Internal and International Migration

Chapter

Abstract

The discussion surrounding how countries in sub-Saharan Africa can reap the benefits of a demographic dividend needs to pay closer attention to the effects of internal and international migration flows. Surprisingly little attention has been paid to the ways in which migration alters the relative size of the working age population, the ratio of children to the total population, and the education level of a population, all of which are key variables in the discussion of the demographic dividend. This chapter aims to address this gap in the literature by drawing on two new datasets on internal and international migration flows as well as an innovative visualization of migration systems. The data suggests that, during the period 1990–2010, the spatial patterns of migration flows in sub-Saharan Africa were distinctive from those observed in the more developed world. Economic factors seem to play a less important role in shaping migration compared to violent conflict and political unrest. The results point to three clusters of countries between which migration flows are concentrated, underlining the importance of the regionalization of migration within sub-Saharan Africa.

1 Introduction

The surge of African migrants and asylum seekers attempting the risky voyage across the Mediterranean in 2014 and early 2015 has brought international migration to the front pages of newspapers, fuelling public anxiety about a looming European migration crisis caused by large uncontrolled inflows from sub-Saharan Africa. Future population growth is often associated with an imminent increase in emigration from the African continent to the Western world. How the European Union should respond to the rising influx and whether to relax or restrict immigration are hotly debated issues, but, unfortunately, political rhetoric and populist media dominate at the expense of fact-based discussions. In the countries of origin in sub-Saharan Africa, debates tend to focus on ways of reducing the emigration of skilled Africans to Western countries and on how to combat human trafficking and smuggling. Although the scientific community is well-equipped to inform public and political debates on migration, little attention has been paid to establishing a comprehensive picture of migrationflows within and away from sub-Saharan Africa. Research on migration around the globe and variations across countries has been hindered by a lack of comparable statistics on internal and international migration flows. The dearth of understanding regarding where people move in the world has inhibited research on the links between the demographic transition and migration.. Hence, the existing literature on the demographic dividend has been rather cautious about grappling with the complexities of migration.

This chapter summarizes the available evidence on the patterns and trends in internal and international migration in sub-Saharan Africa over the period 1990–2010. We take advantage of two newly available datasets on internal and international migration around the globe, allowing us to compare these migrationflows across the region and place them in a global context (Abel and Sander 2014; Bell et al. 2014). The forces which shape migration are summarized in the next section, followed by a discussion of the available data on internal and international movements. Thereafter, there are two sections which provide analyses of spatial patterns of migration in sub-Saharan Africa in a global context. Firstly, key trends occurring in global international migration flows are presented together with relationships between within-sub-Saharan African movements and levels of economic development. Secondly, patterns of internal migration are examined for selected countries in the region, followed by a discussion of links between internal and international migration. By way of conclusion, we provide an outlook on the future of migration in sub-Saharan Africa and its potential impact on future population change in the coming decades.

2 Why People Move

Migration as a means by which people aim to improve their financial and social wellbeing is not a new phenomenon. In fact, the migratory paths of our ancestors can be traced as far back as 200,000 years1. The reasons why people move are often complex and typically involve a mixture of motives related to income, family, housing, and education. The determinants of migration have traditionally been studied with reference to Lee’s push-pull migration model (Lee 1966). Based largely on the determinants of migration that have been observed in the developed world, the push-pull model suggests that uneven processes of development are at the core of factors that explain migrationflows between regions as well as between countries. According to Lee (1966), wage differentials are a key determinant of migration, although people living in the poorest countries are usually not the most likely to migrate due to a lack of resources necessary to realize a move. The notion that (economic) opportunities at the destination and deficiencies at the origin trigger migration is admittedly a rather simplified view of the migration decision-making process, as it overlooks a number of non-economic factors that play an important role in shaping migration in sub-Saharan Africa, most notably violent conflict, environmental change, and the demographic transition.

