Past and Future of Human Capital in Southeast Asia: From 1970 to 2030

This paper examines levels of educational attainment in Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam for the period 1970-2030 through the reconstruction and projection of levels of educational attainment. While the study of the past shows that the determination to invest in education has been strong in the six countries, the investments were implemented at different pace and intensity, the projections show the legacy of past investments. In Singapore, Malaysia, and Thailand, there will be tangible increases in the proportion of the working age population with a tertiary education. The Philippines will have a dichotomous society where large proportions will either have a tertiary education or only a primary education. In Indonesia, the bulk of the working age population will shift from primary in 2000 to secondary by 2030. The projection horizon and the trend type of scenario do not allow Vietnam to catch up with the other countries

Consequences of International Migration on the Size and Composition of Religious Groups in Austria

Scientific knowledge on a population’s religious composition is essential to understand the challenges faced by societies today. It arises in opposition to speculations about the actual size of religious groups that have been increasingly present in the public discourse in Europe for many years. This is particularly the case in Austria where the flows of refugees and migrants coming from the Middle East and Afghanistan have intensified since 2011 and culminated in 2015. These sparked a debate on the actual size of the Muslim population in Austria. This study fills the gap by presenting estimates of the religious composition for 2016 and projections until 2046 based on several scenarios related to the three major forces affecting the religious composition: migration (including asylum seekers), differential fertility and secularisation. The projections demonstrate that religious diversity is bound to increase, mostly through immigration and fertility. We further focus on the role and implications of international migration on the age and sex composition within the six religious groups: Roman Catholics, Protestants, Orthodox, Muslims, other religions and unaffiliated. We find that the volume and composition of international migrants can maintain youthful age compositions in minority religions—Muslims and Orthodox. Sustained immigration leads to slower ageing but does not stop or reverse the process. The disparity between older majority and younger minority religious groups will further increase the cultural generation gap

Religious Denominations in Vienna & Austria: Baseline Study for 2016-Scenarios until 2046

The publication presents the results of the research project “Religious Denominations in Vienna & Austria: Baseline study for 2016 – Scenarios until 2046” conducted by the Vienna Institute of Demography of the Austrian Academy of Sciences. The aim of this study project was twofold: Firstly, to estimate the religious composition of the population of Austria and Vienna in 2016 taking into account the most recent migration movements; and secondly, to project the population of Austria and Vienna from 2016 to 2046 based on several scenarios related mostly to the three major forces affecting religious composition, migration (including asylum-seekers), differential fertility, and religious conversion. While the projections demonstrate some of the possible futures that Austria and its capital city could experience in the coming decades, and those are all quite dissimilar, they also show that religious diversity is bound to increase, and there are no reasons to think that any of the trends that have been in place already for several decades in the country will stop and that the country would move back to the situation of the early 1970s

Global Estimates of Mean Years of Schooling: A New Methodology

The indicator of mean years of schooling (MYS) has the advantage of expressing the distribution of educational attainment in a single number. It is often used for cross-country comparisons and in economic and environmental models as the unique indicator of educational attainment and human capital stock. The computation of MYS from a given educational attainment distribution is complex for two main reasons. First, the standard duration of different levels of schooling varies from country to country, and within countries each school level can have different lengths depending on the type of studies, for example, studies of general secondary as opposed to vocational secondary. Secondly, the calculation is biased by the presence of pupils/students who do not complete the full course at any level, which can amount to a substantial share in some countries. To overcome these difficulties, the methodology used and detailed in this paper computes MYS as the weighted mean of six educational levels based on ISCED 1997 classification - no formal education, incomplete primary, completed primary, completed lower secondary, upper secondary and post-secondary education . and the procedure takes into account country-specific educational systems as well as changes in these systems over time. To adjust for the proportion with incomplete educational levels, we developed regional sets of regression models to improve estimates of MYS for the incomplete primary category and a set of correction factors to adjust higher levels. The models are built using detailed data on duration of schooling by grades completed within primary level for 54 countries. We apply the method to estimate MYS for 171 countries in the Wittgenstein Centre (WIC) dataset on educational attainment, which served as the base for the population projections by levels of education until 2100. Detailed data are available online at www.wittgensteincentre.org/dataexplorer. In the paper we compare our method and results for 2010 to the widely used Barro & Lee data and to that of UNESCO, the main provider of global data on education statistics, and explain the differences

