Sideline demographic methods and data

In this paper, we explore the potential of secondary data from non-profit and community-based organizations for research on temporary residents. Agencies routinely collect client information for record keeping purposes and these data have the potential to offer broader insights on a marginalized population for which large-scale data collection initiatives may not be feasible. For this paper, the data are drawn from the Agency Data on Migration (ADMIG) Project, a survey of non-profit and community organizations on their information systems. In the survey, we also ask for blank registration and intake forms, and annual reports. From these data, the analysis will provide a profile of agencies and a description of the type of data that are collected, the gaps in data, and the degree to which we can distinguish between migrant permit types using secondary data from non-profit agencies. The results of the study will be useful for future studies on both temporary and permanent residents in other places particularly when temporary worker programs are increasing globally and in places not traditionally known to receive large flows of migrants.

Abstract: The International Conference on Population and Development (ICPD) in 1994 signaled a major breakthrough in the way governments and health professionals think about the reproductive health. Data on currently married women aged 15-49 from the 2011 Ethiopian Demographic and Health Survey were analyzed to correlate fertility decline rate and health matters. Findings show that 67 percent of population has access to any type of potential health services. In Ethiopia total fertility rate is 4.8 births per women in 2011. The maternal mortality rate, 676 per 100,000 live births and the infant mortality rate at 56 per 1,000 live births are among the highest in the world. Only 34 percent of women receive antenatal care and skilled personnel attend only 8 percent of births. Even though associations were not consistent across all indicators, spousal discussion of family planning was linked to an increased likelihood of receiving skilled antenatal care, delivery care and health services. Postnatal care is extremely low in Ethiopia. Low status of women in Ethiopia underpins and often directly undermines utilization of reproductive health services. The reproductive health care is the major issue which determines the demographic goals of any couple.

We show that Bayesian population reconstruction, a recent method for estimating past populations by age, works in a very wide variety of data quality contexts. To date, it has been shown to work only in a single case (i.e., Burkina Faso). Bayesian reconstruction simultaneously estimates age-specific population counts, fertility rates, mortality rates and net international migration flows from fragmentary data while formally accounting for measurement error. As inputs, Bayesian reconstruction takes initial bias-reduced estimates of age-specific population counts, fertility rates, survival proportions and net international migration. Here, we show that the method performs well when applied in a range of data quality contexts by reconstructing the female populations of Laos, a country with little vital registration data where population estimation depends largely on surveys, Sri Lanka, a country with some vital registration data, and New Zealand, a country with a highly developed statistical system and high-quality vital registration data. In addition, we extend the method to apply to countries without censuses at regular intervals. We also develop a method for using it to assess the consistency between model life tables and available census data, and hence to compare different model life table systems.

Despite the fact that the United Nations defined youth population to lie in the age category 15-24 long time ago, this age group haven't received a significant attention in demographic analysis and research. This definition of youth was made during preparations for the International Youth Year (1985), and endorsed by the General Assembly of the United Nations in 1981. Demography text books and references devote chapters and sections to the analysis of Age-sex composition, demographic (age) dependency ratios, women in reproductive age 15-49, working age population 15-64, and infants and children. It's clear that the analysis of youth population is absent in these main references, or to not to undermine their effort, on can say that the analysis of youth is embedded into the analysis of age-sex structure in general. Hence, a methodology for the analysis of this specific and important age group is badly needed in order to shed light on this important age group and encourage demographers to include such analysis in their research projects and publications.

We present a methodology based on Cubic Splines to fit the general mortality curve in Mexico by sex at all ages for the years of 2000, 2005 and 2010. This method consists in fitting a polynomial of degree three in the first four ages (fitting them perfectly); between ages 4 and 80 we fit a cubic spline using five nodes; we fit another third-degree polynomial beginning at age 80. We employ 24 parameters to estimate the mortality curve in the full age range. This model presents an excellent goodness of fit in men, which increases over the years; for women, the goodness of fit is, in general, better than men’s. This methodology is considered to be a relatively parsimonious estimation of mortality; it maintains the mortality curve’s changes in concavity; and it allows the realization of mortality projections in different contexts and causes of death.

