Demographics of the gay and lesbian population in the United States: Evidence from available systematic data sources

This work provides an overview of standard social science data sources that now allow some systematic study of the gay and lesbian population in the United States. For each data source, we consider how sexual orientation can be defined, and we note the potential sample sizes. We give special attention to the important problem of measurement error, especially the extent to which individuals recorded as gay and lesbian are indeed recorded correctly. Our concern is that because gays and lesbians constitute a relatively small fraction of the population, modest measurement problems could lead to serious errors in inference. In examining gays and lesbians in multiple data sets we also achieve a second objective: We provide a set of statistics about this population that is relevant to several current policy debates.     

Using administrative data to estimate population displacement and resettlement following a catastrophic U.S. disaster

After a large scale evacuation, authorities need to know the new and frequently changing population distributions in order to meet needs for housing, schools, health care, and other services. This paper reviews literature from the fields of demography and other disciplines to identify available administrative data sets that can form the basis of sound, relevant, and timely county-level population estimates following a catastrophic U.S. event. The most appropriate data to estimate population in damaged counties will be disaster-specific data such as housing damage estimates and FEMA applicant counts initially, and later electric accounts and USPS active residences. In heavily damaged counties, data on electric accounts and USPS active residences may not be consistently collected for many months, during which time sample surveys may be needed. For counties that receive an influx of population, school enrollment data provide the most appropriate basis for population estimates. Population estimates for large, heavily damaged counties are highly uncertain. Sensitivity analysis when using estimates for planning in these areas is recommended. The Census Bureau can build on this research by codifying recommendations to local authorities for developing frequent post-disaster population estimates.     

The Population of Centenarians in Brazil: Historical Estimates from 1900 to 2000

Since the nineteenth century, the census has provided the number of 100-year-olds in Brazil, one of the most populous countries worldwide. In 1900, 4,438 individuals reported themselves to be centenarians, a figure that increased about fivefold by the 2000 census. However, due to data quality issues, we are skeptical about the real size of the recorded population in the Brazilian census. We offer alternative estimates of the most likely number of centenarians during the twentieth century by combining variable-r relations with different mortality models. Our results indicate there was virtually no centenarian at the beginning of the twentieth century. The population has become larger than 1,000 individuals only in the 1990s, suggesting there has been an extensive, although diminishing, overenumeration of centenarians in the census records. Our results can help policymakers to plan the demands of a growing old age population in places that face stricter family and public budget constraints.     

Using Discrete-Time Event History Fertility Models to Simulate Total Fertility Rates and Other Fertility Measures

Event history models, also known as hazard models, are commonly used in analyses of fertility. One drawback of event history models is that the conditional probabilities (hazards) estimated by event history models do not readily translate into summary measures, particularly for models of repeatable events, like childbirth. In this paper, we describe how to translate the results of discrete-time event history models of all births into well-known summary fertility measures: simulated age- and parity-specific fertility rates, parity progression ratios, and the total fertility rate. The method incorporates all birth intervals, but permits the hazard functions to vary across parities. It can also simulate values for groups defined by both fixed and time-varying covariates, such as marital or employment life histories. We demonstrate the method using an example from the National Survey of Family Growth and provide an accompanying data file and Stata program.     

Fathers’ Imprisonment and Mothers’ Multiple-Partner Fertility

We consider the intersection between two striking U.S. trends: dramatic increases in the imprisonment of fathers and increases in the proportion of mothers who have children with more than one partner (multiple-partner fertility, or MPF). Using matched longitudinal administrative data that provide unusually comprehensive and accurate information about the occurrence and timing of imprisonment, fertility, and MPF for the population of the state of Wisconsin, we consider the relationship between paternal imprisonment and MPF among unwed mothers. Employing discrete-time event history analysis with multinomial logistic regression, we model the occurrence and timing of the mother’s second birth, distinguishing between a birth with the same father and a birth with a different father, and distinguishing between current imprisonment and a history of imprisonment. We find that current imprisonment is associated with an increased likelihood of MPF and a decreased likelihood of fertility with the same father (compared with no additional birth) and that a history of imprisonment is associated with increased MPF in some models but not in our preferred model. To control for unobserved heterogeneity among mothers and assess the evidence of a causal effect of fathers’ imprisonment, we also employ the case-time-control method, a fixed-effects method for the analysis of nonrepeated events. Results suggest that fathers’ current imprisonment may increase mothers’ MPF. Policy implications are discussed.     

