Sideline demographic methods and data

Demographic censuses usually contain information about a graded education system, i.e. age and grade declarations. This information can be used to estimate a series of indicators, useful for diagnostics and prognostics of the educational system. One of the principal goals of this paper is to provide a new demographic technique to better understand the population trends in terms of levels of schooling, in a country or region. A detailed scrutiny of the derived indicators proposed can be a powerful tool for policy makers. Our technique follows in the tradition of formal demographic methodologies used in analyzing and projecting population, such as Life Tables. Thus, one could study the probable social consequences of the implementation of any educational policies related to promotion and retention practices, over the medium and long runs. The methodological procedures were applied to the Latin American Countries, although it could be replicated or adapted to other developing countries or regions that have the usual information of grades concluded by age.
Key Words: Demographic analysis, trends and forecast of educational indicators, regional inequalities

This paper examines the reliability and stability of developmental idealism measures in Nepal. Developmental idealism is a cultural schema that contains beliefs and values favoring modern societies and families over traditional ones and that views modern families as causes and effects of modern societies. It also views the world as dynamic, with change from traditionality towards modernity. Earlier studies have shown that developmental idealism has been disseminated widely internationally, but provide little evidence concerning whether individual views of developmental idealism can be reliably measured or the extent to which such views are stable across time. We estimate reliability and stability of developmental idealism measures using panel data collected in Nepal. Our results indicate substantial levels of reliability, with levels equal to or nearly equal to reliability levels of standard value and belief items measured in general American surveys. There is also considerable stability of developmental idealism views across time.

Intercensal methods have been broadly used to estimate mortality in developed and less developed countries with deficient or incomplete data. These methods have several advantages over indirect methods because they do not require the use of model life tables and provide sufficiently accurate results even in the presence of age distortions and death under-registration. The drawback of these methods, however, is that generated life tables do not provide ex post projections of the baseline population that are consistent with the subsequent enumeration, even after adjusting for migration and age misreporting. This article demonstrates these inconsistencies by reviewing and comparing the results of three well established methods. We introduce a simple procedure to solve this inconsistency by providing life tables that are accurate and which generate identical projected and input populations. The empirical illustration demonstrating its efficacy draws on data from Vietnam, but the method can be extended to any context and time period.

An attempt has been made in this study to understand the demographic transition taking place in India, its states & below state level units using NSSO natural divisions (by using the CBR and CDR from SRS reports, 2009) as units of analysis as it may throw better insight into the demographic transition taking place below the state level units. Progress made in the fertility transition, mortality transition and the demographic transition as a whole over time was studied using the indices of fertility (FTI), mortality (MTI) and demographic transition (DTI) developed using the TFR and LEB. FTI, DTI and DTI indices are similar in structure to that of the familiar Human Development Index (HDI). The study concludes that the demographic transition in India is progressing slowly in the recent past mainly due to a slow progress in the mortality transition taking place in the Empowered Action Group of states namely Uttar Pradesh, Madhya Pradesh, Bihar, Rajasthan and Orissa. Within the states, there are differences in progress of demographic transition across NSSO natural division. Thus the future progress in the demographic transition in India entirely seems to depend on the future declines in the mortality and fertility of the EAG states.

The individual rate of aging is defined as the relative derivative of one's risk of death with respect to one's age. The b-hypothesis, formulated by Vaupel (2010), postulates that all humans share the same rate of aging. In order to check this hypothesis given the existing aggregate data on human mortality, we present several statistical approaches, their advantages and shortcomings, as well as some preliminary conclusions.

Traditional demographic methods correct adult mortality by assuming a uniform distribution of the errors in between censuses. We propose the use of quality control charts to detect which years should be corrected at a larger scale than others within inter-census periods. This methodology proves new in the area and highly improves the current available demographic methods, both for all age groups, including the oldest ages usually hard to correct with traditional methods. We used Colombian official death records from 1950 to 2010, as recorded from the Latin American Human Mortality Database (www.lamortalidad.org), and found that this methodology will enhance current available demographic methods.

Rectangularization - the development of an increasingly rectangular
shape of the survival curve - has been theoretically predicted and
empirically noted among humans in nearly all low mortality countries in
the last decade. Explanations that account for rectangularization and
test their applicability to empirical data, however, remain limited. We
propose a new approach that distinguishes between two different kinds of
rectangularization, inner and outer rectangularization. Inner
rectangularization refers to the rectangular shape produced by the
mortality schedule, whereas outer refers to the used maximum living
potential determined by the highest attained age. This allows us to
implement the Maximized Inner Rectangle Approach (MIRA), which
determines the biggest rectangle under the survival curve, thereby
enabling a decomposition of the area below and above the survival curve.
The empirical application of our models reveals that rectangular
movement is not a new development, and has been a visible feature of the
survival curve since the earliest survival data we have access to.
Furthermore, our approach provides empirical evidence against
compression as a mechanism underlying rectangularization, and supports
the explanation that rectangularization is the result of a premature
mortality decline.

In the developing world it is expected that half of the future population growth will be caused by its young population age-structure, an aspect of population dynamics that is referred to as population momentum. Less discussed is the amount of population decline that will be observed in the future in developed countries with its “negative momentum” caused by its old population age-structure. Population momentum summarizes the relation between a population age-structure and the age-structure resulting from its equivalent population under stability (growth equal to zero). Since mortality and fertility change permanently also the population momentum corresponding for each time is different. However, little work has been done to summarize time trends of this measure. We study the trends in time of population momentum for countries with available period and cohort, fertility and mortality information. Our preliminary results show clear distinction between three periods in population momentum, distinguish by their levels of fertility and mortality: high-high, high-low, and low-low, for fertility and mortality respectively. In recent years most developed countries have entered into the low-low stage and more than a decade of negative population momentum.

Applying the Statistical Technique of Principal Components Analysis to the schedules of Age-Specific Fertility Rates (ASFR) in Five year age groups for 74 countries around 1960, for 68 countries around 1970, and for 53 countries around 1980, Sivamurthy found that the First Two Principal Components accounted for about 90 percent of the total variation in observed ASFR, and the First Three Components accounted for 96–97 percent . Based on this analysis, Sivamurthy suggested a Two parameter Principal Components Model ( Sivamurthy’s PC Model) for representing ASFR schedule, which is shown to be useful in fertility estimation and projection. Since fertility situations have changed greatly in most of the countries in recent decades, Sivamurthy and Chetna applied the same PC Analysis to the ASFR schedules of 88 countries for the years around 2001, and found that the First Three Principal Components accounted for 92 percent of the total variation in ASFR. Based on this analysis Sivamurthy and Chetna suggested Revised Sivamurthy’s PC Model for ASFR schedule, which can be used for projecting ASFR. A simple procedure is suggested for estimating the three parameters of the Model. The procedure is applied to the Indian data for illustration.

This paper aims to forecast the probability of progression to the secondary education level for Brazilian men and women aged 25-59. The authors used an age-period-cohort model and a time-series approach to model and forecast future trends in period and cohort effects. To account for uncertainty, this study utilized a scenario approach. The authors carried out separate models for males and females in order to account to sex differentials in the progression probability. Data were selected from the National Household Survey in Brazil (PNAD), which offers nationally representative data from 1981 to 2011. This study concludes that there will be improvements in this indicator for both men and women, and that the rate of improvement will be higher for older adults because they start at a lower probability level. Also, these results show that the probability of progression to the secondary education level is slightly lower for men, even though both men and women will experience improvements in this indicator.