Violent conflict is associated with vast population displacements out of conflict zones, often into neighboring countries, and thus causes a shock to the migration system that is extremely difficult to foresee. The United Nations High Commissioner for Refugees (UNHCR) estimated that by the end of 2013 there were 51.2 million people ‘of concern’, which included 33.3 million internally displaced persons, 16.7 million refugees, and 1.2 million asylum seekers2. As reliable data on the spatial patterns and trends in internally displaced persons is extremely sparse, the focus of this chapter is on internal and international movements of legal migrants and refugees, although internal displacement in many conflict situations is far more common than migration captured by national statistics. Nevertheless, the analyses presented here highlight the refugee movements triggered by the numerous conflicts seen in Central and East Africa in the Republic of the Congo, Rwanda, Burundi, Uganda, South Sudan, and Sudan since 1990. In addition, the economic collapse in Zimbabwe caused substantial emigration to South Africa. Outside Africa, the violent conflicts in Iraq and Afghanistan are also noteworthy.

The ways in which environmental change shapes migration are complex and closely linked with socio-economic, cultural,, and political factors determining migration decisions. For example, drought-stricken populations may be constrained in their mobility due to the associated lack of capital (e.g., livestock, harvest), which is necessary to realize a move further afield. The combination of factors affecting migration makes it extremely difficult to identify the causal relationship between environmental change and human mobility. Nevertheless, a general pattern has emerged of short-distance migration in response to slow-onset environmental change being more common than longer distance movement triggered by sudden environmental disasters, such as tsunamis and hurricanes (Stojanov 2008).

The level and direction of migration is also shaped by demographic factors, most prominently the size of a population, its growth rate, and age structure (e.g., Preston et al. 1989). The combination of strong population growth and a young age structure releases an abundant labor supply. Regional and cross-national variation in labor supply and labor demand often act as drivers of both domestic and international labor migration. As current patterns of labor migration from South to West Asia demonstrate, movements tend to originate in countries experiencing strong population growth and target destinations with rising labor demand. Will future population growth in sub-Saharan Africa result in equally large movements towards the oil-rich Gulf countries and traditional destination countries in the developed world?

Predicting the likely future trajectory of migrationflows to, from, and within sub-Saharan Africa is difficult given the scarcity of data on migration and the dearth of research on the topic. It is unlikely that the trajectory of sub-Saharan Africa will closely follow that of many Asian countries, given the profound differences in socio-demographic characteristics between populations, most notably rates of literacy and educational attainment. Hence, it is unclear whether a growing young adult population that exerts pressure on domestic education systems and labor markets will trigger substantial migration flows from countries south of the Sahara to more developed, rapidly aging countries.

3 Migration and the Demographic Dividend

When considering the role of the demographic dividend in shaping migration trends, one may speculate that a growing labor force may be associated with higher volumes of movement within sub-Saharan Africa, rather than increased emigration to more developed countries. In this scenario, regions or countries that have more effective policies in place to ensure the adequate provision of services and incentives for economic growth are successful in attracting labor migrants from neighboring countries with less favorable conditions. A key question underlying this scenario that has not yet been adequately addressed in the literature is whether the trend of migration streams going up the income ladder, which is observed across the more developed world, also holds in sub-Saharan Africa. Provided that income differentials trigger migration, developing countries might be able to reap fiscal and economic benefits from their sizable young adult populations and perhaps even transition from a migrant sending to a receiving nation by placing emphasis on solid political institutions, expansion in education, and strong economic growth. This chapter aims to shed some light on the effects of cross-national variation of gross national income on migration trends in sub-Saharan Africa.

The demographic dividend not only shapes migration trends, but in turn it is also shaped by migration. Important in this context is the selectivity of migration by age, with young adults being the most mobile age group. The dividend begins with change in the population structure, which is commonly attributed to falling fertility. At the same time, the relative size of the working age population and the number of children per adult of working age can also be influenced by migration among younger adults. In the oil-rich Gulf countries, for example, immigration has led to an increase in the relative size of the working age population, whereas in Nepal the working age population has shrunk substantially due to emigration. At the sub-national level, similar effects are caused by migrationflows up the urban hierarchy. Around the globe, internal migration tends to result in a growing labor force in cities and a shrinking labor force in rural areas The movements of young adults, especially if they leave their children behind, can significantly alter the demographic prerequisites needed to capture a demographic dividend.