Socio-economic status and fertility decline: Insights from historical transitions in Europe and North America

The timings of historical fertility transitions in different regions are well understood by demographers, but much less is known regarding their specific features and causes. In the study reported in this paper, we used longitudinal micro-level data for five local populations in Europe and North America to analyse the relationship between socio-economic status and fertility during the fertility transition. Using comparable analytical models and class schemes for each population, we examined the changing socio-economic differences in marital fertility and related these to common theories on fertility behaviour. Our results do not provide support for the hypothesis of universally high fertility among the upper classes in pre-transitional society, but do support the idea that the upper classes acted as forerunners by reducing their fertility before other groups. Farmers and unskilled workers were the latest to start limiting their fertility. Apart from these similarities, patterns of class differences in fertility varied significantly between populations.     

Estimating historic population data for small geographies using census housing information

Historical population data for small geographies (e.g. blocks, block-groups, and census tracts) are not available for periods earlier than 1980. In this research note, we propose a geographically-constrained housing unit method (GHUM) to estimate historic population for small geographies using housing age data available in the 1980–2000 censuses. The GHUM is a two-stage method. The first stage follows a traditional housing unit method and provides initial household and group quarter population estimates for small geographies. The second stage takes advantage of the availability of historic data for larger geographies (e.g. counties, states) to adjust the first stage estimates and to provide final estimates. The GHUM is used to estimate 1940–1990 county population and census tract population in Kentucky. The quality of the population estimates is assessed. A two-sample Kolmogorov–Smirnov test indicates that these estimates are statistically reliable at the 10 % significance level.     

Mortality estimation from registered deaths in less developed countries

Age-specific population growth rates were introduced to demographic analysis in earlier work by Bennett and Horiuchi (1981) and Preston and Coale (1982). In this paper, we derive a method which uses these growth rates to transform what may be a set of incompletely recorded deaths by age into a life table that accurately reflects the true mortality experience of the population under study. The method does not rely on the assumption of stability and, for example, in contrast to intercensal cohort survival techniques, is simple to implement when presented with nontraditional intercensal interval lengths. Thus we can obtain mortality estimates for less developed countries with defective data, despite departures from stability. Further, we assess the sensitivity of the method to violations in various assumptions underlying the procedure: error in estimated growth rates, existence of non-zero net intercensal migration, age dependence in the completeness of death registration, and misreporting of age at death and age in the population. We demonstrate the use of the method in an application to data referring to Argentine females during the period 1960 to 1970.     

Immigrant mothers’ preferences for children’s sexes: A register-based study of fertility behaviour in Norway

Parental sex preferences have been documented in many native populations, but much less evidence is available on immigrants’ preferences for the sexes of their children. Using high-quality longitudinal register data from Norway, a country with a recent immigration history, we estimate hazards regression models of third birth risks by the sex composition of the first two children. A central question in the extant literature is whether the sex preferences of immigrant mothers match those observed in their country of origin, or if cultural adaption to local conditions is more important. Our analyses indicate that the sex preferences of immigrants generally match those previously documented for their native population, especially in the case of son preferences. The pattern of sex preferences is unmodified by the mother’s exposure to the host society. In sum, our evidence generally supports theories emphasizing cultural persistence in preferences, rather than theories of adaption or immigrant selectivity.     

