我国男女两性老龄人口死亡率联合建模与预测

老龄人口死亡率建模和预测是长寿风险度量和养老金风险管理的基础。在我国,退休年龄及以上老龄人口死亡数据稀少,随机波动大,构建能够捕捉老龄人口死亡率随性别、年龄和时间变动的动态预测模型成为难题。本文采用Logistic两人口死亡率模型研究我国老龄人口死亡率的建模与预测。首先,运用死亡率数据质量较好的我国台湾地区数据,对模型结构进行选择,并检验模型的稳健性和预测性能。其次,基于我国大陆地区死亡率数据对模型结构进行二次验证和选择,应用所选模型对大 陆地区老龄死亡率进行建模和预测。结果显示,对于我国男女老龄死亡率的拟合和预测,Logistic 两人口模型均优于单人口CBD模型。最后,运用Logistic两人口死亡率模型对死亡率在年龄和时间两个维度上外推和预测,计算出时期和队列老龄人口分年龄的预期余寿,为养老金精算评估和长寿风险分析提供更准确的数据支持。     

The estimation of adopted mortality and morbidity rates using model and the phase type law: the Turkish case

Abstract

This paper aims to estimate mortality rate, morbidity-mortality rates of a chronic disease utilizing phase type law in the frame of two and three state processes. The application on commonly used mortality tables in Turkey are adopted to process to estimate the future mortalities with respect to phase type distribution for the purpose of justifying. Using one absorbing state, two and three state Models calculate the time until absorbing of the death and death by phase type distribution for each gender. Consequently, the 3-state probabilities in estimating the mortality-morbidity rates of IHD for Turkish population yield a significant information on the health management and pricing health insurance products.     

Tracing studies and analysis of the effect of loss to follow-up on mortality estimation from patient registry data

Summary. Before patient registries are used for studies of the long-term mortality that is associated with chronic medical conditions, the potential bias resulting from patients who become lost to follow-up must be investigated. A study design, used for a systemic lupus erythematosus patient registry, is described. The design involves tracing patients who are defined as 'lost to follow-up' according to specific criteria. This provides supplementary information on the mortality experience of patients who are lost to (regular) follow-up. Some methods of analysis are described, based on comparing the mortality experience of patients when under regular follow-up with the experience of patients after they are deemed to be lost to follow-up. The effect of loss to follow-up, death reporting and visits to the clinic on estimation procedures is illustrated and recommendations are made for patient registries which are to be used in mortality studies.     

Regime-switching pure jump processes and applications in the valuation of mortality-linked products

In this paper, we study the pricing of longevity bonds and an insurance contract on multiple lives in a regime-switching market driven by an underlying continuous-time Markov chain. For modeling dependent mortality, we make use of a Markov chain and some shot noise processes with regime switching. By using a martingale method, we give semi-analytical expressions for the price of longevity bonds and the premium of an insurance contract on the kth person to die.     

我国农户借贷需求影响因素及差异性的实证分析

 本文以全国12个省市农户借贷需求的问卷调查为样本数据,通过建立Logistic回归模型来分析我国农户借贷需求的影响因素及其差异性。计量结果表明,影响农户借贷需求的主要因子是农户纯收入、借款利率、借款期限以及农户家所在地与金融机构的距离。进一步的,从不同地区和不同收入层次两个角度,分别建立了农户借贷需求的计量模型,进行差异化分析,并提出相应的政策含义。     

Trends in inequality in infant mortality in the north of England, 1921–1973, and their association with urban and social structure

Summary.  The paper analyses a time series of infant mortality rates in the north of England from 1921 to the early 1970s at a spatial scale that is more disaggregated than in previous studies of infant mortality trends in this period. The paper describes regression methods to obtain mortality gradients over socioeconomic indicators from the censuses of 1931, 1951, 1961 and 1971 and to assess whether there is any evidence for widening spatial inequalities in infant mortality outcomes against a background of an overall reduction in the infant mortality rate. Changes in the degree of inequality are also formally assessed by inequality measures such as the Gini and Theil indices, for which sampling densities are obtained and significant changes assessed. The analysis concerns a relatively infrequent outcome (especially towards the end of the period that is considered) and a high proportion of districts with small populations, so necessitating the use of appropriate methods for deriving indices of inequality and for regression modelling.     