Besides the tendency to select younger adults, migration is also selective of more highly educated individuals. Rising education levels within a country’s population are commonly attributed to rising investments in children, as falling fertility lowers the number of children each couple has to support through education. But the second demographic dividend, which results in the higher economic productivity of a working age population, can also be shaped directly by high-skilled immigration. Highly-educated people tend to exhibit a greater propensity to move up the urban hierarchy towards metropolitan centers rich in job opportunities, and are more likely to move over long distances than their less educated peers. Therefore, highly-skilled migration has the potential to affect not only the first demographic dividend through alterations in national and regional population age structures, but also the second demographic dividend through shifts in the education level of populations.

Migration makes it much more difficult to establish how accelerated growth in a country’s economy can be achieved. Besides strategic investments in health, education, and good governance, managing migration effectively through adequate policy development will be crucial for countries in sub-Saharan Africa. Such policies should facilitate both the flow of unskilled labor between neighboring countries, and circular migration of skilled labor between origin countries and destinations in North America, Europe, and Australia. International circular migration programs can be an effective means for reducing a labor surplus while at the same time reducing the risk of losing human capital to brain drain (Hugo 2013). However, the science-based development of circular migration policies has long been hindered by a lack of comparable data on migrationflows and migrant characteristics at regional and global scales, a topic to which this chapter now turns.

4 Data on Migration in Sub-Saharan Africa

In contrast to other components of demographic change, comparative statistics on migration have long been absent from national and international statistical collections (Bell et al. 2014). This is rapidly changing, with the emergence of new estimates of international migrationstocks (UNPD2013) and more recently, estimates of international migrationflows between 196 countries (Abel and Sander 2014). The IMAGE project (Comparing Internal Migration Around the Globe) has sought to advance comparative statistics on internal migration by conducting an inventory of data collection practices and developing a suite of methods and metrics for the purpose of cross-national comparison (see e.g., Bell et al. 2014, 2015). Notwithstanding, there remain severe impediments to cross-country comparisons due to differences in data collection instruments, the types of migration data collected, and the spatial and temporal framework employed. This is more marked for the analysis of internal migration than international moves, which have benefitted from significant recent advances in data collection and estimation procedures (see for example Abel and Sander 2014).

Globally, three main instruments are conventionally used to collect migration data: population and housing censuses; population registers and administrative data sets; and surveys. Population censuses are the most common source of data, with 142 of 193 UN member states collecting some form of internal migration data in the 2000 Census Round (Bell et al. 2014). The number of countries collecting data on the size of their immigrant population is broadly similar. Data from population registers and administrative sources is used in at least 50 countries around the globe, however, these collections are largely limited to Europe and Asia. Surveys are much more common, but vary widely with respect to sample size and coverage, severely limiting their utility for migration analysis. Compared with other parts of the world, data on migration in sub-Saharan Africa is relatively scant. Of the 48 UN member states, 28 collected internal migration data via a census in the 2000 Census Round, 36 collected internal migration data via a survey, while no countries employed a population register or administrative data set (Bell et al. 2015).

The questions and criteria used to capture migration within censuses, registers, and surveys vary widely around the globe, further complicating regional or global comparisons. The most common form of migration data collected by population censuses is place of birth, with 26 African countries collecting these data in the 2000 Census Round. This question provides information on the number (or stock) of internal migrants currently living outside their region of birth, as well as the size of a country’s immigrant population. Lifetime data is usually collected on a relatively coarse spatial scale, limiting its utility for the analysis of spatial patterns. A more serious limitation of this data is the lack of information regarding the timing of moves, making it difficult to identify changes in migrationintensity and patterns over time. Census questions on recent migration do allow temporal shifts in the intensity and pattern of migration to be more readily explored. These questions take a number of forms. Most common in sub-Saharan Africa are questions asking respondents about their place of previous residence at some time in the past, commonly one or 5 years ago (16 countries in SSA). Data on the duration of current residence is also frequently collected (15 countries) and, when coupled with information on place of previous residence (11 countries), can be used to explore internal migration patterns and estimate recent immigrant stock. Despite the growing availability of census data, differences in the spatial and temporal frames used to collect migration data severely constrain cross-national comparisons and the quantification of international movements around the globe. This is further impacted by a lack of data availability, with collection not always guaranteeing the dissemination of migration data. For this study, census data is used to explore the spatial patterns of internal migration for a small sample of countries.

