Coverage of the population in Census 2000: Results from Demographic Analysis

Since the 1960 Census, Demographic Analysis (DA) has been used by the Census Bureau to evaluate the coverage of the population. Administrative statistics on births, deaths, immigration and Medicare enrollments as well as estimates of legal emigration and net undocumented immigration are used to produce demographic analysis estimates of the population for the census date. These estimates are compared to the Census 2000 data to evaluate coverage in the census. The results are also compared to measures of undercount obtained from dual system estimation. The DA measures substantial reduction in net undercount in Census 2000 compared to 1990. The reductions occur among all demographic categories: all broad age groups, males and females, Blacks and Non-Blacks.     

Can Regional Variations in Demographic Structure Explain Regional Differences in Car Use? A Case Study in Austria

Due to its manifold impact on the environment private car use represents an important dimension of environmental behavior in industrialized countries. Obviously, private car use is related to demographic characteristics of households such as the life-cycle stage and the living arrangement the household lives in. In addition systematic regional differences of private car use have to be taken into account. In this paper a causal model is derived, which aims to explain regional differences in car ownership and car use by regional demographic differences and region-specific control factors such as the car technology and institutional factors. Using aggregate data from a household survey in Austria and data from Austrian official statistics causal effect coefficients are then estimated. By applying path analysis the estimated effects of regional demographic characteristics on region-specific car ownership and car use can be decomposed into direct and indirect effects, with the latter effects being mediated by the control factors. Except for the average age of household heads and population density no significant direct demographic effects on regional patterns of car ownership and car use can be found. Car ownership and car use are best predicted by using the considered control factors as predictor variables. Nevertheless, many of the presumed indirect effects turn out to be of importance since demographic factors are closely linked to measures of regional institutional settings like per capita income, ownership of house/apartment and net commuting index.     

Investigating Regional Disparities of China’s Human Development with Cluster Analysis: A Historical Perspective

This paper adopts both one-dimensional and multi-dimensional cluster analysis to analyze China’s HDI data for 1982, 1995, 1999, and 2003, and to classify China’s provinces into four tiers based on the three basic developmental aspects embedded in HDI. The classifications by cluster analysis depends on the observations’ similarities with respect to clustering variable(s), rather than subjectively predetermined threshold values adopted by major international organizations, like UNDP, to make their classification. By investigating the multi-dimensional clustering results, this paper describes the features of each of the four tiers based on their characteristics within the three developmental aspects, explores the patterns of cross-tier disparities, and tracks the evolutions from a historical perspective. Also found is that, in China, the overall regional disparities have been increasingly attributable to regional economic disparities.     

Helpless Dependents or Active Independents: A Cluster Analysis of Elders in China

The current study aimed to gain a better understanding of Chinese seniors’ demographic information as well as their attitudes toward old-age support as an indicator for their subjective well-being related to their retirement preparation. Particularly, the variation of demographic and attitudinal characteristics within the population was examined. The data was based on a sample of the Chinese senior population, aged 60 and over in 2006 from 20 provinces and metropolitan areas in China. A two-step cluster analysis was used in the current study and the auto-clustering algorithm indicated a two-cluster solution. Both demographic information and attitudinal responses were used for the clusters. The results showed that Chinese seniors’ attitudinal and behavioral traits were relevant to the classification with regard to their retirement preparedness. The current study demonstrated that Chinese seniors were a heterogeneous group that could be divided into two basic, distinct segments, namely, helpless dependents and active independents. Each different group of seniors may raise different key issues in meeting their needs for retirement management.     

基于GIS的宁夏人口经济压力空间分布研究

空间分析是深入探索空间特征的重要技术,因此作者利用空间分析中的主成分分析方法和空间自相关分析对宁夏人口经济压力分类及其分布关系进行了深入探索,结果表明,宁夏人口经济压力从北部向南部逐渐增大,在空间分布关系上人口经济压力呈现明显的组团模式,北部区域以银川为核心呈低—低关联模式,南部区域以原州区为核心呈高—高关联模式。     

Spatial Regression Models for Demographic Analysis

While spatial data analysis has received increasing attention in demographic studies, it remains a difficult subject to learn for practitioners due to its complexity and various unresolved issues. Here we give a practical guide to spatial demographic analysis, with a focus on the use of spatial regression models. We first summarize spatially explicit and implicit theories of population dynamics. We then describe basic concepts in exploratory spatial data analysis and spatial regression modeling through an illustration of population change in the 1990s at the minor civil division level in the state of Wisconsin. We also review spatial regression models including spatial lag models, spatial error models, and spatial autoregressive moving average models and use these models for analyzing the data example. We finally suggest opportunities and directions for future research on spatial demographic theories and practice.