Estimating confidence regions of common measures of the baseline and treatment effect on dichotomous outcome of a population

In this article, we estimate confidence regions of the common measures of (baseline, treatment effect) in observational studies, where the measure of a baseline is baseline risk or baseline odds, while the measure of a treatment effect is odds ratio, risk difference, risk ratio or attributable fraction, and where confounding is controlled in estimation of both the baseline and treatment effect. We use only one logistic model to generate approximate distributions of the maximum-likelihood estimates of these measures and thus obtain the maximum-likelihood-based confidence regions for these measures. The method is presented via a real medical example.     

The E-Bayesian and hierarchical Bayesian estimations for the proportional reversed hazard rate model based on record values

In this paper, E-Bayesian and hierarchical Bayesian estimations of the shape parameter, when the underlying distribution belongs to the proportional reversed hazard rate model, are considered. Maximum likelihood, Bayesian and E-Bayesian estimates of the unknown parameter and reliability function are obtained based on record values. The Bayesian estimates are derived based on squared error and linear–exponential loss functions. It is pointed out that some previously obtained order relations of E-Bayesian estimates are inadequate and these results are improved. The relationship between E-Bayesian and hierarchical Bayesian estimations is obtained under the same loss functions. The comparison of the derived estimates is carried out by using Monte Carlo simulations. A real data set is analysed for an illustration of the findings.     

Inferences from logistic regression models in the presence of small samples,rare events,nonlinearity, and multicollinearity with observational data

The logistic regression model has been widely used in the social and natural sciences and results from studies using this model can have significant policy impacts. Thus, confidence in the reliability of inferences drawn from these models is essential. The robustness of such inferences is dependent on sample size. The purpose of this article is to examine the impact of alternative data sets on the mean estimated bias and efficiency of parameter estimation and inference for the logistic regression model with observational data. A number of simulations are conducted examining the impact of sample size, nonlinear predictors, and multicollinearity on substantive inferences (e.g. odds ratios, marginal effects) when using logistic regression models. Findings suggest that small sample size can negatively affect the quality of parameter estimates and inferences in the presence of rare events, multicollinearity, and nonlinear predictor functions, but marginal effects estimates are relatively more robust to sample size.     

脱实向虚和金融强监管对金融实体行业间极端风险关联的影响

随着金融机构影子银行业务的扩张和部分实体企业“脱实向虚”倾向的加剧,金融与实体经济的联系愈发紧密,对于极端风险的研究不应只局限于金融体系内部。故此,本文首先基于行业指数日度数据与五分钟高频数据测算行业风险价值,其次利用Elastic-Net-VHAR模型构建金融实体极端风险网络进行动态演化分析,最后研究实体与金融行业间风险溢出水平的影响因素。结果显示:第一,基于横截面维度,材料和工业行业在网络中居于中心位置,金融行业的风险净溢出水平为负;第二,2017年金融强监管政策开启后,网络整体密度明显下降,实体行业对金融行业风险输出水平降低,而金融行业对实体行业风险输出水平略有提升;第三,面板回归结果显示,实体行业“脱实向虚” 程度显著提升了实体与金融行业之间双向风险溢出水平,并且在金融强监管与双向风险溢出水平之间起到了正向调节效应。根据上述结论,建议监管层进一步推进金融强监管政策,注意金融监管政策与供给侧结构性改革政策之间的配合,还应特别重视对实体企业金融化规模进行严格监控,更加有效地防范系统性风险。     

煤炭大数据指数编制及经验模态分解模型研究

基于开放性数据源、连续观测昨多变量数据编制的大数据指数,与传统的统计调查指数存在的差异不仅在于数据本身的无限扩张,而且在于编制方法以及分解研究的规则、模型方面的差异。在大数据背景下,率先尝试性地提出大数据指数的定义和数据假设,将"互联网大数据指数"引入煤炭交易价格指数综合编制太原煤炭交易大数据指数,从而反映煤炭价格的变动趋势;导入经验模态分解模型,对所编制的煤炭大数据指数进行分解研究,尝试比较与传统的统计调查指数的差异。研究表明:新编制的煤炭价格大数据指数要比太原煤炭交易价格指数更为敏感和迅速,能更好地反映煤炭价格的变动趋势。随着"互联网+"和大数据战略的逐渐普及,基于互联网大数据编制的综合指数会影响到更多领域,将成为经济管理和社会发展各个领域的晴雨表和指示器;与传统统计调查指数逐步融合、互补或者升级,成为宏观经济大数据指数的重要组成部分。     

The magnitude of the difference of crude and adjusted log odds ratios

Crude and adjusted odds ratios, calculated from a collapsed 2×2 table or a stratified 2×2×K table, can be very similar or quite different when significant associations are found between each dichotomous variable and the K-level stratifying variable. It is demonstrated here that the magnitude of the difference between the logs of the two estimators can be approximated by 4 times the covariance between log linear interactions describing the associations of each of the binary variables with the stratifying variable. Two data examples illustrate the usefulness of the variability and covariability of the interactions in providing a statistical accounting for the magnitude of the difference between the logs of the crude and adjusted odds ratios. Other interpretations and applications of the variances and covariances of the log linear interactions are discussed.     

