关于人口统计调查方法体系存在的问题和改革设想

我国现行的人口统计调查方法体系是“以经常性的人口抽样调查为主体,以人口普查为基础,重点调查等为补充的多种方法的运用”,但随着经济社会的快速发展,“以普查为基础,经常性抽样调查为主体"的人口统计调查方法体系,与政府、社会对人口信息多层次、精细化、时效性的需求变得不适应,在实践中显露出矛盾和问题。本文以下将对当前人口普查和人口变动情况抽样调查,在人口统计中作用和存在问题做出分析,在此基础上提出人口统计的改革设想,并落实到具体的解决办法,以2020年第七次人口普查为契机,建立《人口统计与管理服务数据平台》,并结合社区网格化管理进行年度更新,取得年度全国、省级及省级以下的常住人口数据;同时改革人口抽样调查的内容,结合手机信令大数据在人口统计中的应用,完善人口统计调查方法体系。     

2007年浙江省人口变动抽样调查主要数据公报

根据浙江省人民政府的决定，我省于2007年11月1日进行了全省5％。人口抽样调查工作。这次调查是以全省为总体，以各市为次总体，采取分层、多阶段、整群概率比例的抽样方法。最终样本单位为调查小区。我省这次调查的常住人口为24．8万人，占全省常住人口的近5．0‰。按照国家统计局的统一部署，在省政府和地方各级政府的统一领导下，在全省广大人民群众的密切支持配合下，经过全省三千名调查工作人员的艰苦努力，基本完成了人口变动抽样调查工作，现将主要数据公布如下：     

2005年全国1%人口抽样调查主要数据公报

根据国务院的决定,我国于2005年11月1日进行了全国1%人口抽样调查工作.这次调查以全国为总体,以各省、自治区、直辖市为次总体,采取分层、多阶段、整群概率比例的抽样方法.最终样本单位为调查小区.四川省在21个市、州的181个县(市、区)、1673个乡、镇、街道、3104个村(居委会)的3873个调查小区进行调查.在国务院和省政府的统一领导下,通过调查工作人员的艰苦努力,圆满完成了人口抽样调查的现场登记和复查任务.调查登记现有人口为892201人,其中常住人口645603人.目前,调查的全部资料正在用电子计算机进行数据处理.主要数据的快速汇总工作已经结束,现将根据抽样调查结果推算的四川全省2005年人口数据资料公布如下:     

权威解读之一：四川人口普查主要数据分析

一、关于人口总量 （一）常住人口。2010年11月1日零时，全省常住人口为8041．8万人，占全国总人口的6％，居全国第4位。与2000年第五次全国人口普查结果相比，常住人口减少287．3万人，减少3．45％，平均每年减少0．35％，占全国总人口的比重下降0．58个百分点，在全国的位次未发生变动。常住人口减少，主要是因为近年来各地狠抓劳务输出工作，大量劳动力流到省外造成的。     

人口调查调查谁

谈起人口调查的调查对象,大家就会不约而同地想到“常住人口”这个概念,因为我国自“三普”以来的历次人口普查和大型人口调查都以常住人口作为调查对象,也就是说只有符合常住人口定义的人才会在普查和调查中被登记。但国家统计局在制定2005年全国1%人口抽样调查(以下简称“1%调查”)方案时,决定对调查对象进行重新界定。本文将就这一问题谈几点认识。为什么要重新界定人口调查对象2000年第五次全国人口普查的调查对象是常住人口。顾名思义,一个地区的常住人口是指经常居住在该地区的人口。《第五次全国人口普查办法》中规定的“常住”时间…     

1%人口抽样调查引发的思考

云南省2005年1%人口抽样调查工作在国务院和各级地方政府的领导下,经过各级调查机构和调查人员的精心组织和艰苦努力,圆满完成了调查的组织准备、宣传动员、经费筹措、试点、培训、摸底、入户登记、复查、事后质量抽查、数据处理、分析、评估和论证等一系列工作。这标志着云南省1%人口抽样调查取得了阶段性的重要成果。通过本次全省人口抽样调查,实现了既定的调查的主要结果对县(市、区)有代表性,省、州(市)、县(市、区)三级常住人口数据衔接统一的目标,获得了主要人口数据质量较高,得到国家和有关部门及专家的一致认可,但同时也引发笔者很…     

严格执行统计法,认真做好今年的人口变动情况和城镇劳动力抽样调查工作

人口变动情况抽样调查从1982年起，已连续进行了15年，为国务院和各省、自治区、直辖市人民政府提供了比较准确的年度人口数据，为党和政府制定政策提供了比较准确的可靠依据。统计局和劳动部又决定从今年开始在全国建立并实施城镇劳动力调查制度。目前调查工作一方面越来越受到各级领导的重视，另一方面调查的难度也越来越大，特别是人为干扰不如实提供调查数据的现象时有发生。我们要想做好今年的人口变动情况和城镇劳动力抽样调查工作，首先要提高对调查工作重要性的认识．人口变动情况抽样调查数据是掌握各省、自治区、直辖市年度人口增…     

