The Rise of Global Human Capital and the End of World Population Growth

2017 ◽  
Author(s):  
Wolfgang Lutz ◽  
KC Samir
Keyword(s):  
Human Capital ◽  
Social Change ◽  
Educational Attainment ◽  
Economic Change ◽  
Adult Population ◽  
Social Structures ◽  
Historical Period ◽  
The World ◽  
Over Time ◽  
Age And Sex

This is the first of three chapters that present the population projections by age, sex, and level of educational attainment for all countries in the world with a time horizon of 2060, and extensions to 2100. Before discussing the Wittgenstein Centre for Demography and Global Human Capital (WIC) projections, however, it is worth stepping back to consider how social structures change over time. While understanding the evolution of social structures is important under the conventional demographic approach that breaks down populations by age and sex, a more in-depth understanding of the changes in human capital requires that the interplay between different levels of schooling over time (the flow variable), and the changing educational attainment composition of the adult population (the stock variable) be taken into account. Societies can be stratified along several dimensions. In conventional social science the divisions studied refer to social class, race, or ethnicity. Demographers routinely break down populations by age and sex. Another important demographic dimension is that of birth cohorts or generations, that is, persons born and socialized during the same historical period. Particularly during periods of rapid social change, young cohorts tend to differ from older ones in important respects, and the demographic process of generational replacement is a powerful driver of socio-economic change. This process is analytically described by the theory of ‘Demographic Metabolism’, recently introduced as a generalized predictive demographic theory of socio-economic change by the first author (Lutz, 2013), building on earlier work by Mannheim (1952) and Ryder (1965). Ryder, who introduced the notion of Demographic Metabolism in a qualitative way, saw it as the main force of social change. While this theory applies to many stable human characteristics that are acquired at young age and remain invariant over a lifetime, it is particularly appropriate for studying and modelling the dynamics of the change in the distributions of highest educational attainment by age and sex over time. This perspective on human capital formation is the main focus of this book. This first of the three results chapters will highlight the results with respect to future population numbers by level of education in different parts of the world.

Linguistic failures

English Today ◽  
2007 ◽  
Vol 23 (1) ◽  
pp. 61-64 ◽  
Author(s):  
Niu Qiang ◽  
Martin Wolff
Keyword(s):  
Contract Law ◽  
Social Structures ◽  
Language And Culture ◽  
International Language ◽  
The World ◽  
Global Spread ◽  
The Status ◽  
China Today ◽  
World Maritime ◽  
Over Time

Heart-felt opposition to the status and spread of English in the world at large and most particularly in China today. It can hardly be denied that England has given the world maritime law, contract law, and an international language. However, whether by accident or design, the effect of these ‘gifts’ over time has, we would argue, been the destruction of many ethnic customs, social structures, and other aspects of culture. There appears to be little or no dissent among linguists regarding the proposition that language and culture are inseparable: what affects one affects the other.This paper discusses how the global spread of English has affected – deleteriously – many languages and cultures, and currently engages too much time and too many resources in China today. Maritime and contract law may have been less problematic.

The Kitchen Sink

2018 ◽  
Author(s):  
Gary Smith
Keyword(s):  
Multiple Regression ◽  
Historical Period ◽  
Scatter Plot ◽  
Consumer Spending ◽  
Explanatory Variables ◽  
The World ◽  
Scatter Plots ◽  
Using Data ◽  
The One ◽  
Over Time

Back in the 1980s, I talked to an economics professor who made forecasts for a large bank based on simple correlations like the one in Figure 1. If he wanted to forecast consumer spending, he made a scatter plot of income and spending and used a transparent ruler to draw a line that seemed to fit the data. If the scatter looked like Figure 1, then when income went up, he predicted that spending would go up. The problem with his simple scatter plots is that the world is not simple. Income affects spending, but so does wealth. What if this professor happened to draw his scatter plot using data from a historical period in which income rose (increasing spending) but the stock market crashed (reducing spending) and the wealth effect was more powerful than the income effect, so that spending declined, as in Figure 2? The professor’s scatter plot of spending and income will indicate that an increase in income reduces spending. Then, when he tries to forecast spending for a period when income and wealth both increase, his prediction of a decline in spending will be disastrously wrong. Multiple regression to the rescue. Multiple regression models have multiple explanatory variables. For example, a model of consumer spending might be: C = a + bY + cW where C is consumer spending, Y is household income, and W is wealth. The order in which the explanatory variables are listed does not matter. What does matter is which variables are included in the model and which are left out. A large part of the art of regression analysis is choosing explanatory variables that are important and ignoring those that are unimportant. The coefficient b measures the effect on spending of an increase in income, holding wealth constant, and c measures the effect on spending of an increase in wealth, holding income constant. The math for estimating these coefficients is complicated but the principle is simple: choose the estimates that give the best predictions of consumer spending for the data used to estimate the model. In Chapter 4, we saw that spurious correlations can appear when we compare variables like spending, income, and wealth that all tend to increase over time.