B-S模型的扩展及其在石油开发中的应用

近年来,在石油勘探开发投资决策中,采用实物期权的方法进行评估取得了快速发展,但是随着国际油价的大幅走高,人民币汇率的坚挺,传统的B-S模型对实物期权的估价方法受到挑战。对多元伊藤过程进行研究,实现了期权估价的B-S模型的扩展,并且通过对开发勘探中随机变量的规范,引入国际油价和汇率两个变量,开发出一种新型的石油开发实物期权评价方法。     

我国最低工资统计测算模型研究

 最低工资统计测算模型研究，历来是各国政府极为重视的问题之一。它涉及到运用统计调查方法、经济计量模型、计算机辅助测算等方法，对最低工资测算、劳动者生存质量，以及对制度法规等问题进行定性定量分析的跨学科研究的问题，由于该课题在我国研究的时间较短，特别是统计学者介入研究不够，导致各级劳动和社会保障部门虽然亟需解决最低工资统计测算模型问题，但囿于统计技术问题，其发展极为缓慢。这也是本课题组亟力推动研究之动力。     

基于贝叶斯面板模型的扩展C-D生产函数估计及实证

利用2008—2011年的省际面板数据并充分收集和整理先验信息,运用贝叶斯面板模型分析和研究了扩展的C-D生产函数,有效地处理了短期时序造成的小样本问题以及误差项之间的相关性问题,实现参数的适时修正和更新。研究发现:目前中国物质资本份额的后验均值为55%,明显低于中国学者估计的60%;人力资本所占份额仅为5%~6%,其对经济增长的拉动作用没有得到充分的发挥,中国应增大人力资本投入;固定资产投资比例人均产出弹性的后验均值为1.37;地理位置等个体差异依旧是造成中国发展不平衡问题逐年扩大的重要原因。     

油气开发的实物期权特征及应用B-S模型的条件检验

分析石油开发期权特征以及应用B-S模型的假设条件,并使用SPSS软件的K-S检验以及Q-Q图分析方法,通过对纽约伦敦两大石油交易所原油价格数据的研究,验证了石油价格遵循对数正态分布的假设,从而检验了石油开发期权应用B-S模型评价中几何布朗运动的前提条件假设。     

辽宁省就业和经济增长关系的时变参数模型

在讨论就业和经济增长之间关系的理论基础上,分析辽宁省就业弹性偏低和奥肯定律发生重大变异的机理,然后指出随时间变化的就业弹性系数才是分析辽宁省就业和经济增长之间关系的重要前提,最后构建辽宁省就业与经济增长之间关系的时变参数模型。     

数据挖掘中多分类有序变量间距差异分析及应用

文章在明确累积logistic回归模型的基础上,针对多分类有序变量存在间距差异的问题,提出了统计检验方法并引入工具虚拟变量对logistic模型加以改进,通过其在实际中的应用,取得了良好的效果.     

我国货币供应与经济增长及物价水平关系研究

 本文采用协整、向量误差模型以及脉冲响应和方差分解的方法对中国货币供应、物价水平与经济增长的关系进行实证研究。研究表明,物价水平在长期中对经济增长的负影响明显,在短期内,也存在负面影响,但影响方向不明显;短期内物价水平与货币供应量之间相互影响,互相促进。货币供应对经济增长的影响具有促进效应,长期内货币非中性。此外,向量误差模型也表明经济增长、货币供应和物价水平都受到自身滞后期的影响,经济发展具有长期且趋于稳定的特性。     

外商直接投资与我国资本形成的协整研究

文章首先概述了经济学界对外商直接投资与资本形成一般关系的分析,然后运用协整理论对数据进行了平稳性检验、格兰杰原因检验,建立了外商直接投资和全社会固定资产投资的协整模型和误差修正模型,认为在长期和短期内外商直接投资对我国的资本形成都有促进作用。