四川人口年龄结构变动趋势

人口年龄结构与人类经济活动有密切关系，它的变动几乎关系到一个地区社会经济发展的方方面面。本文根据第五次和第六次人口普查数据，对四川人口年龄结构变动趋势进行了分析。     

基于人口集聚视角的人口变动对劳动收入份额的影响

劳动收入份额作为国民收入分配环节中的重要问题,关系到初次分配的公平程度和经济发展质量。威廉姆森假说表明适度的人口集聚可以促进经济发展,但过度集聚反而会导致人口结构恶化,抑制劳动收入份额增长。为探究中国人口变动对劳动收入份额的影响,创新性地以人口集聚为切入点,采用世代交叠模型进行理论机制分析的同时,结合中介效应和门槛效应模型对中国30个省份(除西藏、港澳台外)2000—2017年的数据进行实证检验,以探究人口自然变动、迁移变动和结构变动对劳动收入份额的作用是否会受人口集聚效应的影响,以及沿海与内陆地区变动规律的差异。研究表明：人口变动过程中存在人口集聚的中介效应和门槛效应;人口自然增长可以促进劳动收入份额增长,但人口密度高于门槛值时促进作用明显减弱;人口净迁入对劳动收入份额的影响呈倒U型,人口密度高于门槛值时促进作用转为抑制作用;老年抚养比提升会抑制劳动收入份额增长;沿海和内陆地区劳动收入份额变动规律一致,但沿海地区人口集聚的门槛效应更加明显。从人口变动视角出发,有助于为中国统筹提升各地劳动收入份额,完善收入分配政策提供理论依据与建议。     

关于抽调查应用的思考

我国统计调查发展垢目标模式是建立一个以必要的周期性普查为基础、以经常性的抽样为主体,同时辅之以重点调查、科学推算和全面报表综合运用的统计调查方法体系。纵观改革开放以来统计调查方法改革的进程,全面统计报表在现行的统计调查方法体系中仍占优势,而通过抽样调查取得资料的指标仅占三分之一左右。目前抽样调查的应用限于城乡住户调查、农产量调查、物价调查、人口变动调查等领域,近年来虽开始进行小型贸易企业、工业企业抽样调查,但收效不甚明显。人们必须重新审视抽样调查,进行实事求是的分析,这对更有效地应用抽样无疑是有效的。     

Enriching Surveys with Supplementary Data and its Application to Studying Wage Regression

We consider the problem of supplementing survey data with additional information from a population. The framework we use is very general; examples are missing data problems, measurement error models and combining data from multiple surveys. We do not require the survey data to be a simple random sample of the population of interest. The key assumption we make is that there exists a set of common variables between the survey and the supplementary data. Thus, the supplementary data serve the dual role of providing adjustments to the survey data for model consistencies and also enriching the survey data for improved efficiency. We propose a semi‐parametric approach using empirical likelihood to combine data from the two sources. The method possesses favourable large and moderate sample properties. We use the method to investigate wage regression using data from the National Longitudinal Survey of Youth Study.     

A validation of a computer-assisted randomized response survey to estimate the prevalence of fraud in social security

Summary.  In the Netherlands, there is a research tradition that measures fraud against regulations by interviewing eligible individuals using a survey. In these studies the sensitive questions about fraud are posed by using a randomized response method. The paper describes the results of a Dutch study into the consequences of replacing home interviews by trained interviewers with Internet-delivered interviews in a survey on fraud in the area of disability benefits. Both surveys used computer-assisted self-interviews with randomized response questions. This study has three goals: first to present the research tradition that makes use of randomized response, second to compare the results of home interviews and the Internet survey and finally to introduce an adapted weighted logistic regression method to test the relationship between the probability of fraud and explanatory variables. The results show that there are no systematic differences between modes of interview, either for estimates of the prevalence of fraud or for the identification of associated variables. These outcomes result in the conclusion that the Internet survey is a useful and cost-effective instrument for measuring fraud in a population, and that it is unlikely that replacing home interviews with the Internet survey will result in a significant break with tradition.     

Simulation of close-to-reality population data for household surveys with application to EU-SILC

Statistical simulation in survey statistics is usually based on repeatedly drawing samples from population data. Furthermore, population data may be used in courses on survey statistics to explain issues regarding, e.g., sampling designs. Since the availability of real population data is in general very limited, it is necessary to generate synthetic data for such applications. The simulated data need to be as realistic as possible, while at the same time ensuring data confidentiality. This paper proposes a method for generating close-to-reality population data for complex household surveys. The procedure consists of four steps for setting up the household structure, simulating categorical variables, simulating continuous variables and splitting continuous variables into different components. It is not required to perform all four steps so that the framework is applicable to a broad class of surveys. In addition, the proposed method is evaluated in an application to the European Union Statistics on Income and Living Conditions (EU-SILC).     