Wage Differences between Polish and Romanian Intra-EU Migrants in a Flexi-Secure Labour Market: An Over-Time Perspective

2021 ◽  
pp. 095001702110562
Author(s):  
Jonas Felbo-Kolding ◽  
Janine Leschke
Keyword(s):  
Human Capital ◽  
Time Perspective ◽  
Language Education ◽  
Social Structures ◽  
Further Training ◽  
Wage Differences ◽  
Positive Return ◽  
Over Time ◽  
The Eu

By merging longitudinal register data and a customised survey, this article explores whether sectoral segmentation, migrants’ pre- and post-migration human capital and social structures, shape wages of Polish and Romanian long-term migrants to Denmark. Pronounced wage differences in favour of Polish migrants are evident in the first two years in Denmark, notwithstanding the same regulatory context under the free movement of labour in the EU. Wage differences persist – albeit at a considerably lower level – throughout the eight-year period, mainly because of significant sectoral segmentation. Sectoral segmentation not explained by demographics, pre-migration human capital or crisis effects, might indicate categorical stereotyping by employers. Regarding (co-ethnic) social networks, at least for the early stages of migration, the study does not find significant effects on wages. While the evidence shows a positive return on wages of formal higher education taken post migration, this is not the case for further training and Danish language education.

Data and Methods

2017 ◽  
Author(s):  
KC Samir ◽  
Michaela PotanČoková
Keyword(s):  
Human Capital ◽  
Educational Attainment ◽  
Expert Knowledge ◽  
Population Projections ◽  
World Population ◽  
International Institute ◽  
Future Fertility ◽  
The World ◽  
And Migration

The preceding chapters have all contributed to building the knowledge base for the actual Wittgenstein Centre for Demography and Global Human Capital (WIC) projections that will be presented and discussed in the second part of this book. This chapter stands as a bridge between the two parts. Its focus is the translation and operationalization of the empirical evidence and the substantive arguments presented so far into specific population projections by age, sex, and level of educational attainment for all countries in the world. This is a complex exercise in which data and methodology play the crucial roles. The cohort–component multidimensional projections presented in this volume require a large amount of information, ranging from base-year data on population disaggregated by levels of educational attainment by age and sex, to data on fertility, mortality, and migration by age, sex, and education for the base year, and, finally, to the assumed numerical values of these determinants according to the different scenarios. This new set of expert argument-based projections by age, sex, and educational attainment presents an important new step at the forefront of international population projections. As discussed in Chapter 1, this is a logical next step in the tradition of international population projections by the World Population Program of the International Institute for Applied Systems Analysis (IIASA). This effort also goes beyond what the United Nations (UN) and other agencies have been doing in two important ways: it provides the most comprehensive and systematic summary of expert knowledge on future fertility, mortality, and migration to date—including the input of hundreds of demographers from around the world—and it translates this into the most comprehensive set of human capital projections for 195 countries. The WIC projections cover all countries in the world with more than 100,000 inhabitants. In this effort, the study builds on and significantly expands earlier IIASA reconstructions and projections of the population by age, sex, and educational attainment for 120 countries published in 2007 and 2010 (KC et al., 2010; Lutz et al., 2007).

scholarly journals How Education Drives Demography and Knowledge Informs Projections

2017 ◽  
Author(s):  
Wolfgang Lutz ◽  
Vegard Skirbekk
Keyword(s):  
Human Capital ◽  
Educational Attainment ◽  
Review Article ◽  
Population Heterogeneity ◽  
Population Projections ◽  
Demographic Analysis ◽  
Underlying Assumption ◽  
Economic Implications ◽  
Explicit Consideration ◽  
Age And Sex