Surveys present an alternative to census data for countries in sub-Saharan Africa. The Demographic and Health Survey, conducted by USAID, has collected data on duration of current residence across a number of survey waves. While this data provides next to no information on the spatial pattern of moves and is limited to women aged 15–49, its strength lies in the standard approach to collecting data on internal migration, capturing a broadly comparable measure of internal migrationintensity to be calculated with a sample of 35 countries. Together, this data provides some limited insight into the intensity of internal migration across the region. To explore the intensity and pattern of international migration in the region, we draw on bilateral flow estimates developed by Abel and Sander (2014).

5 Spatial Patterns of International Migration

This section draws on new estimates of bilateral migrationflows covering the period 1990–2010 (Abel and Sander 2014). To quantify international migration flows, an indirect estimation methodology was developed to determine the number of movements required to meet changes over time observed in migrant stock data published by the United Nations. The estimates capture the number of migrants who changed their country of residence over 5-year periods, thereby omitting most seasonal and circular types of movements. The estimates include refugee movements that were registered by the UNHCR but fail to take into account undocumented migration, nor do they cover recent migrant streams triggered by the violent conflicts in Syria, Libya, and Yemen.

The data enables us to provide a much more comprehensive overview of the geography of migration and the position of sub-Saharan Africa within the global system of flows than has been possible to date. Figure 1 shows the relative size and direction of migration streams between 15 world regions over the 5-year period 2005–2010. By focusing on flows in excess of 140,000 people, we can highlight the global flow of people between world regions, which are represented by the segments of the circle, in just one visualization. Neighboring world regions are arranged close to one another around the circle and the size of each migration flow flow is represented by the width of the links between the regions. The color of each flow is identical to the color of the origin region, following the idea that migrants take their characteristics with them when moving to another country. The direction of the flow is shown also by a gap between the flow and the circle segment at the destination. For example, one of the largest migration flows around the globe was the orange flow from Central America (orange, located at about 11 o’clock in Fig. 1) to North America (red, located at about 12 o’clock). The numbers on the outside of the segment for North America indicate that the volume of the flow was about 3 million people.
Fig. 1

International migrationflows between 15 world regions in 2005–2010. Note: How to read the graphic: world regions are arranged in a circular layout, with each world region assigned a distinctive color. The band width denotes the size of the migration flow and assumes the color of the origin region. The direction of the flow is also indicated by a greater separation of the band from the outer circle at the destination region. The numbers outside the circle indicate the total migration in and out of a region in millions

(Source: Abel and Sander 2014. Quantifying Global International Migration Flows. Science, 343 (6178): 1520–22)

The visualization shows that most migrants move over short distances within the same region or between neighboring regions, and relatively few move between continents. North America, Europe, and the oil-rich Gulf countries in Western Asia are the destinations of flows that come from furthest afield (most of which go through the centre of the circular graphic). Sub-Saharan Africa recorded movements of about 10 million migrants. The largest flow (3.7 million) was within the region, whereas 2.2 million people moved to Europe and North America. The flow within sub-Saharan Africa was therefore larger in volume than the stream from Central to North America (3.2 million), but smaller than the flow from South to Western Asia (4.9 million).

At the global scale, the intensity of international migration was estimated to be stable at about 0.6% of world population moving over 5-year periods since 1995. In 1990–1995, the violent conflicts in Eastern Africa and Afghanistan, as well as the fall of the Iron Curtain, triggered stronger movements (0.7%). The system-wide intensity of international migration within sub-Saharan Africa was above the global average in 1990–1995 (7.7 million moves, or 1.5% of the population) but declined to 3.7 million (or 0.5% of the population) in 2005–2010. The total net loss of population through migration to countries outside the region was 1.8 million (or 0.24% of population) in 2005–2010.

