基于JJ检验的农村文化消费时间序列模型分析

文章利用时间序列模型对河南省农村文化消费的影响因素进行了实证分析,结果表明:收入水平、价格因素、消费结构及消费观念是影响河南省农村文化消费增长的主要因素；而农村人均社会保障及农村人均文化产业投资由于水平较低,微幅增长并不能改变农村居民的消费预期,因此,对文化消费支出的影响较小.并以此为基础,提出了相应的政策建议.     

中国人口因素对寿险需求影响的实证分析

应用双对数线性回归模型、岭回归模型对中国寿险需求进行实证分析。着重分析了人口因素对寿险需求的影响，在分析中引入了虚拟变量，并对多重共线性问题利用岭回归加以改善。研究表明：人口的城乡结构对中国寿险需求起着决定性的作用；城镇居民年人均可支配收入与寿险需求有显著的正相关性；少儿负担系数及银行实际利率与寿险需求有显著的负相关关系；受教育程度对寿险需求有显著的正面作用；而老年负担系数显示了对寿险需求正面的但不十分显著的影响。     

国外人均GNP变化对我国旅游服务出口增长的影响

改革开放以来,我国旅游服务出口贸易量迅速增长,国外人均GNP变化是影响我国旅游出口增长的重要因素.通过实证分析,得出了国外人均GNP的上升对我国旅游服务出口增长影响的大小.还分析了几个主要国家人均GNP的变化对该国居民来华旅游的影响程度.     

中国农村居民消费阶段性差异分析

文章利用H-P滤波将农村居民人均消费分为两个阶段,并通过构建VAR模型对两个阶段中国居民消费水平进行实证分析,得出两个阶段农村居民人均消费、人均收入和财富对农村居民人均消费的不同影响,最后根据实证分析结论提出相应建议.     

基于面板数据的陕西省农村居民消费结构分析

采用个体固定效应变系数模型研究陕西省农村居民消费结构。使用2005--2009年数据，对陕西省农村居民人均消费值进行实证分析。结果表明：在自发人均消费支出中，住房支出位居首位，其次是食品、医疗保健、文教娱乐项目；在人均可支配收入系数之中，低收入者的食品、居住、家庭设备系数值相对中、高收入者要大。比较而言，高收入者在衣着、医疗保健、文化娱乐上的系数值要高；在受上年度人均消费支出影响方面，食品、交通通讯支出影响不显著。     

物价变动、收入水平对我国产业结构的长短期影响

文章运用协整理论和误差修正模型对我国改革开放以来物价变动、收入水平对产业结构的长短期影响进行了实证分析,结果表明第一、二、三产业增加值占GDP的比重均与物价增长率、人均国民收入之间存在长期稳定的均衡关系,而且无论从长期还是从短期来看,物价增长率的变动和人均国民收入的变动对产业结构的调整都具有显著的影响.     

房价影响因素的灰色关联度分析

本文从供给和需求两方面科学的选取房价影响因素指标体系,引入灰色关联分析方法,对房价影响因素相对重要性进行分析。并以济南市为例,对其房价影响因素进行了实证分析,得出影响济南市房价的因素重要性依次为建材价格、土地价格、户籍人口、人均可支配收入、GDP、储蓄存款余额、房地产投资额。     

中部粮食主产区农户储粮行为的影响因素分析

文章利用湖北700个农户的调查数据,采用Tobit模型对影响农户粮食储备行为的因素进行实证分析.研究发现:地势类型对农户储粮行为具有显著影响,平原农户人均储粮量低于丘陵农户,但与山区农户无差异:距最近县城距离对农户储粮行为影响很大,距离远的农户人均储量粮更多:家庭年龄结构与经济条件对农户储粮行为无显著影响;农户粮食产出规模与农户储粮行为正相关,而粮食商品化率则与其负相关.     

中国各地区人口特征和房价波动的动态关系

本文分析了人口特征、金融市场和房地产市场三者的相互影响机制，基于2002-2015年中国大陆31个省市自治区直辖市的年度数据，建立了面板平滑转换模型，将人口密度作为异质变量构建计量模型来研究房地产市场的非线性影响因素，研究中国省市人口特征对房价波动的影响机制。实证结果表明：人均GDP对房价的影响随人口密度增加呈现非线性提升效应；人口密度小的城市房地产价格上涨比人口密度大的城市更像是“货币现象”；当人口密度较小时，地区中老年人口占比越大，房价有下降趋势，反映了房地产“年轻人推动房价上涨”的直观趋势，但是极少人口密度比较大城市例外。     

西部地区三级教育生均经费影响因素及实证分析

文章运用计量模型对中国西部地区三级教育生均经费的影响因素进行了实证分析。分析认为 :人均 GDP、人均受教育年限、二、三产业比重是影响西部各省(区 )三级教育生均经费的主要因素 ,并且它们对三级生均经费影响存在着显著的结构性差异。针对分析结果 ,提出了若干政策建议。     

Goodness-of-fit tests for additive mean residual life model under right censoring

The mean residual life (MRL) measures the remaining life expectancy and is useful in actuarial studies, biological experiments and clinical trials. To assess the covariate effect, an additive MRL regression model has been proposed in the literature. In this paper, we focus on the topic of model checking. Specifically, we develop two goodness-of-fit tests to test the additive MRL model assumption. We explore the large sample properties of the test statistics and show that both of them are based on asymptotic Gaussian processes so that resampling approaches can be applied to find the rejection regions. Simulation studies indicate that our methods work reasonably well for sample sizes ranging from 50 to 200. Two empirical data sets are analyzed to illustrate the approaches.     

