既定待遇的企业补充养老金计划的债务测算

企业补充养老金作为养老保险体系的重要组成部分,正在发挥着越来越重要的作用. 一、企业补充养老金计划的涵义 企业补充养老保险最初是由企业为提高职工的养老保险待遇水平而设立的一种补充养老计划,当时的主要目的是激励员工,它在发达国家已经有上百年的历史了.     

为“新农保制度”叫好

近日,国务院常务会议审议并原则通过《关于开展新型农村社会养老保险试点的指导意见》,接着在北京召开了全国新型农村社会养老保险试点工作会议,全面安排和部署这项工作,标志着中央又一重大惠农政策正式出台。“新农保制度”主要包括两个方面,一是实行基础养老金和个人账户养老金相结合的养老待遇,闰家财政全额支付最低标准基础养老金;二是实行个人缴费、集体补助、政府补贴相结合的筹资办法,地方财政对农民缴费实行补贴。     

延迟退休、养老金福利损失与配套政策

通过构建反映任一时点特征的终身现值精算模型，以城镇职工养老保险为例，探究延迟退休对个人养老金福利的影响。基于现实可行参数，进行模拟研究发现：第一，延迟退休的出台会导致个人养老金福利损失。相比退休制度不变，即时退休和逐步退休分别使得个人养老金净收益平均下降38.10万元和33.78万元，并使得个人养老金出现缴不抵收的局面。第二，在实行延迟退休的同时，辅之以降低缴费率和提高养老金待遇等配套性政策，可减少延迟退休带来的负面影响。当即时退休缴费率最高达到8.40%或养老金增速提高幅度最低为5.20%时，逐步退休缴费率最高达到9.34%或养老金增速提高幅度最低为3.60%时，延迟退休下的未来历年个人养老金净收益均不低于退休制度不变时未来历年个人养老金的净收益。相比单方面调整缴费率或养老金增速，降低缴费率和提高养老金增速的政策组合效应，使得个人生命周期内的养老金净收益改善情况更为显著。上述研究的政策启示在于，延迟退休与降低缴费率、提高养老金待遇等政策相配套的使用，可有效减少延迟退休政策的改革阻力。     

中国养老金体系待遇充足性的多维度评估

养老金制度的首要目标是防止老年贫困和实现一定水平的收入替代,从而养老金的“待遇充足”至关重要。本文借鉴国际上关于养老金充足性的多维度评估思路,结合中国实际,构建了中国养老金体系待遇充足性的三维度、六指标评价体系。在此基础上,基于国家统计局公开的数据以及全国综合社会调查（CGSS）提供的微观数据进行测算分析,发现我国养老金体系在收入水平、防止贫困和性别差异三个维度上的表现并不理想,各地区养老金充足性在不同时间上存在差异。进而提出我国应在不同层次养老金制度设计中强化收入替代功能、防止老年贫困和缩小性别差异等政策建议。     

我国城镇居民养老保障实证研究

面对数字庞大的老年群体,养老财政收入越来越不堪重负,飞速增长的物价也使老年人的养老金日益捉襟见肘。文章从经济学角度分析了人口老龄化背景下城镇居民的养老保障问题,提出了在养老财政支出困顿格局下养老保障的出路。     

2009年苏浙沪与全国主要经济指标比较/2010年浙江省政府十大民生实事

一、2009年浙江、江苏、上海与全国主要经济指标比较 二、2010年浙江省政府十大民生实事 就业:帮助30成名城镇失业人员实现再就业,城镇零就业家庭发现一户、解决一户;完成农民转移就业技能培训20万人. 养老和基本生活保障:新增企业职工基本养老保险参保人数70万,提高企业退休人员基本养老金待遇,提高城乡最低生活保障水平,确保符合条件的60周岁以上城乡居民按规定领取到每人每月不低于60元的基础养老金.     