A closer look at the patterns of international migration within sub-Saharan Africa reveals three separate systems of flows in Western, Eastern, and Southern Africa with very little movement between these systems (see Fig. 2). In contrast to the global pattern of movement with many longer-distance flows between continents that go through the center of the circle in Fig. 1, migration in sub-Saharan Africa occurs almost exclusively between neighboring countries. The largest flows in the region from Zimbabwe to South Africa, from Tanzania to Burundi and from Uganda to South Sudan were triggered by political instability and violence rather than purely economic considerations, highlighting the region’s vulnerability to shocks that fundamentally alter the migration system. Although few people move directly from the poorest to the richest countries, the global pattern of migration flows flows is characterized by movements from lower to higher income countries. This pattern of flows up the income ladder is much less clear in sub-Saharan Africa. Movements occur from lower to higher income countries, such as from Mozambique and Malawi to South Africa, but also in the reverse direction, such as from Côte d’Ivoire and Guinea to Liberia and from Sudan to Chad. It appears that economic factors (such as income levels and unemployment rates) play a less important role in the migration decision-making compared to other world regions, and that geographic proximity, violent conflict, and political instability play a major role in shaping migration patterns. Thus far, we have found surprisingly little evidence for the trend of migration streams going up the income ladder to hold in sub-Saharan Africa.
Fig. 2

Net migrationflows between countries in sub-Saharan Africa in 2005–2010. Note: Countries with very small volumes of movement were omitted. Similar to Fig. 1, countries are arranged in a circular layout, with each country assigned a distinctive color. The band width denotes the size of the migration flow and assumes the color of the origin region. The numbers outside the circle indicate the total migration in and out of a region in 10,000 people

International migration has become an increasingly important component of national population growth, especially in low-fertility countries across North America, Asia, and Europe. Figure 3 suggests that for most countries in sub-Saharan Africa, the impact of migration on population size is much more modest. The majority of countries that recorded net migration gains or losses in excess of 5% sent or received people from other countries within the region. Senegal, Somalia, and Malawi are the only countries that experienced a noticeable net loss of migrants to countries outside of sub-Saharan Africa, providing little support for the notion of mass skilled emigration causing a ‘brain drain’. Triggered by the violent conflicts in Eastern Africa, the intensity of movements was substantially higher in the period 1990–1995 than in 2005–2010, in which only Somalia, South Sudan and Lesotho recorded noticeable net migration gains from within the region.
Fig. 3

Net migration rates rates for countries in sub-Saharan Africa in 1990–2010 and 2005–2010. Note: A distinction is made between net migration gains/losses with other countries in SSA, and gains/losses with countries outside SSA

In summary, the spatial patterns of international migration in sub-Saharan Africa are different from those observed in other world regions. Migration occurs over relatively short distances, chiefly between neighboring countries, and appears to be triggered largely by non-economic factors that, in the case of violent conflict and political instability, are very difficult to predict. Although migration does not resemble the patterns observed elsewhere, its impact on national population size and age structure has been more subtle than in many developed countries, with the exception of refugee movements in Eastern Africa. The findings suggest that international migration may only play a minor role in alleviating or intensifying labor market imbalances created by a large cohort of young adults.

6 Internal Migration in Sub-Saharan Africa

The existing literature on the demographic dividend has paid little attention to within-country variations, although it is well established that cities tend to lead the demographic transition compared to poorer rural areas (Williamson 2013). This neglect is somewhat surprising, given the key role that internal migration plays in shaping the distribution of population within countries. Evidence suggests that there is significant heterogeneity in the intensity, spatial pattern, and impact of internal migration around the globe. Results from the IMAGE project which draw on census data indicate significant regional variability in internal migration intensities across Africa, with pockets of both high and low mobility (Bell et al. 2015). The geographic coverage of this analysis is relatively limited, due to a lack of detailed census data.

