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This article presents a narrative of the unfolding of the Second Demographic Transition (SDT) since the theory was first formulated in 1986. The first part recapitulates the foundations of the theory, and documents the spread of the SDT to the point that it now covers most European populations. Also for Europe, it focuses on the relationship between the SDT and the growing heterogeneity in period fertility levels. It is shown that the current positive relationship between SDT and TFR levels is not a violation of the SDT theory, but the outcome of a \"split correlation\" with different sub-narratives concerning the onset of fertility postponement and the degree of subsequent recuperation in two parts of Europe. The second part of the article addresses the issue of whether the SDT has spread or is currently spreading in industrialized Asian countries. Evidence gathered for Japan, South Korea, Hong Kong, Singapore, and Taiwan is presented. That evidence pertains to both the macro-level (national trends in postponement of marriage and parenthood, rise of cohabitation) and the micro-level (connections between individual values orientations and postponement of parenthood). Strong similarities are found with SDT patterns in Southern Europe, except for the fact that parenthood is still very rare among Asian cohabiting partners.

Over the past 25 years, technological improvements that have made the collection, transmission, storage, and analysis of data significantly easier and more cost efficient have ushered in what has been described as the 'big data' era or the 'data revolution'. In the social sciences context, the data revolution has often been characterized in terms of increased volume and variety of data, and much excitement has focused on the growing opportunity to repurpose data that are the by-products of the digitalization of social life for research. However, many features of the data revolution are not new for demographers, who have long used large-scale population data and been accustomed to repurposing imperfect data not originally collected for research. Nevertheless, I argue that demography, too, has been affected by the data revolution, and the data ecosystem for demographic research has been significantly enriched. These developments have occurred across two dimensions. The first involves the augmented granularity, variety, and opportunities for linkage that have bolstered the capabilities of 'old' big population data sources, such as censuses, administrative data, and surveys. The second involves the growing interest in and use of 'new' big data sources, such as 'digital traces' generated through internet and mobile phone use, and related to this, the emergence of 'digital demography'. These developments have enabled new opportunities and offer much promise moving forward, but they also raise important ethical, technical, and conceptual challenges for the field.

The world population will reach 7 billion in late 2011, a demographic milestone that is causing renewed attention to the challenges caused by population growth. This article looks at the last 50 years of demographic change, one of the most extraordinary periods in demographic history. During this period, world population grew at rates that have never been seen before and will almost surely never be seen again. There were many concerns about the potential impact of rapid population growth in the 1960s, including mass starvation in countries such as India, depletion of nonrenewable resources, and increased poverty in low-income countries. The actual experience was very different. World food production increased faster than world population in every decade since the 1960s, resource prices fell during most of the period, and poverty declined significantly in much of the developing world. The article considers the economic and demographic explanations for the surprising successes of this important period in demographic history. It also looks at regions that have been less successful, especially Africa, and at the lessons for dealing with the important challenges that still remain.

This article explores new methods for gathering and analyzing spatially rich demographic data using mobile phones. It describes a pilot study (the Human Mobility Project) in which volunteers around the world were successfully recruited to share GPS and cellular tower information on their trajectories and respond to dynamic, location-based surveys using an open-source Android application. The pilot study illustrates the great potential of mobile phone methodology for moving spatial measures beyond residential census units and investigating a range of important social phenomena, including the heterogeneity of activity spaces, the dynamic nature of spatial segregation, and the contextual dependence of subjective well-being.

In this paper, we examine how business cycles affect labor market outcomes in the United States. We conduct a detailed analysis of how cycles affect outcomes differentially across persons of differing age, education, race, and gender, and we compare the cyclical sensitivity during the Great Recession to that in the early 1980s recession. We present raw tabulations and estimate a state panel data model that leverages variation across U.S. states in the timing and severity of business cycles. We find that the impacts of the Great Recession are not uniform across demographic groups and have been felt most strongly for men, black and Hispanic workers, youth, and low-education workers. These dramatic differences in the cyclicality across demographic groups are remarkably stable across three decades of time and throughout recessionary periods and expansionary periods. For the 2007 recession, these differences are largely explained by differences in exposure to cycles across industry-occupation employment.