Existing studies of fertility concentration have focused on nonparametric measures such as `have half', `half have', and the well-known Gini index. Here, we review the literature and discuss the nature of fertility variation, as well as the behavioural patterns leading to over- and underdispersion respectively and their theoretical implications. We demonstrate that commonly used concentration measures are less informative than is generally believed, and cannot be used to study changes in fertility variation in the presence of changes in the level of fertility, or to draw inferences about behavioural heterogeneity or change. Instead, we focus on the statistical measure of dispersion (i.e. the variance-to-mean ratio), and present a collection of empirical results on patterns of over- and underdispersion in relation to the overall level of fertility, and discuss their significance. The finding that, especially when fertility is low, instances of under-dispersion are common, which are difficult to model with the statistical toolkit customary in demographic analysis, motivates an introduction to alternative count models recently revived in the statistical literature and an examination of their ability to fit both over- and under-dispersed distributions of complete parity.

While seemingly straightforward, many common indicators of educational participation, such as enrolment ratios, are subject to distortions that are transparent from within a demographic framework, but generally ignored in the field of educational development. We propose to present on the full range of effects mentioned above at the conference, but as an example, here we elaborate in greater detail on the issue of the age composition effect.
The value of aggregate education indicators such as enrolment rates is influenced by the age structure of the population through a pure composition effect. This phenomenon is not generally acknowledged in educational statistics, much less accounted for. The scant treatment the question of age distribution has received in this context has been limited to examining it as a source of measurement error when comparing administrative and survey data sources. By using an age-standardization technique, we show how this very common demographic tool can straightforwardly be applied to educational metrics and how doing so alters the results. We conclude that the effect on net participation rates is moderate in general, but with respect to gross rates, parity indices and their changes over time, age standardization appreciably influences conclusions about educational system performance.

The association between maternal smoking during pregnancy and offspring’s birthweight reduction is very well established. However, less is known about the effect of smokeless tobacco on birthweight and about the specific mechanism through which smoking reduces birthweight. This paper aimed at filling these knowledge gaps by studying the effect of maternal Swedish snuff use during pregnancy (SUDP) on offspring’s birthweight. Swedish snuff is grounded tobacco without any toxic substance added, which provides us with the opportunity to isolate the effect of nicotine on birthweight. With data from the Swedish Medical Birth Register (2002-2009), we applied a sibling analysis using multilevel linear regression model (50,497 siblings nested within 23,443 mothers). This design has potential to study causal associations since, it accounts for unknown genetic and environmental characteristics of the mother associated to both tobacco habits and offspring birthweight. Our results show that SUDP does not have an effect on birthweight reduction.

This study presents two approaches of constructing adult mortality table or life table from an appropriate set of survival probability (p-values) from a given set of 5-year cumulative life table survival ratios (in short, 5-cum-LSRs), defined by the ratios T(x+5)/T(x), beyond age 5. The set of survival probability (p-values) over ages, so obtained, is not only consistent with the given set of 5-cum-LSRs but also satisfy the usual properties and depicts the true trends of life table p-values over ages. The two approaches for estimating survival probabilities at various quinquennial ages are as follows -- one makes use of algebraic chain relationships between two survival probabilities in the adjacent 5-year age-intervals for a given set of 5-cum-LSRs, and the other one is based on an iterative procedure under conventional and Greville’s approximations for estimating L(x, x+5) from l(x). The empirical investigations of the two approaches based on model life tables show that the estimated p-values and hence the mortality table so obtained beyond age 5 are almost identical to the true one under certain condition. The empirical and analytical investigations show that non-conventional method (that of Greville's) converges much faster than the conventional method of life table construction. Convergence can be proved mathematically .

Nigeria’s census history began in 1866; during the intervening period to date, Nigeria has had 12 censuses. Using age in single years, the census data were subjected to tests of quality by using known quality tests available. The quality of Nigeria’s most recent censuses (1991 and 2006) was assessed using the following indices to assess the extent of errors: sex and age ratios, UN joint score, Whipple’s index, modified Whipple’s index, Myers’ index and index preference. The results of these assessment showed that the quality of the censuses data are comparable to some African censuses results obtained in the 1970s and 1980s. It is thus concluded that the quality Nigeria’s age and sex data were poor.