Guy J. Abel

Quantifying Global International Migration Flows

Monitoring Migration Migrant “stock” data—the number of people living in a country other than the one in which they were born—are frequently used to understand contemporary trends in international migration, but the data are severely limited. Abel and Sander (p. 1520) present a set of global bilateral migration flows estimated from sequential stock data in 5-year intervals. The percentage of the world population moving over 5-year periods has not shown dramatic changes between 1995 and 2010. People from individual African countries tended to move within the continent, whereas people from Europe tended to move to very diverse locations. Estimates are provided for the international flow of people over 5-year periods between 1990 and 2010. Widely available data on the number of people living outside of their country of birth do not adequately capture contemporary intensities and patterns of global migration flows. We present data on bilateral flows between 196 countries from 1990 through 2010 that provide a comprehensive view of international migration flows. Our data suggest a stable intensity of global 5-year migration flows at ~0.6% of world population since 1995. In addition, the results aid the interpretation of trends and patterns of migration flows to and from individual countries by placing them in a regional or global context. We estimate the largest movements to occur between South and West Asia, from Latin to North America, and within Africa.

Meeting the Sustainable Development Goals leads to lower world population growth

Significance The future of world population growth matters for future human well-being and interactions with the natural environment. We show the extent to which world population growth could be reduced by fully implementing the Sustainable Development Goals (SDGs) whose health and education targets have direct and indirect consequences on future mortality and fertility trends. Although this assessment is consistent with the Shared Socioeconomic Pathways scenarios used in the Intergovernmental Panel on Climate Change context, it is inconsistent with the prediction range of the United Nations projections for which we present sensitivity analyses and suggests that their range is likely too narrow. Given our assumptions, the SDGs have a sizable effect on global population growth, providing an additional rationale for vigorously pursuing their implementation. Here we show the extent to which the expected world population growth could be lowered by successfully implementing the recently agreed-upon Sustainable Development Goals (SDGs). The SDGs include specific quantitative targets on mortality, reproductive health, and education for all girls by 2030, measures that will directly and indirectly affect future demographic trends. Based on a multidimensional model of population dynamics that stratifies national populations by age, sex, and level of education with educational fertility and mortality differentials, we translate these goals into SDG population scenarios, resulting in population sizes between 8.2 and 8.7 billion in 2100. Because these results lie outside the 95% prediction range given by the 2015 United Nations probabilistic population projections, we complement the study with sensitivity analyses of these projections that suggest that those prediction intervals are too narrow because of uncertainty in baseline data, conservative assumptions on correlations, and the possibility of new policies influencing these trends. Although the analysis presented here rests on several assumptions about the implementation of the SDGs and the persistence of educational, fertility, and mortality differentials, it quantitatively illustrates the view that demography is not destiny and that policies can make a decisive difference. In particular, advances in female education and reproductive health can contribute greatly to reducing world population growth.

Does Specification Matter? Experiments with Simple Multiregional Probabilistic Population Projections

Population projection models that introduce uncertainty are a growing subset of projection models in general. In this paper we focus on the importance of decisions made with regard to the model specifications adopted. We compare the forecasts and prediction intervals associated with four simple regional population projection models: an overall growth rate model, a component model with net migration, a component model with in-migration and out-migration rates, and a multiregional model with destination-specific out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destination-specific out-migration for the North, Midlands, and South regions in England. They are also used to forecast different international migration measures. The base data represent a time series of annual data provided by the Office for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals differ for the multiregional model in comparison to other simpler models, as well as for different assumptions about international migration. The paper ends with a discussion of our results and possible directions for future research.

Estimates of global bilateral migration flows by gender between 1960 and 2010

An indirect estimation method is used to derive country to country migration flows from changes in global bilateral stock data. Estimates are obtained over five- and 10-year periods between 1960 and 2015 by gender, providing a comprehensive picture of past migration patterns. The estimated total of global international migrant flows generally increases over the 55-year time frame. The global rate of migration over five- and 10-year periods fluctuate at around 0.65 and 1.25 percent of the population, respectively. The sensitivity of estimates to alternative input stock and demographic data are explored.