This chapter provides the background necessary for understanding our approach to projecting population and human capital. First, we investigate the proper place of education in demographic analysis and the evidence for an underlying causal relationship between education and demographic outcomes. Second, we emphasize the importance of explicit assumptions undergirding population projections and detail our procedures for incorporating the views of hundreds of experts into sets of assumptions that drive the Wittgenstein Centre (WIC) projections. Subsequent chapters build on this background in their detailed discussions of trends and arguments in fertility, mortality, migration, and education. A major innovative feature of this volume is the systematic addition of educational attainment as a standard demographic dimension in addition to age and sex for demographic analyses, particularly for projections. The underlying assumption is that educational attainment is not just one of many socio-economic factors that matter for population, as it is often viewed in conventional demographic analysis, but is the single most important source of empirically observable population heterogeneity next to age and sex. The suggestion of routinely adding educational attainment as a dimension of demographic analysis is not new. It was first proposed in a Population and Development Review article by Lutz et al. (1998), entitled ‘Adding Education to Age and Sex’. More recently, the idea of adding the education factor to demographic analysis was discussed by Lutz (2010) in a commentary entitled, ‘Education Will be at the Heart of 21st Century Demography’. It has also been the focus of two recent articles by Lutz and KC, one published in Philosophical Transactions entitled, ‘Dimensions of Global Population Projections’ (2010), and a review article published in Science entitled, ‘Global Human Capital: Integrating Education and Population’ (2011). In the latter paper they argue that an additional demographic dimension should be added routinely to age and sex in population analyses and projections according to three criteria: (i) its explicit consideration should be feasible in terms of available data and methodology; (ii) it should matter substantially in terms of altering population dynamics; and (iii) it should be of interest in its own right in terms of its social and economic implications.

scholarly journals Examining the Poverty Human Capital and Economic Development Nexus in Pakistan: Evidence from Southern Punjab

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Salyha Zulfiqar Ali Shah ◽  
Imran Sharif Chaudhry ◽  
Fatima Farooq
Keyword(s):  
Human Capital ◽  
Economic Development ◽  
Vocational Training ◽  
Household Survey ◽  
Vital Role ◽  
Influential Factor ◽  
Primary Data ◽  
The World ◽  
Training Schools ◽  
Over Time

Different socioeconomic and demographic characteristics of households have been examined over time, across the world. Developing countries are struggling and striving to achieve the path of economic development. The present study has based on primary data, collected through a household survey during the year 2019. Human capital constitutes education, health, skills and on-the-job training are the most significantly related to the prosperity of the households. The results of the study conclude human capital is the most significant and influential factor that would play a vital role in promoting the prosperity and development of the Southern Punjab, Pakistan. Government should develop various projects to promote education in Pakistan. Vocational training schools would help to enhance the skills of the households.

When the “We” Impacts How “I” Feel About Myself

2010 ◽  
Vol 15 (4) ◽  
pp. 271-282 ◽  
Author(s):  
Roxane de la Sablonnière ◽  
Émilie Auger ◽  
Nazgul Sadykova ◽  
Donald M. Taylor
Keyword(s):  
Social Change ◽  
Relative Deprivation ◽  
Past Research ◽  
Well Being ◽  
Multiple Points ◽  
The Past ◽  
The World ◽  
Entire Trajectory ◽  
Dominant Theory ◽  
Over Time

Dramatic social change leads to profound societal transformations in many countries around the world. The two recent revolutions in March 2005 and April 2010, and the ethnic conflict in June 2010 in Kyrgyzstan are vivid examples. The present research aims to understand people’s reactions to dramatic social change in terms of personal well-being. To further understand how people react psychologically to dramatic social change, the theoretical framework of our research is based on a dominant theory in social psychology: Collective relative deprivation theory. In the past, researchers have argued that collective relative deprivation is logically associated with collective outcomes, and thus is not likely to impact personal well-being (e.g., Walker & Mann, 1987 ). Others, however, have argued that feelings of collective relative deprivation do impact personal well-being (e.g., Zagefka & Brown, 2005 ). We postulate that these inconsistent results arise because past research has failed to consider multiple points of comparison over time to assess collective relative deprivation. Specifically, we theorize that multiple points of collective relative deprivation need to be taken into account, and in so doing, collective relative deprivation will, indeed, be related to personal well-being. We also explore the entire trajectory of collective relative deprivation (which represents how an individual perceives the evolution of his/her group’s history across time) to predict personal well-being. In the present study, we tested these theoretical propositions in the context of dramatic social change in Kyrgyzstan. Regressions, group-based trajectory modeling, and MANOVA confirm our hypotheses.