The Impact of Ovarian Cancer on Life Expectancy in Japan

The purpose of this study was to determine how life expectancy is modified by ovarian cancer from 1950-2000. The contributions of ovarian cancer to life expectancy were estimated. The age characteristics of ovarian cancer were detected using the Gompertz relational mortality model. The patterns between years of potential life lost (YPLL) and mortality were obtained by fitting a linear regression equation to the natural logarithm of their ratios. YPLLs are substantially higher in Ireland than in Japan. However, the rates of change were much higher in Japan than in Ireland. YPLLs changed from 0.02 year in 1950 to 0.12 year in 2000. In Japan, there was a sixfold increase in the proportion of YPLLs for death from ovarian cancer relative to those for death from gynaecological cancers during the last half century. The impact of ovarian cancer on life expectancy clearly increased and the age-specific mortality tend to ageing.     

收入、预期寿命和社会养老保险收入再分配效应

本文在考虑职工基本养老保险典型不同缴费基数参保者寿命存在异质性的情况下，通过内部收益率的计算考察典型不同缴费基数参保者之间的养老金收入再分配效应。首先根据省级宏观截面数据估计了职工基本养老保险典型不同缴费基数参保者退休时的平均余命，再据此分别计算和比较不同参保群体的内部收益率。 研究发现职工基本养老保险制度总体上呈现微弱的正向收入再分配效应。虽然低缴费基数参保者内部收益率略高于中、高缴费基数参保职工，但其内部收益率因相对较短的寿命而大大降低。这也提醒政策制定者在研究制定延迟退休、社会养老保险全国统筹等政策时需要充分考虑参保职工内部不同群体间的平均预期寿命差别，对低收入参保者予以特别关注。     

Incidence-based estimates of life expectancy of the healthy for the UK: coherence between transition probabilities and aggregate life-tables

Summary.  Will the UK's aging population be fit and independent, or suffer from greater chronic ill health? Life expectancy of healthy people represents the expected number of years of healthy well-being that a life-table cohort would experience if age-specific rates of mortality and disability prevailed throughout the cohort's lifetime. Robust estimation of this life expectancy is thus essential for examining whether additional years of life are spent in good health and whether life expectancy is increasing faster than the decline of rates of disability. The paper examines a means of generating estimates of life expectancy for people who are healthy and unhealthy for the UK that are consistent with exogenous population mortality data. The method takes population transition matrices and adjusts these in a statistically coherent way so as to render them consistent with aggregate life-tables.     

Regional differences in life expectancy

An analysis of life tables constructed for the 49 voivodships of Poland for the years 1973-1975 and 1976-1980 is presented. The life tables have been prepared for periods of several years to avoid distortions due to data inadequacies for the smaller voivodships. The paper is in two parts: Part 2 is concerned with the major causes of death and the effect of their elimination on life expectancy.     

Semiparametric regression for restricted mean residual life under right censoring

A mean residual life function (MRLF) is the remaining life expectancy of a subject who has survived to a certain time point. In the presence of covariates, regression models are needed to study the association between the MRLFs and covariates. If the survival time tends to be too long or the tail is not observed, the restricted mean residual life must be considered. In this paper, we propose the proportional restricted mean residual life model for fitting survival data under right censoring. For inference on the model parameters, martingale estimating equations are developed, and the asymptotic properties of the proposed estimators are established. In addition, a class of goodness-of-fit test is presented to assess the adequacy of the model. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and the approach is applied to a set of real life data collected from a randomized clinical trial.     

Some results on the mean residual waiting time of records

Often, in reliability theory, risk analysis, renewal processes and actuarial studies, mean residual life function or life expectancy plays an important role in studying the conditional tail measure of lifetime data. In this paper, we introduce the notion of the mean residual waiting time of records and present some monotonic and aging properties. Sharp bounds for the mean residual waiting time of records are also investigated.     

Estimation of actuarial quantities at fractional ages with Kriging

ABSTRACT

Life tables used in life insurance are often calibrated to show the survival function of the age of death distribution at exact integer ages. Actuaries usually make fractional age assumptions (FAAs) when having to value payments that are not restricted to integer ages. Traditional FAAs have the advantage of simplicity but cannot guarantee to capture precisely the real trends of the survival functions and sometimes even result in a non intuitive overall shape of the force of mortality. In fact, an FAA is an interpolation between integer age values which are accepted as given. In this article, we introduce Kriging model, which is widely used as a metamodel for expensive simulations, to fit the survival function at integer ages, and furthermore use the precisely constructed survival function to build the force of mortality and the life expectancy. The experimental results obtained from a simulated life table (Makehamized life table) and two “real” life tables (the Chinese and US life tables) show that these actuarial quantities (survival function, force of mortality, and life expectancy) presented by Kriging model are much more accurate than those presented by commonly-used FAAs: the uniform distribution of death (UDD) assumption, the constant force assumption, and the Balducci assumption.     

The generalized exponential cure rate model with covariates

In this article, we consider a parametric survival model that is appropriate when the population of interest contains long-term survivors or immunes. The model referred to as the cure rate model was introduced by Boag 1 Boag, J. W. 1949. Maximum likelihood estimates of the proportion of patients cured by cancer therapy. J. R. Stat. Soc. Ser. B, 11: 15–53.  [Google Scholar] in terms of a mixture model that included a component representing the proportion of immunes and a distribution representing the life times of the susceptible population. We propose a cure rate model based on the generalized exponential distribution that incorporates the effects of risk factors or covariates on the probability of an individual being a long-time survivor. Maximum likelihood estimators of the model parameters are obtained using the the expectation-maximisation (EM) algorithm. A graphical method is also provided for assessing the goodness-of-fit of the model. We present an example to illustrate the fit of this model to data that examines the effects of different risk factors on relapse time for drug addicts.