Using Twitter Data to Estimate the Relationship between Short-term Mobility and Long-term Migration

Migration estimates are sensitive to definitions of time interval and duration. For example, when does a tourist become a migrant? As a result, harmonizing across different kinds of estimates or data sources can be difficult. Moreover in countries like the United States, that do not have a national registry system, estimates of internal migration typically rely on survey data that can require over a year from data collection to publication. In addition, each survey can ask only a limited set questions about migration (e.g., where did you live a year ago? where did you live five years ago?). We leverage a sample of geo-referenced Twitter tweets for about 62,000 users, spanning the period between 2010 and 2016, to estimate a series of US internal migration flows under varying time intervals and durations. Our findings, expressed in terms of migration curves, document, for the first time, the relationships between short-term mobility and long-term migration. The results open new avenues for demographic research. More specifically, future directions include the use of migration curves to produce probabilistic estimates of long-term migration from short-term (and vice versa) and to nowcast mobility rates at different levels of spatial and temporal granularity using a combination of previously published American Community Survey data and up-to-date data from a panel of Twitter users.

Climate Vulnerability and Human Migration in Global Perspective

The relationship between climate change and human migration is not homogenous and depends critically on the differential vulnerability of population and places. If places and populations are not vulnerable, or susceptible, to climate change, then the climate–migration relationship may not materialize. The key to understanding and, from a policy perspective, planning for whether and how climate change will impact future migration patterns is therefore knowledge of the link between climate vulnerability and migration. However, beyond specific case studies, little is known about this association in global perspective. We therefore provide a descriptive, country-level portrait of this relationship. We show that the negative association between climate vulnerability and international migration holds only for countries least vulnerable to climate change, which suggests the potential for trapped populations in more vulnerable countries. However, when analyzed separately by life supporting sector (food, water, health, ecosystem services, human habitat, and infrastructure) and vulnerability dimension (exposure, sensitivity, and adaptive capacity), we detect evidence of a relationship among more, but not the most, vulnerable countries. The bilateral (i.e., country-to-country) migration show that, on average, people move from countries of higher vulnerability to lower vulnerability, reducing global risk by 15%. This finding is consistent with the idea that migration is a climate adaptation strategy. Still, ~6% of bilateral migration is maladaptive with respect to climate change, with some movement toward countries with greater climate change vulnerability.

Circular visualization of China’s internal migration flows 2010–2015:

We adapted the chord diagram plot to visualize China’s recent inter-provincial migration during 2010–2015. The arrowheads were added to present the direction of the flows. This method allows us to show the complete migration flows between 31 provinces in China including the direction and volume of the flows. The spatial component was also clearly depicted in the plot using four color palates representing four regions in China (i.e. East, Center, West, Northeast) and arranging the 31 provinces in an approximate geographic order. Besides that, we extend the chord diagram plot to describe China’s bilateral net migration during 2010–2015.

Changing internal migration flows patterns in South Korea

Abstract In comparison with other developed nations, there is a relative lack of analyses on internal migration flow in South Korea. During the last 50 years, the country has witnessed distinct changes in both the levels and patterns of internal migration. Traditionally, the faster developing north-west administrative units (Seoul, Incheon and Gyeonggi regions) have accounted for the majority of in-migration. However, since 2011, internal migration in Korea has become more diffuse, with migrants moving to a greater variety of regions. We visualize these changes using chord diagram plots.

Subnational gender balances in South Korea

Within one generation, the South Korean economy developed from one of the poorest countries in the world during the 1950s to a developed, high-income country by the end of the 1990s. During the latter part of this period, South Korea (hereafter called Korea) experienced rapid demographic change characterized by a steep decline in fertility levels and abnormally high sex ratios at birth. Unlike other East and South-East Asian countries that underwent similar economic and demographic changes, Korea has witnessed a steady decline in the sex ratios at birth since the end of 1990s through 2000s. In this paper, we visualize the current spatial distribution of population born during the peak years of sex ratios at birth.