scholarly journals EPISTEME AIMS OF EDUCATION

2021 ◽  
Vol 38 ◽  
pp. 202-220
Author(s):  
Sohni Siddiqui ◽  
Naureen Nazar Soomro ◽  
Reena Majid Memon
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Adult Population ◽  
Developed Countries ◽  
Quality Education ◽  
The Past ◽  
The World ◽  
Creative Learning ◽  
Comprehensive Curriculum ◽  
And Training

Finland educational system is among the top systems in the world and Finnish students have proven themselves as intellects and responsible citizens in the past. In contrast, Pakistan is facing substantial education challenges and despite efforts been made, providing quality education to all children is still a dream. More than half of the adult population is not able to read and write, and there is huge inadequacy of skilled human resource that can impact the economy of the country. Malaysia, like other developed countries, has recognized importance of lifelong learning and is advancing it as a major source for economic growth. Competence, skills needed to ensure holistic growth of students is mentioned explicitly. Besides comprehensive curriculum development, Malaysia introduces such programs as to generate human capital by means of education and training. The creative learning environment and constant encouragement to students is provided to focus on latest skills that are need of the labour market. In Pakistan, it seems curriculum is properly documented with clear aims of what excellences to be fostered in individual but how to foster such excellence is missing.

Globalization and interconfessional communications

2001 ◽  
pp. 13-17
Author(s):  
Serhii Viktorovych Svystunov
Keyword(s):  
21St Century ◽  
Global Economy ◽  
Modern World ◽  
The World ◽  
Target Set ◽  
Almost All ◽  
Over Time ◽  
Rapid Appearance

In the 21st century, the world became a sign of globalization: global conflicts, global disasters, global economy, global Internet, etc. The Polish researcher Casimir Zhigulsky defines globalization as a kind of process, that is, the target set of characteristic changes that develop over time and occur in the modern world. These changes in general are reduced to mutual rapprochement, reduction of distances, the rapid appearance of a large number of different connections, contacts, exchanges, and to increase the dependence of society in almost all spheres of his life from what is happening in other, often very remote regions of the world.

BIOASSAY CHARACTERISTICS OF INDIVIDUAL URINARY GONADOTROPHIN EXTRACTS

1963 ◽  
Vol 42 (2) ◽  
pp. 214-224
Author(s):  
Raymond C. Mellinger ◽  
Jalileh A. Mansour ◽  
Richmond W. Smith
Keyword(s):  
Reference Material ◽  
Young Women ◽  
Reference Standard ◽  
General Acceptance ◽  
Modifying Factors ◽  
Large Numbers ◽  
The World ◽  
Quantitative Bioassay ◽  
Different Parts ◽  
Age And Sex

ABSTRACT A reference standard is widely sought for use in the quantitative bioassay of pituitary gonadotrophin recovered from urine. The biologic similarity of pooled urinary extracts obtained from large numbers of subjects, utilizing groups of different age and sex, preparing and assaying the materials by varying techniques in different parts of the world, has lead to a general acceptance of such preparations as international gonadotrophin reference standards. In the present study, however, the extract of pooled urine from a small number of young women is shown to produce a significantly different bioassay response from that of the reference materials. Gonadotrophins of individual subjects likewise varied from the multiple subject standards in many instances. The cause of these differences is thought to be due to the modifying influence of non-hormonal substances extracted from urine with the gonadotrophin and not necessarily to variations in the gonadotrophins themselves. Such modifying factors might have similar effects in a comparative assay of pooled extracts contributed by many subjects, but produce significant variations when material from individual subjects is compared. It is concluded that the expression of potency of a gonadotrophic extract in terms of pooled reference material to which it is not essentially similar may diminish rather than enhance the validity of the assay.

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