two classes of priors in a normal model. Also, under the general ε-contamination class of prior distributions, the PRGM predictor of a general linear combination of the finite population values is obtained. Finally, we provide a real-life example to predict a finite population mean and compare the estimated risk and risk bias of the obtained predictors under the LINEX loss function by a simulation study.