非稳态下公共养老金资产负债表的编制与精算平衡调整

公共养老金资产负债表是国家资产负债表的重要组成部分,也是政府实施养老金改革的重要依据。已有研究给出了稳态下公共养老金资产负债表的编制方法,但这些方法无法直接用于非稳态情形。当前我国面临经济、人口、制度调整等非稳态环境,因此构建适应我国实际的非稳态下的公共养老金资产负债表成为重要的研究问题。非稳态下公共养老金资产负债表编制的主要难题在于缴费资产的计算。本文在梳理公共养老金资产负债表编制原理的基础上,推导出非稳态下缴费资产的计算公式,给出我国公共养老金资产负债表的编制方法和实际应用,并进一步测算分析了降低养老金待遇指数、延迟退休、提高缴费等多项改革对公共养老金资产负债表的影响。结果显示：我国公共养老金的资产负债平衡过度依赖财政补贴,无法实现缴费资产与负债的平衡。适当调整养老金待遇指数、退休年龄、缴费水平等参数,有助于恢复资产和负债的平衡,减轻制度对财政补贴的依赖。     

完善企业职工养老金政策之我见

企业职工基本养老金政策，是保障企业职工离退休后获得基本生活来源的制度。作为社会的“稳定器”和“安全网”，对于促进改革开放，稳定社会，具有非同寻常的意义。规范有序地做好养老金工作，代表着最广大人民群众的根本利益。笔者认为，保证养老金工作在平衡的轨道上运作，现阶段应从以下几方面加以改进：一、改变离退休职工养老金待遇发放标准目前，机关、事业单位离退休职工根据离退休前工资和工龄年限按一定比例发放养老金，企业单位离退休职工养老金由离退休前一年社会月平均工资的20％(基础养老金)和个人账户的一百二十分之一(个人…     

“补入口还是补出口”?——对城乡居保财政补贴模式的精算评估

政府承担城乡居民基本养老保险入口环节对个人缴费的补贴和出口环节的基础养老金。运用精算模型对城乡居保这两种财政补贴模式提高养老金待遇的效果进行评估,研究发现:在财政投入力度相同的条件下,出口补贴模式的效果优于入口补贴模式,且比较优势随个人缴费档次和基金投资收益率的提高而扩大。为提高城乡居民养老金待遇,应调整财政支出结构,控制政府在入口处对参保人缴费补贴的速度,而增加对出口处基础养老金待遇提高的速度;完善基础养老金与个人缴费档次挂钩机制;对参保人缴费实行梯度累进补贴政策;加快推进城乡居保基金委托投资步伐,提高基金投资收益率和个人账户记账利率。     

欧美国家典型养老金代际公平程度研究及其对中国的借鉴

对美国公共养老金制度、瑞典的名义缴费确定型公共养老金制度及其若干变型以及德国公共养老金制度等三种公共养老金制度的特点进行分析,使用横向公平指数比较不同养老金制度如何对待代内和代际之间的利益冲突,并利用随机模拟分析公共养老金制度如何分散由代际之间人口和经济冲击产生的风险。研究结果表明,相比其他养老金制度,瑞典名义缴费确定型养老金制度更能平滑随机波动,横向公平程度也最高。在养老金待遇方面,通过积累缓冲资产减轻养老金制度频繁调整对养老金需要的影响,这种资产积累不仅使公共养老金制度拥有更大的调整空间,而且还分散了代际风险。欧美国家典型公共养老金制度在解决代际公平程度上的做法对完善中国统账结合的公共养老金制度、消除人口老龄化产生的代际失衡关系有一定借鉴作用。     

Should responder analyses be conducted on continuous outcomes?

Continuous outcomes are often dichotomized to classify trial subjects as responders or nonresponders, with the difference in rates of response between treatment and control defined as the “responder effect.” In this article, we caution that dichotomization of continuous interval outcomes may not be best practice. Defining clinical benefit or harm for continuous interval outcomes as the difference between the means of treatment and control, that is, the “continuous treatment effect,” we examine the case where treatment and control outcomes are normally distributed and differ only in location. For this case, continuous treatment effects may be considered clinically relevant if they exceed a prespecified minimum clinically important difference. In contrast, using minimum clinically important differences as dichotomization thresholds will not ensure clinically relevant responder effects. For example, in some situations, increasing the threshold may actually relax the criterion for effectiveness by increasing the calculated responder effect. Using responder effects to quantitatively assess benefit or risk of investigational drugs for continuous interval outcomes presents interpretational challenges. In particular, when the dichotomization threshold is halfway between the treatment and control outcome means, the responder effect is at a maximum with a magnitude monotonically related to the number of standard deviations between the mean outcomes of treatment and control. Large responder effect benefits may therefore reflect clinically unimportant continuous treatment effects amplified by small standard deviations, and small responder effect risks may reflect either clinically important continuous treatment effects minimized by large standard deviations, or selection of a dichotomization threshold not providing maximum responder effect.     