A Probabilistic Perspective on Re-Identifiability

A quasi-identifier is a set of attributes that can be used to re-identify entries in anonymized data sets. A group of individuals is considered about whom quasi-identifying numerical information is disclosed such as date of birth, age, weight, and height. The fraction of individuals is determined whose information is unique in that group and hence is identifiable unambiguously. Nonuniformity can be captured well by a single number, the Kullback-Leibler distance. For example sets of real microdata, given approximations based on Kullback-Leibler distances are accurate. Second, the effect of disclosing more specific or less specific information is analyzed experimentally. Third, the effect of correlation between numerical attributes is measured. A formula gives the re-identifiability level. The approximations are validated using publicly available demographic data sets.     

Variable Weighting via Multidimensional IRT Models in Composite Indicators Construction

One of the most controversial steps in Composite Indicators (CIs) construction is the selection of one (possibly) best weighting technique. In this paper, we introduce a new endogenous weighting methodology developed in an extended Item Response Theory (IRT) framework. As weighting is much more thorough when carried out by accounting for the dimensionality of a dataset rather than by ignoring it, we suggest to assign weights on the basis of the discrimination parameters estimated through a multidimensional two-parameter logistic IRT model. Specifically, the procedure is developed through two consecutive steps. The first applies a hierarchical clustering algorithm to ascertain the number of dimensions measured by the data. The second estimates the discrimination parameters under the multidimensional two-parameter logistic model selected at the first step. The discrimination parameters can then be used to compare and weight the items that refer to the same dimension. Besides, in order to make such discrimination indices comparable across dimensions, the distribution of the latent trait is standardised for each dimension. The potentialities of this novel weighting technique are illustrated through an application to educational data, which refer to a national standardised test developed and collected by the Italian National Institute for the Evaluation of the Education System.     

Demographic Efficiency: Concept and Estimation

The concept of demographic efficiency is proposed and data envelopment analysis (DEA) is introduced as a method for determining which countries are demographically efficient. While the purpose of the paper is primarily to introduce the concept and the method, several simple examples are used for purposes of illustration. The first two explore how efficiently countries have converted their level of development (the input) into male and female life expectancy at birth (the outputs). The second two reverse the postulated relationship, treating life expectancies as inputs reflecting general health status of a population, and level of development as the output. Countries are said to be efficient if they have achieved the maximum output observable for a given level of input, or if they have minimized the inputs needed to achieve a prescribed level of output. Together, the efficient cases form an efficiency frontier. DEA, a form of linear programming, also permits the degree of inefficiency of countries lying behind this frontier to be measured by calculating the extent of the output slacks that are present. Output slacks are the shortfalls in the level of performance that could have been achieved given the inputs available, and may themselves be treated as independent variables in explorations of the sources of demographic inefficiency. One example of such an exploration is offered—an attempt to account for shortfalls in female life expectancy, given levels of development.     

Neonatal mortality and stillbirths in early twentieth century Derbyshire,England

Neonatal mortality and stillbirths are recognised to be subject to similar influences, but survival after a successful live birth is usually considered in isolation of foetal wastage. Moreover, individual-level data on age-specific influences and causes of death in a historical context are rare. This paper uses an unusual data set to compare the influences on neonatal mortality and stillbirths in early twentieth century Derbyshire, England. Multivariate hazard and logistic analyses are performed to examine the relative roles of various social, environmental, and demographic factors. The influences on and causal structures of neonatal mortality and stillbirths emerge as broadly similar, with previous reproductive history linked to a considerable amount of variation. The clustering of endogenous deaths was much greater than the clustering of exogenous and post-neonatal deaths, probably reflecting the cause-of-death structure and the relatively healthy social and environmental position of early twentieth century Derbyshire.     

Religion as a Determinant of Economic and Demographic Behavior in the United States

This note reviews and synthesizes research on the effects of religion on various economic and demographic behaviors of individuals and families in the United States, including the choice of marital partner, union formation and dissolution, fertility, female time allocation, education, wages, and wealth. Using a theoretical framework based on Gary Becker's contributions to the economics of the family, it demonstrates that religious affiliation affects economic and demographic behavior because of its impact on the costs and benefits of many interrelated decisions that people make over the life cycle. In addition, for behaviors that pertain to married-couple households, religious affiliation matters because it is a complementary trait within the context of marriage. Religiosity, another dimension of religion, also affects economic and demographic outcomes, partly because it accentuates differences by religious affiliation, partly because religious involvement has generally beneficial effects on health and well-being.     