The Demographic and Health Survey provides an alternative source of internal migration data. It benefits from a much wider geographic coverage compared with census data, as well as consistent migration questions across countries, but is limited to women aged 15–49. Figure 4 shows estimates of migration intensities over a 5 year interval for 34 countries across sub-Saharan Africa3. Estimates range from a low 6.6% in the island state of Comoros, i.e., 6.6% of women aged 15–49 changed their place of residence in the 5 years prior to the survey, to a high of 39.8% in Zambia. Three broad clusters of countries with high migration intensities can be identified: a West African group centred on Côte d’Ivoire, Gabon, and Liberia; an East African group, with high intensities in Kenya and Uganda; and a Southern African group, echoing the regional groupings in international migration described earlier. Lower internal migration intensities are observed throughout Central Africa and parts of the Sahel – the latter may reflect high levels of temporary mobility. There is likely a gender dimension to these patterns, with the mobility of women not necessarily representative of the mobility in the population as a whole. Differences are likely to be greatest in countries with the lowest levels of gender equality.
Fig. 4

Intensities of internal migration over a 5 year interval for 34 countries across sub-Saharan Africa

(Source: DHS data)

In the developing world, rural to urban migration is often viewed as the primary form of internal migration. In point of fact, migrationflows are rarely unidirectional, with counter-flows from urban to rural regions, flows between urban centers, and between rural localities all typically a part of wider migrationsystems. An understanding of migration across different levels of the settlement hierarchy is useful for a number of reasons. It provides an insight into the pace and drivers of urbanization. It can indicate the degree of inequality within national space economies, and it provides insights into the spatial patterns of development. Cross-national comparison of migration patterns across the settlement hierarchy is impeded by both the lack of spatially referenced migration data, and a lack of standard definitions for urban and rural areas which vary widely between countries. Following Rees and Kupiszewski (1999) and Rees et al. (2015), we adopt population density as a proxy for the degree of urbanization of regions within countries. For each country, regions are grouped into four density quartiles, with the top quartile the most densely populated (i.e., most urban) and the bottom quartile the least (i.e., most rural). Flows between region types can be examined to see whether the largest flows are from low density to high density regions (i.e. rural-urban migration), between regions in the same density band (i.e., inter-urban or inter-rural flows) or from high density to lower density regions (i.e., counter urbanization). Figure 5 shows inter-regional migrationflows classified by density band for five countries: Burkina Faso, Kenya, Senegal, Sudan (includes both Sudan and South Sudan), and Tanzania. In Burkina Faso, Kenya, Senegal, and Sudan the largest single flow is between regions in the top density bands, suggesting significant inter- and intra-city exchange. There is also evidence of significant rural to urban flows in each of these four countries, but these are partly offset by counter-streams from high to low density regions. The migration system of Tanzania stands apart from other countries, in that it is dominated by flows down the urban hierarchy, particularly from regions belonging to the third quartile to regions in the second quartile. Flows into the highest density regions are also offset to a large degree by flows back down the settlement hierarchy.
Fig. 5

Internal migrationflows between quartiles of regions’ population density for five selected countries. Note the scale: Burkina Faso in 10,000s; Kenya, Senegal, Sudan and Tanzania in 100,000s

In summary, there is significant cross-national variation in the intensity of internal migration across sub-Saharan Africa, with pockets of high internal migration echoing clusters of countries with similar patterns of international migration, suggesting an association between these types of mobility. The limited evidence presented on the spatial distribution of migrationflows across the urban hierarchy, confirms the importance of rural-to-urban flows in many sub-Saharan African countries. These are accompanied by strong inter-urban and urban-rural exchanges, suggesting a diverse range of spatial strategies and individual motives for migration that seem to go well beyond economic factors.

7 Linking Internal and International Migration

International and internal migration are typically viewed as two separate demographic components, although they are clearly intertwined at the individual level, because migrant trajectories often involve a sequence of internal and international moves. Conventional wisdom suggests that internal migration from rural to urban areas acts as a stepping stone for international migration; and that large cities serve as gateways for international immigrants, causing the displacement and replacement of the host population. Neither of these important links has been rigorously studied (King and Skeldon 2010), largely because of the dearth of longitudinal migration data that allows migrants to be traced across national borders. Hence, existing evidence on the relationship between internal and international migration is mostly based on a small number of national surveys.