Treatment effect measures under nonproportional hazards

In a clinical trial with a time-to-event endpoint the treatment effect can be measured in various ways. Under proportional hazards all reasonable measures (such as the hazard ratio and the difference in restricted mean survival time) are consistent in the following sense: Take any control group survival distribution such that the hazard rate remains above zero; if there is no benefit by any measure there is no benefit by all measures, and as the magnitude of treatment benefit increases by any measure it increases by all measures. Under nonproportional hazards, however, survival curves can cross, and the direction of the effect for any pair of measures can be inconsistent. In this paper we critically evaluate a variety of treatment effect measures in common use and identify flaws with them. In particular, we demonstrate that a treatment's benefit has two distinct and independent dimensions which can be measured by the difference in the survival rate at the end of follow-up and the difference in restricted mean survival time, and that commonly used measures do not adequately capture both dimensions. We demonstrate that a generalized hazard difference, which can be estimated by the difference in exposure-adjusted subject incidence rates, captures both dimensions, and that its inverse, the number of patient-years of follow-up that results in one fewer event (the NYNT), is an easily interpretable measure of the magnitude of clinical benefit.     

Asymptotic Normality in Mixtures of Power Series Distributions

Abstract.  The problem of estimating the individual probabilities of a discrete distribution is considered. The true distribution of the independent observations is a mixture of a family of power series distributions. First, we ensure identifiability of the mixing distribution assuming mild conditions. Next, the mixing distribution is estimated by non-parametric maximum likelihood and an estimator for individual probabilities is obtained from the corresponding marginal mixture density. We establish asymptotic normality for the estimator of individual probabilities by showing that, under certain conditions, the difference between this estimator and the empirical proportions is asymptotically negligible. Our framework includes Poisson, negative binomial and logarithmic series as well as binomial mixture models. Simulations highlight the benefit in achieving normality when using the proposed marginal mixture density approach instead of the empirical one, especially for small sample sizes and/or when interest is in the tail areas. A real data example is given to illustrate the use of the methodology.     

外商直接投资、集聚外部性与环境污染

本文在新经济地理和集聚外部性的综合理论框架下,利用2003-2013年中国275个地级市面板数据对外商直接投资、集聚外部性与环境污染之间的关系进行了实证研究。空间计量结果显示,我国城市污染排放强度存在显著的正向空间相关性,而且这种正向空间正相关性随着空间距离的增加呈现有规律的减弱趋势。在控制了FDI与集聚外部性的交互作用后,FDI引入明显降低了区域污染排放强度,Mar外部性和Jacobs外部性进一步增强了FDI的减排效应,但其影响效应随着地理距离的增加呈现出倒U型曲线特征。对于不同规模的城市而言,小城市更容易受益于专业化集聚带来的Mar外部性,大中型城市更容易分享多样化集聚带来的Jacobs外部性红利。     

Modern statistics: the myth and the magic

Summary.  The paper is a personal exploration of the puzzling contradiction between the fundamental excitement of statistics and its poor public image. It begins with the historical foundations and proceeds through the role of applications and the dramatic impact of the computer in shaping the discipline. The mismatch between the reality of statistics and its public perception arises from a number of dichotomies, some of which are explored. In particular, although statistics is perhaps typically seen as an impersonal discipline, in some sense it is very personal, and many of its applications are aimed at providing unique benefit to individuals. This benefit depends on the creation of detailed data sets describing individuals, but the contrary view is that this represents an invasion of privacy. Some observations on statistical education are made, and issues which will affect the future health of the discipline are examined.     

