Updating the Debate on Intergenerational Fairness in Pension Reform

This article examines the arguments involved in claims about the fairness or unfairness of government policies that would require current working generations to bear the full impact of their lower fertility on the costs of retirement pensions. The analysis is set in the context of a wider review of debate on the role of the idea of generational fairness in assessing options for reform under conditions of population ageing. The article considers three questions: whether generational fairness poses a serious problem for pay‐as‐you‐go pension schemes; whether it is reasonable to assess the generational fairness of pension policy in isolation from other kinds of generational transfer; and whether there is a good case for redistribution from future generations in favour of the baby boom generation.     

Some improved ratio type estimators of population mean and ratio in finite population sample surveys

In this paper we present a class of ratio type estimators of the population mean and ratio in a finite population sample surveys with without replacement simple random sampling design, where information on an auxiliary variate x positively correlated with the main variate y is available. Large sample approximations to mean square errors (MSE) of these estimatorsare evaluated and their MSE's are compared with the MSE of the usual ratio estimator [ybar]_R of [ybar] the population mean of y. It is shown that under certain conditions these estimators are more efficient than [ybar]_R. When a prior knowledge of the value of thecoefficient of variation, c_y, of y is at hand, ratio type estimator, say [ybar]₁ of [ybar] is proposed. It is shown, under certain conditions, that [ybar]₁ is more efficient than [ybar]_R. When values of c_y, c_x and the population correlation coefficient ρ is at hand, then we have proposed another estimator, say [ybar]₂ of [ybar], which is always better than [ybar]_R as far as the efficiency is concerned. In fact, is [ybar] ₂ is shown to be even better than [ybar]₁. Finally estimators better than the usual ratio estimator [ybar]/[xbar] of [Ybar] are given.     

空间城市化机制和人口城市化目标——对中国当代城市化发展的一项研究

无论从城市人口变化还是城市空间变化角度观察,以上个世纪90年代中期为界,中国的城市化都经历了两个不同的阶段。90年代中期以来的城市化是以地方政府经营土地使用权为内在动力的空间城市化过程,这一机制是由一系列土地法规催生形成的。这一城市化机制的主要问题在于:它无意于解决人口城市化中跨省市流动人口的异地城市化问题;它造成空间意义上低效率的假性城市化;更为重要的是,它造成了具有宏观影响的土地金融风险。本文基此认为,应该制定相关政策调整和规范地方政府策动的空间城市化机制,规避其产生的问题,通过激励设计促进城市化在机制与目标方面的协调。     

我国不同经济类型地区深入开展计划生育"三结合"的建议

实事求是地阐述了我国经济贫困地区、欠发达地区和较发达地区深入开展计划生育“三结合”的对策建议     

人口、经济增长对环境影响的库兹涅茨曲线分析——以昆山市为例

采用昆山市1991-2007年人口、经济相关数据,对昆山市人口、经济发展现状和环境质量进行了库兹涅茨曲线拟合分析,发现昆山市目前工业废水排放量、工业废气排放量分别与经济增长呈倒N型和正N型曲线关系,工业固体废物排放方面则不存在明显曲线,人口增长速度较快但对环境影响不明显。这说明昆山市目前已进入人口、经济增长与环境质量关系转折的关键点,转折的实现需要积极的环境政策响应。     

我国养老保险覆盖面扩大及可持续性分析

 基于我国现有政策及2020年覆盖城乡的战略目标，通过建立人口预测模型和基本养老保险收支预测模型，课题组引入相关的政策变量，对我国未来近50年基本养老保险收支及其可持续性进行预测，分析不同政策变量对于养老保险可持续性的影响，最后提出了具有针对性的政策建议。     

A Mixed Model-assisted Regression Estimator that Uses Variables Employed at the Design Stage

The Generalized regression estimator (GREG) of a finite population mean or total has been shown to be asymptotically optimal when the working linear regression model upon which it is based includes variables related to the sampling design. In this paper a regression estimator assisted by a linear mixed superpopulation model is proposed. It accounts for the extra information coming from the design in the random component of the model and saves degrees of freedom in finite sample estimation. This procedure combines the larger asymptotic efficiency of the optimal estimator and the greater finite sample stability of the GREG. Design based properties of the proposed estimator are discussed and a small simulation study is conducted to explore its finite sample performance.     

山区贫困人口与资源与环境的关系——武义县下山脱贫实践的个案剖析

近年来,随着我国经济的快速增长,社会各界日益关注山区贫困人口的生存状况,扶贫工作正在向纵深发展。本文针对山区贫困人口的贫困根源和扶贫方式,采取理论分析和实证分析相结合的方法,通过对浙江省武义县大规模的下山脱贫实践的剖析,认为山区人口贫困的导因在于当地资源和环境的制约,而当地人口与资源及环境关系的相互恶化,则是人口贫困的最终原因,因而下山脱贫是正确处理人和资源及环境关系的最佳路径。     

台湾地区失业人口特征分析

利用1992—2002年台湾地区人力资源相关数据,对台湾失业人口①状况进行了描述和分析,静态分析失业人口的绝对数量和相对构成并考察其性别、年龄和受教育程度方面表现出的特征及差异,动态分析和描述这11年来台湾失业人口的变动状况及发展趋势。认为失业问题的根本原因在于产业结构的变动,台湾当局执政角色的变化也制约了其经济发展,加剧了劳动力市场的结构性矛盾。     

A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces

Differential Evolution (DE) is a simple genetic algorithm for numerical optimization in real parameter spaces. In a statistical context one would not just want the optimum but also its uncertainty. The uncertainty distribution can be obtained by a Bayesian analysis (after specifying prior and likelihood) using Markov Chain Monte Carlo (MCMC) simulation. This paper integrates the essential ideas of DE and MCMC, resulting in Differential Evolution Markov Chain (DE-MC). DE-MC is a population MCMC algorithm, in which multiple chains are run in parallel. DE-MC solves an important problem in MCMC, namely that of choosing an appropriate scale and orientation for the jumping distribution. In DE-MC the jumps are simply a fixed multiple of the differences of two random parameter vectors that are currently in the population. The selection process of DE-MC works via the usual Metropolis ratio which defines the probability with which a proposal is accepted. In tests with known uncertainty distributions, the efficiency of DE-MC with respect to random walk Metropolis with optimal multivariate Normal jumps ranged from 68% for small population sizes to 100% for large population sizes and even to 500% for the 97.5% point of a variable from a 50-dimensional Student distribution. Two Bayesian examples illustrate the potential of DE-MC in practice. DE-MC is shown to facilitate multidimensional updates in a multi-chain “Metropolis-within-Gibbs” sampling approach. The advantage of DE-MC over conventional MCMC are simplicity, speed of calculation and convergence, even for nearly collinear parameters and multimodal densities.