As a first step towards the development of a better understanding of the links between internal and international migration, we compare the intensities of the two types of movement for 30 countries in sub-Saharan Africa that DHS data was available for, and that had a population above 1.5 million people in 2010. The intensities in per cent of the population are paired and depicted in a scatterplot in Fig. 6 along with an indication of the gross national income (GNI) (GNI) of each country. Green shading indicates above-median intensities of internal migration and net gains through international migration, whereas grey shading indicates below-median intensities of internal migration and net international losses. Darker shading corresponds to above-median GNI levels, whereas lighter shading suggests below-median income levels. Focusing first on the scatterplot in Fig. 6, the overall picture is one of little or no systematic relationship between internal and international migration. High levels of internal migration (predominantly from rural to urban areas) do not coincide with high levels of international migration, with the exception of Liberia. There does not appear to be a clear relationship between income levels and intensities of migration. Some countries with lower income levels experience high internal migration intensities coupled with negligible intensities of international migration (e.g., Zambia), while some countries with higher income levels have low internal and higher international migration intensities (e.g., South Africa).
Fig. 6

Linking internal migration, international migration, and gross national income (GNI): A simple typology of countries in sub-Saharan Africa. Note: Internal migration intensities calculated using DHS data; international migration intensities calculated using estimates by Abel and Sander (2014) and UN WPP 2014 population data. Data on GNI for the period 2005–2010 sourced from the World Bank

The spatial representation of the typology of countries shown in the map in Fig. 6, however, echoes the three clusters of countries described earlier and underlines the importance of the regionalization of migration within sub-Saharan Africa. The West African group includes a diverse set of countries with regards to their pairings of migration intensities and income levels. The East African group is dominated by countries with negative international net migration and high intensities of internal migration, whereas the Southern African group includes the only country with high international migration gains, high internal migration intensities, and higher income levels (i.e. South Africa). These findings, however, should be interpreted with caution, given the limited data quality discussed earlier.

8 Conclusions

This chapter has provided a summary of the existing evidence on patterns and trends in internal and international migration in sub-Saharan Africa. Our aim has been to fill the gap in the literature created by the absence of adequate studies which examine the relationship between migration and countries’ ability to reap the benefits of the demographic dividend. A key obstacle to a better understanding of this relationship is the limited availability of reliable migration data. While the United Nations has made some progress in promoting a unified standard for collecting statistics on migration, national legal frameworks and the divergent interests of nation states limit the degree of alterations which national statistical institutes are willing to implement so as to improve cross-national consistency. In response to the limitations of secondary data sources, the scientific community has focused on the development of harmonization and estimation methodologies as well as the exploitation of new alternative data sources, such as mobile phone data (Abel and Sander 2014; Raymer et al. 2013; Wesolowski et al. 2013; Bell et al. 2015). The collection of adequate data and the promotion of open access to census and register data should be a top priority in sub-Saharan Africa and beyond.

Projecting the likely future trajectory of migration in sub-Saharan Africa and its impact on population size and age structure is inherently difficult, especially in the context of African migration being largely triggered by shocks to the system, such as violent conflict and political regime changes. These difficulties are reflected in the United Nations opting for the simple but unrealistic assumption of net-international migration rates converging to zero by the year 2050. Even fewer studies have been devoted towards projecting sub-national populations within countries south of the Sahara, owing partly to the lack of adequate data. Another source of uncertainty in population projections for sub-Saharan Africa is the speed of expansion of education. A commensurate expansion in education and the growth of a more skilled workforce could lead to higher levels of internal migration as individuals seek to maximize their economic potential, but, unless domestic job markets are sufficiently attractive, it could also result in an increase in emigration from Africa to the more developed world.

Footnotes

  1. 1.

    See the Genographic Project available at: https://genographic.nationalgeographic.com (accessed 25 June 2016).

  2. 2.

    UNHCR Mid-Year Trends, 2014.

  3. 3.

    Estimates are derived from the question on duration of residence. Data is drawn from the most recently available DHS data.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Population Research CentreUniversity of GroningenGroningenThe Netherlands
  2. 2.School of Earth and Environmental SciencesThe University of QueenslandBrisbaneAustralia

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