Demographic data and geographic information systems for decision making: The case of public health

Recent changes in the United States health care system include a broadened definition of health and renewed focus on public health. Increasingly, demographic analyses are incorporated into public health decision-making. Analysts also are using geographic information more routinely, because Geographic Information System (GIS) software is becoming easier to use. The paper describes three cases in which demographers used GIS to analyze the spatial distribution of public health data. The first case, from Santa Clara County, California, focuses on adolescent sexually transmitted diseases in secondary school districts. The second case, also from Santa Clara County, maps preventable hospitalizations of senior citizens. The third examines the distribution of premature births in Tennessee counties. The researchers applied demographic techniques and perspectives in each case, and each case produced information that is being used by officials who plan health education campaigns and services.     

Poverty,Inequality, and Fertility: The Contribution of Demographic Change to Global Poverty Reduction

Global poverty has fallen dramatically over the past decades. In many developing countries, this transformation was accompanied by rapid improvements in demographic outcomes, such as falling child mortality and fertility. Yet, recent theorizing and empirical research into the causes of global poverty reduction has mostly omitted demographic factors. This paper aims to fill this gap by testing for effects of demographic variables on poverty. Using time series data for 140 countries, we document a strong effect of lagged fertility on country-specific poverty rates. This effect is robust across several specifications and data sets. It appears to be stronger in countries with larger fertility differentials, in the early transition stages. The proposed mechanism behind this result is a “Kuznets curve-type” expansion of fertility inequality at the onset of the demographic transition. We conclude by calling for a stronger inclusion of demographic variables in the distribution-sensitive analysis of global poverty.     

Barriers to Managing Coronary Artery Disease Among Older Women

Numerous barriers to managing coronary artery disease (CAD) among older women are reported in the literature; however, few studies adjust for demographic and health status differences. A survey assessing barriers and other factors was distributed to a stratified random sampling of older women with CAD. Factor analysis and multiple logistic regression procedures were used to estimate the impact of these issues on receiving a CAD-related office visit. The most problematic barriers included denial and low health literacy. Efforts to promote patient awareness of heart health and better communication between patients and clinicians may alleviate these barriers.     

Birth outcome, not pregnancy process: Reply to van der Veen

In a recent article (Frisbie. Forbes. and Pullum 1996) we documented racial/ethnic differences in birth outcomes according to a more fine-grained classification than has typically been employed in the demographic literature. In his commentary, van der Veen focuses on the measurement of one of the dimensions of that classification, maturity of the infant. as proxied by the fetal growth ratio. The crux of the critique is easily seen in van der Veen's statement that “all of my disagreements with Frisbie et al. 's method arise from their particular use of a postnatal standard for the assessment of intrauterine growth.” Our critic misunderstands our objective: He fails to realize our interest in birth outcome, not pregnancy process, and does not perceive that our intent was to extend the research extant in both the demographic and public-health literatures in which patently postnatal (i.e., ex utero) measures are taken as outcomes interesting in their own right and/or as risk factors for infant mortality and infant and childhood morbidity. Specifically, he does recognize that we purposefully expanded our focus to include moderately compromised births to determine if they were at higher risk than the normal births with whom they are conventionally categorized. Our discussion draws on research cited in the original article, on studies cited by our critic, and on a few more recent investigations. Although we have never argued that ours is the only, or even the best, approach in all cases, we try to clarify the rationale for, and adduce additional empirical evidence of, the utility of the method we used.     

Aging in the United Kingdom: a review of demographic trends,recent policy developments and care provision

"Although the U.K.'s population is not predicted to grow very much in the future, the population structure is changing and there is a shift towards a much older age distribution. The characteristics of demographic aging in the U.K. include a marked reduction in fertility rates, increasing rates of life expectation at birth..., increasing dependency ratios and variations in mortality and social class in old age. The U.K.'s demographic context has important implications for aged care policy and planning. This paper documents the demographic trends, reviews recent major policy changes and their impact on care provision, and discusses some of the emerging implementation issues that challenge the potential of such policies to meet the needs of an aging population."     

A spatial analysis of population dynamics and climate change in Africa: potential vulnerability hot spots emerge where precipitation declines and demographic pressures coincide

We present an integrative measure of exposure and sensitivity components of vulnerability to climatic and demographic change for the African continent in order to identify “hot spots” of high potential population vulnerability. Getis-Ord Gi* spatial clustering analyses reveal statistically significant locations of spatio-temporal precipitation decline coinciding with high population density and increase. Statistically significant areas are evident, particularly across central, southern, and eastern Africa. The highly populated Lake Victoria basin emerges as a particularly salient hot spot. People located in the regions highlighted in this analysis suffer exceptionally high exposure to negative climate change impacts (as populations increase on lands with decreasing rainfall). Results may help inform further hot spot mapping and related research on demographic vulnerabilities to climate change. Results may also inform more suitable geographical targeting of policy interventions across the continent.