A longitudinal analysis of household and nonhousehold living arrangements in later life

Most explanatory models of living arrangements in later life link the decision process surrounding choice of living arrangement to personal resources such as income and health. Applications of these models, however, are based for the most part on cross-sectional rather than longitudinal data. In this paper we examine living arrangements in later life among the nonmarried population aged 55 and over, using data from the Survey of Income and Program Participation. We observe individuals as they change living arrangements, die, or become institutionalized. Our results suggest that economic resources dominate the decision-making process in transitions across different household arrangements, whereas health is most important in explaining institutionalization.     

On the estimation of multidimensional demographic models with population registration data

In this paper the estimation of multidimensional demographic models is investigated in situations where population registration data are available. With this kind of aggregate data, estimation by traditional methods is not possible. We look at two versions of the multidimensional model: the constant intensities model and the linear integration model. Some logical inconsistencies in the derivation of the latter are discussed. In particular, we argue that the linear integration model is not compatible with a Markov process. A new algorithm for the estimation of the constant intensities model with population registration data is proposed. Some preliminary results on the mathematical and statistical properties of this method are given. The algorithm is applied to Dutch nuptiality data.     

Evaluating Population Forecast Accuracy: A Regression Approach Using County Data

Many studies have evaluated the impact of differences in population size and growth rate on population forecast accuracy. Virtually all these studies have been based on aggregate data; that is, they focused on average errors for places with particular size or growth rate characteristics. In this study, we take a different approach by investigating forecast accuracy using regression models based on data for individual places. Using decennial census data from 1900 to 2000 for 2,482 counties in the US, we construct a large number of county population forecasts and calculate forecast errors for 10- and 20-year horizons. Then, we develop and evaluate several alternative functional forms of regression models relating population size and growth rate to forecast accuracy; investigate the impact of adding several other explanatory variables; and estimate the relative contributions of each variable to the discriminatory power of the models. Our results confirm several findings reported in previous studies but uncover several new findings as well. We believe regression models based on data for individual places provide powerful but under-utilized tools for investigating the determinants of population forecast accuracy.     

Optimization models for degrouping population data

In certain countries population data are available in grouped form only, usually as quinquennial age groups plus a large open-ended range for the elderly. However, official statistics call for data by individual age since many statistical operations, such as the calculation of demographic indicators, require the use of ungrouped population data. In this paper a number of mathematical models are proposed which, starting from population data given in age groups, enable these ranges to be degrouped into age-specific population values without leaving a fractional part. Unlike other existing procedures for disaggregating demographic data, ours makes it possible to process several years' data simultaneously in a coherent way, and provides accurate results longitudinally as well as transversally. This procedure is also shown to be helpful in dealing with degrouped population data affected by noise, such as those affected by the age-heaping phenomenon.     

Some New Techniques for Applying the Housing Unit Method of Local Population Estimation: Further Evidence

The housing unit method of population estimation is often characterized as being imprecise and having an upward bias. In an earlier paper we argued that the method itself cannot be properly characterized by a particular level of precision or direction of bias. Only specific techniques of applying the method can have such characteristics. In that paper we presented several new techniques for estimating the number of households and average number of persons per household (PPH). However, the testing of these new techniques was limited by the lack of census results against which the estimates could be compared. Complete census data on population, households, and PPH are now available and can be used to test alternate estimation techniques. In this paper we replicate the tests reported in our earlier paper using 1980 census data for Florida’s 67 counties. These tests provide further evidence that the new techniques produce more precise, less biased estimates than previously used techniques.     