It has long been hypothesized that individuals' migration propensities depend on their risk attitudes, but the empirical evidence has been limited and indirect. We use newly available data from the German Socio-Economic Panel to measure directly the relationship between migration and risk attitudes. We find that individuals who are more willing to take risks are more likely to migrate. Our estimates are substantial compared to unconditional migration probabilities, as well the effects of conventional determinants of migration, and are robust to controlling for a variety of demographic characteristics. We find no evidence that our results are the result of reverse causality.

Demographers study population change across time and place, and traditionally they place a strong emphasis on a long-range view of population change. This paper builds on current reflections on how to structure the study of population change and proposes a two-stage perspective. The first stage, discovery, focuses on the production of novel evidence at the population level. The second stage, explanation, develops accounts of demographic change and tests how the action and interaction of individuals generate what is discovered in the first stage. This explanatory stage also provides the foundation for the prediction of demographic change. The transformation of micro-level actions and interactions into macro-level population outcomes is identified as a key challenge for the second stage. Specific instances of research are discussed.

The sheer impact of the recent global financial turmoil and scandals (such as Enron and WorldCom) has demonstrated that unbridled commercial entrepreneurs who are allowed to pursue their short-term opportunities regardless of the consequences has led to a massive depreciation of the wealth of nations, social livelihood and environmental degradation. This article suggests that the time has come for entrepreneurs to adopt a more integrad ve view of business that blends economic, social and environmental values. Social entrepreneurs present such a proposition through their deep commitment towards the social vision, appreciation of sustainable practices, innovativeness, ability to build social networks and also generate viable financial returns. It could be expected that social entrepreneurs often possess certain distinct personality characteristics which define their behaviours/actions. Personality traits are partly developed by innate nurturing, socialization and education. These tacit traits are also formed values/beliefs held and play an important role in driving social entrepreneurial decision making. Thus, personality traits may influence the intentions and the manner in which the individual acts. We hold that if social entrepreneurship is to be effective and impactful, business and management education can facilitate the development of these critical personality traits. Thus, this study primes at determining the personality traits that influence social entrepreneurs' start-up intentions. It also reinforces the findings that personality traits do influence entrepreneurship in general. This study examines the influence of the Big Five personality traits on social entrepreneurship dimensions. The findings reveal that agreeableness positively influences all dimensions of social entrepreneurship, whereas openness exerts a positive influence on social vision, innovation and financial returns. Methodologically, this study develops valid and reliable scales for social entrepreneurship and verifies the adopted Big Five personality measure of Schmit et al. (Pers Psychol 53: 153-193, 2000) using the five-point Likert scale. The implication of this study is that element of appreciation of social responsibility, sustainability and character development needs to be integrated within the business education curriculum to support social entrepreneurs in realizing genuine value and impact to the causes and communities they serve. Future business leaders also need to be equipped with entrepreneurship skills, while exuding independent and reflective thinking in the pursuit life-long learning. The originality of this study lies in its focus on personality traits on social rather than commercial entrepreneurship. It is hoped that the findings will trigger a paradigm shift towards greater social entrepreneurship through education by nurturing sustainable development values in future business graduates.

Taller populations are typically richer populations, and taller individuals live longer and earn more. In consequence, adult height has recently become a focus in understanding the relationship between health and wealth. We investigate the childhood determinants of population adult height, focusing on the respective roles of income and of disease. Across a range of European countries and the United States, we find a strong inverse relationship between postneonatal (ages 1 month to 1 year) mortality, interpreted as a measure of the disease and nutritional burden in childhood, and the mean height of those children as adults. Consistent with these findings, we develop a model of selection and stunting in which the early-life burden of undernutrition and disease not only is responsible for mortality in childhood but also leaves a residue of long-term health risks for survivors, risks that express themselves in adult height and in late-life disease. The model predicts that at sufficiently high mortality levels, selection can dominate scarring, leaving a taller population of survivors. We find evidence of this effect in the poorest and highest-mortality countries of the world, supplementing recent findings on the effects of the Great Chinese Famine.