Optimal stratification in stratified designs using weibull-distributed auxiliary information

Sampling has evolved into a universally accepted approach for gathering information and data mining as it is widely accepted that a reasonably modest-sized sample can sufficiently characterize a much larger population. In stratified sampling designs, the whole population is divided into homogeneous strata in order to achieve higher precision in the estimation. This paper proposes an efficient method of constructing optimum stratum boundaries (OSB) and determining optimum sample size (OSS) for the survey variable. The survey variable may not be available in practice since the variable of interest is unavailable prior to conducting the survey. Thus, the method is based on the auxiliary variable which is usually readily available from past surveys. To illustrate the application as an example using a real data, the auxiliary variable considered for this problem follows Weibull distribution. The stratification problem is formulated as a Mathematical Programming Problem (MPP) that seeks minimization of the variance of the estimated population parameter under Neyman allocation. The solution procedure employs the dynamic programming technique, which results in substantial gains in the precision of the estimates of the population characteristics.     

网络访问固定样本调查的统计推断研究

如何解决网络访问固定样本调查的统计推断问题,是大数据背景下网络调查面临的严重挑战。针对此问题,提出将网络访问固定样本的调查样本与概率样本结合,利用倾向得分逆加权和加权组调整构造伪权数来估计目标总体,进一步采用基于有放回概率抽样的Vwr方法、基于广义回归估计的Vgreg方法与Jackknife方法来估计方差,并比较不同方法估计的效果。研究表明:无论概率样本的样本量较大还是较小,本研究所提出的总体均值估计方法效果较好,并且在方差估计中Jackknife方法的估计效果最好。     

含非随机缺失数据的面板数据参数估计方法

抽样调查领域常采用对多个受访者进行跟踪调查得到面板数据,进而对总体特性进行统计推断,在面板数据中常含缺失数据,大多数处理面板缺失数据的软件都是直接删去含缺失值的受访者以得到完全数据集,当数据缺失机制为非随机缺失时会导致总体参数估计结果有偏。本文针对数据缺失机制为非随机缺失情形下,如何对面板数据进行统计分析进行了阐述,主要采用的是基于模型的似然推断法,对目标变量、缺失指示变量和随机效应向量的联合分布建模,在已有选择模型和模式混合模型的基础上,引入随机效应,研究目标变量期望的计算方法,并研究随机效应杂合模型下参数的估计方法,在变量分布相对简单的情形下给出了用极大似然法推断总体参数的估计步骤,最后通过模拟分析比较方法的优劣。     

On robust causality nonresponse testing in duration studies under the Cox model

High survey nonresponse in unemployment duration studies may have a strong effect on inference if the so called causal mechanism is present. A robust method of testing the causal nonresponse is proposed for data sets where survey information can be combined with complete administrative records. It is assumed that population distribution follows approximately the Cox regression model. Formal justification of the method and a comparative simulation study are included.     

Variance estimation in complex survey sampling for generalized linear models

Summary.  Complex survey sampling is often used to sample a fraction of a large finite population. In general, the survey is conducted so that each unit (e.g. subject) in the sample has a different probability of being selected into the sample. For generalizability of the sample to the population, both the design and the probability of being selected into the sample must be incorporated in the analysis. In this paper we focus on non-standard regression models for complex survey data. In our motivating example, which is based on data from the Medical Expenditure Panel Survey, the outcome variable is the subject's 'total health care expenditures in the year 2002'. Previous analyses of medical cost data suggest that the variance is approximately equal to the mean raised to the power of 1.5, which is a non-standard variance function. Currently, the regression parameters for this model cannot be easily estimated in standard statistical software packages. We propose a simple two-step method to obtain consistent regression parameter and variance estimates; the method proposed can be implemented within any standard sample survey package. The approach is applicable to complex sample surveys with any number of stages.     

Planning a sample survey with a many-to-many frame structure: an empirical investigation of the effects of frame imperfections on estimates of population totals

When faced with a sampling frame that has an imperfect correspondence with the target population, the survey researcher must decide whether to use the frame as is or to expend the resources to correct its imperfections. One important consideration is the effects of the frame's imperfections on the precision of the estimate. Using simulation techniques, this paper explores the effects of frame imperfections on the precision of an estimate of a population total in simple and stratified random sampling. Some factors studied were the amount of imperfection in the frame, the nature of the correspondence between the frame units and population elements, the population coefficient of variation, and the correlation of the weights used to correct for the frame's imperfections with the measure of interest. Recommendations for planning the survey design are presented based upon our findings.