Estimating the completeness of reporting of adult deaths in populations that are approximately stable

An elaboration of Preston's (Preston and Hill, 1980) procedure for determining the completeness with which deaths are recorded in approximately stable populations is presented. Both the procedures of Preston and that of Brass are conventionally limited to mortality beyond early childhood, to mortality above age 5 or age 10. The method considered here is based on characteristics of stable populations, i.e., populations that have been subject for a long time to little variation in age-specific mortality schedules or in overall levels of fertility. The essential features of a stable population are maintained even if fertility has changed. This is the case as long as no strong trend in fertility existed more than 15 or 20 years before the date at which the population is observed. Recent changes in fertility may affect the structure of the population at adult ages, but the effect on estimates of completeness of death records can generally be kept within tolerably narrow limits. Prior to showing how explicit estimates of the relative completeness of recording of numbers of deaths and persons can be derived from counts of deaths and persons by age, it is noted that a life table for a stable population can be constructed directly from the recorded distribution of deaths by age, or from the recorded distribution of persons. The procedures described are applied to several different populations in order to illustrate the computational steps necessary to estimate the completeness of death records at ages above childhood in populations that are approximately stable.     

Count data models for demographic data∗

Key demographic variables, such as the number of children and the number of marriages or divorces, can only take integer values. This papers deals with the estimation of single equation models in which the counts are regressed on a set of observed individual characteristics such as age, gender, or nationality. Most empirical work in population economics has neglected the fact that the dependent variable is a nonnegative integer. In the few cases where this feature was recognized, the authors advocated the use of the Poisson regression model. The Poisson model imposes, however, the equality of conditional mean and variance, a restriction which is often rejected by the data. We propose a generalized event count model to simultaneously allow for a wide class of count data models and account for over‐ and underdispersion. This model is successfully applied to German data on fertility, divorces and mobility.     

Economic and Institutional Context and Second Births in Seven European Countries

The extent to which mothers progress to a second child varies greatly between European countries. Although both institutional and economic context are believed to be partly responsible for these differences, available research on economic conditions and fertility mostly focuses on first births and studies on family policy and fertility have hitherto insufficiently addressed population heterogeneity. Combining longitudinal microdata from the Harmonized Histories with contextual data on labour market uncertainty and family policy, this paper uses discrete-time hazard models to analyse the impact of economic and institutional context on second birth hazards of 22,298 women in 7 European countries between 1970 and 2002. Particular attention is paid to variation in the contextual effects by level of education. We find that aggregate-level unemployment and temporary employment reduce second birth hazards, particularly for low- and medium-level educated women. Family policies are positively related to second birth hazards. Whereas family allowances stimulate second births particularly among low educated mothers, the positive effect of childcare is invariant by level of education.     

初婚初育史对育龄妇女二孩生育间隔的影响

由于常规生存模型假定删截和事件发生相互独立,导致研究者常常忽略删截案例中可能还包含经历事件的风险为零的长期存活者。忽略这一总体异质性会导致有偏的参数估计。文章介绍并应用分割总体生存模型来探究初婚初育史对中国育龄妇女的二孩生育间隔的影响。结果发现,在控制个体特征和所处文化背景特性的情况下,对于有可能生育二孩的妇女,初婚年龄的推迟、初育为女孩的情况都将导致二孩生育间隔的缩短;所属初育队列越晚、初育孩子健康、初育后哺乳时间越长、间隔期内人工流产次数越多则都会显著延长二孩生育间隔。     

A new technique for measuring household changes

Because many recent policy decisions have been aimed at effecting changes in the socioeconomic characteristics of families or households, it has become necessary to isolate policy-induced changes from demographic changes in households over time. To obtain such longitudinal data, the family records from three panels of the Current Population Survey that were interviewed both in March, 1964, and March, 1965, were used in a computer record-matching operation.The resulting data confirm that approximately 20 percera of all households are mobile in the period of a year as evidenced by the nonmatched households that were found in 1964 but not present in 1965. More important, the data indicate that S percent of the nonmobile family households became individual households, or the reverse, and 15 percent of all the remaining households changed in family size. These last two statistics represent the first national estimates of gross changes in the demographic characteristics of households.In addition to data on changes in households, this relatively inexpensive method can be used to match Current Population Survey persons' records and provide longitudinal data on the persons within households. Over all, this prototype technique offers policy planners an analytical tool with the necessary statistical controls for assessing the effects of policy decisions and predicting policy success.