Measuring the Influence of Unemployment Insurance on Unemployment Experiences

This article investigates the comprehensive effects of unemployment insurance (UI) policies on the amount of time and unemployment that individuals report between jobs. The econometric model jointly determines the effects of UI on the lengths of nonemployment spells, the classification of these spells as unemployment, and the likelihood of collecting program benefits. The model carefully attempts to isolate variation in UI benefits attributable to differences in generosity across programs to avoid biases in estimating policy effects induced by other contaminating sources of benefit variation. Using data on men from the National Longitudinal Survey of Youth, the empirical results find (a) UI recipients typically experience longer spells between jobs, at least up to the exhaustion of UI benefits, and report substantially larger fractions of these spells as unemployment; (b) weekly benefit amounts exert no significant influence on the likelihood of UI recipiency, on the length of spells between jobs, or on the fraction of these spells classified as unemployment; and (c) increases in weeks of UI eligibility raise the likelihood of UI collection and lengthen the number of weeks of unemployment between jobs by inducing long spells to become longer and not by altering short-duration behavior.     

Using the Standardized Difference to Compare the Prevalence of a Binary Variable Between Two Groups in Observational Research

Researchers are increasingly using the standardized difference to compare the distribution of baseline covariates between treatment groups in observational studies. Standardized differences were initially developed in the context of comparing the mean of continuous variables between two groups. However, in medical research, many baseline covariates are dichotomous. In this article, we explore the utility and interpretation of the standardized difference for comparing the prevalence of dichotomous variables between two groups. We examined the relationship between the standardized difference, and the maximal difference in the prevalence of the binary variable between two groups, the relative risk relating the prevalence of the binary variable in one group compared to the prevalence in the other group, and the phi coefficient for measuring correlation between the treatment group and the binary variable. We found that a standardized difference of 10% (or 0.1) is equivalent to having a phi coefficient of 0.05 (indicating negligible correlation) for the correlation between treatment group and the binary variable.     

新疆经济增长与环境污染的库兹涅茨关系验证及成因分析

本文利用新疆1985—2008年新疆经济与环境数据,通过建立人均GDP与工业“三废”之间的计量模型,得到了新疆环境库兹涅茨曲线的特征,研究表明新疆经济增长与环境污染程度之间不符合典型的EKC特征,工业“三废”的环境质量改善转折点尚未到来。因此,应切实转变经济增长方式,加大治污力度,实现地区经济与环境的协调发展。     

企业职工基本养老保险、养老金替代率和人口增长率

本文在一般均衡框架内、用OLG模型分析企业职工基本养老保险制度,考察个人账户养老金替代率、社会统筹养老金替代率和人口增长率对资本劳动比、社会统筹养老金、个人账户养老金、工作期消费、退休期消费和效用的影响,求解最优的社会统筹养老金替代率。该最优替代率取决于人口增长率、个人折现率、社会折现率和资本的收入份额。模拟显示：提高个人账户养老金替代率、降低社会统筹养老金替代率和严格执行计划生育政策利多于弊;最优的社会统筹养老金替代率应随人口增长率下降而适当调低。     

Dose‐escalation strategies which use subgroup information

Dose‐escalation trials commonly assume a homogeneous trial population to identify a single recommended dose of the experimental treatment for use in future trials. Wrongly assuming a homogeneous population can lead to a diluted treatment effect. Equally, exclusion of a subgroup that could in fact benefit from the treatment can cause a beneficial treatment effect to be missed. Accounting for a potential subgroup effect (ie, difference in reaction to the treatment between subgroups) in dose‐escalation can increase the chance of finding the treatment to be efficacious in a larger patient population. A standard Bayesian model‐based method of dose‐escalation is extended to account for a subgroup effect by including covariates for subgroup membership in the dose‐toxicity model. A stratified design performs well but uses available data inefficiently and makes no inferences concerning presence of a subgroup effect. A hypothesis test could potentially rectify this problem but the small sample sizes result in a low‐powered test. As an alternative, the use of spike and slab priors for variable selection is proposed. This method continually assesses the presence of a subgroup effect, enabling efficient use of the available trial data throughout escalation and in identifying the recommended dose(s). A simulation study, based on real trial data, was conducted and this design was found to be both promising and feasible.