An Evaluation of the IIASA/VID Education-Specific Back Projections

In 2007, IIASA and the Vienna Institute of Demography of the Austrian Academy of Sciences (VID) released a database reconstructing detailed information on levels of educational attainment by age (in five-year age groups from 15 to 65+ years), sex, and for every five years between 1970 and 2000 for 120 countries (see Lutz et al. 2007). This database was created in two steps. The reconstruction methodology was applied for the first time and generated what is called the Beta version of the database (unpublished). This paper presents the validation procedure that was implemented to check the plausibility of the Beta version against scattered real data from different sources, mostly from the UNESCO collection of levels of educational attainment. The verification was done by using two main indicators where a comparison was possible: Proportion of the population with no education (E1) and proportion with a tertiary education (E4). The validation procedure was a crucial factor in arriving at the present version of the database (called version 1.0). This paper also presents the results of the validation of the published version against real data, and highlights the need for the harmonization of education data to facilitate comparison over time and space

Populations for 171 Countries by Age, Sex, and Level of Education around 2010: Harmonized Estimates of the Baseline Data for the Wittgenstein Centre Projections

Data series on levels of educational attainment of the adult population consistent across time and space cannot be found as such, readily available, not in an aggregated form and not by age and sex. This is a pity because levels of educational attainment of the working age population are the main component of human capital that is used in many models, mostly related to economics, IT and health. Researchers at IIASA have developed a methodology to reconstruct and project levels of educational attainment (see Lutz et al. 2007) based on the information contained in the best source for the most recent year. An improved and increased version will become available in 2013. We are showing in this paper that it does not really make sense to keep the data as close as possible to those directly available datasets since a large majority of those suffer from severe flaws, hampering any trend and regression analysis on levels of educational attainment. We show how picking the right dataset for the starting year can be a real hassle and point towards the necessity to invest in harmonizing and mapping levels of education to facilitate academic research for the benefit of societies

Projection of Populations by Level of Educational Attainment, Age and Sex for 120 Countries for 2005-2050

Using demographic multi-state methods, this paper presents projections for the population of 120 countries (covering 93 percent of the world population in 2000) by age, sex and level of educational attainment for the years 2000 to 2050. The dataset produced gives the full educational attainment distributions for four categories (no education, primary, secondary and tertiary education) by five-year age groups, with definitions that are consistent with a previous reconstruction of educational attainment for the years 1970 to 2000. Based on empirical distributions of educational attainment by age and sex for the year 2000, the method moves along cohort lines while taking into account differentials in fertility and mortality by education level. The most extensive in time and geographical coverage to date, to our knowledge this work represents the first attempt to project future educational attainment trends based on a statistical model of historical international attainment growth. The resulting dataset provides valuable insights both on the feasibility of international education targets and on their implications for human capital and population size and age structure

Summary of Data, Assumptions and Methods for New Wittgenstein Centre for Demography and Global Human Capital (WIC) Population Projections by Age, Sex and Level of Education for 195 Countries to 2100

This paper describes the base-line data and summarizes the methodology that underlies the projections presented for 195 countries of the world by age, sex, and educational attainment, based on detailed data on education for 171 countries. These multi-dimensional cohort-component projections require a large amount of empirical information, ranging from base-year data on populations disaggregated by levels of educational attainment by age and sex, to data on educational differentials of fertility and mortality. The paper also summarizes the procedures by which the assumed trajectories for future fertility, mortality and migration were derived by combining structured expert judgments with statistical models. It also describes in detail the procedures by which assumptions on aggregate fertility, mortality and migration trends were translated into education-specific trajectories in order to then calculate the implications of alternative education scenarios