Population and migration

Global population distribution and population density

Distribution is where people are; density is how tightly packed they are, measured as people per square kilometre. The world's population has passed 8 billion and is spread very unevenly. More than half of all people live in Asia, and the great clusters are East Asia (eastern China, Japan, South Korea), South Asia (India, Pakistan, Bangladesh), South-East Asia (Java, the Philippines, Vietnam), Europe, and the eastern United States, with a further fast-growing cluster in West Africa around Nigeria. Between those clusters lie enormous areas that are almost empty: the polar regions, the Sahara and the Arabian deserts, the high plateaus of Tibet and the Andes, and the equatorial rainforests of the Amazon and the Congo basin.

Physical factors explain much of that pattern. People concentrate on low land, on coasts and river floodplains where there is fresh water and fertile alluvial soil, in temperate climates without extremes of heat, cold or aridity, and where there are resources to work - coal, oil, minerals, fish. They avoid steep, high, cold or dry land where farming is difficult, and places where disease or hazards make settlement dangerous.

Human factors explain the rest, and in the modern world they usually outweigh the physical ones. Economic pull towards jobs in industry and services has built the great urban clusters; social factors such as schools, hospitals and family ties hold people where services are good; political decisions move people, close borders or open new land for settlement; and historical events - the slave trade, colonial trade routes, the industrial revolution - explain why some ports and coasts are still crowded long after the industry that built them has gone.

Density is calculated by dividing the total population by the area in square kilometres, and a national average can be badly misleading. Egypt's average is around 100 people per square kilometre, yet almost the whole population lives on the irrigated strip along the Nile and in its delta, while most of the country is empty desert. A good answer always says where the people are as well as how many there are.

• Physical factors: relief, climate, soils, water supply, natural resources, disease and hazard risk.
• Economic factors: employment, industry, trade, transport, the cost of living.
• Social factors: services, education, healthcare, family and community ties.
• Political factors: government policy, resettlement schemes, borders, conflict and security.
• Historical factors: colonial routes, the slave trade, earlier industrial growth, land ownership.
• Density = total population / area in square kilometres; the figure says nothing about where inside the country the people actually live.

Trends in global population growth and regional variation

Population change in a country equals natural increase (births minus deaths) plus net migration (immigration minus emigration). Global growth is driven almost entirely by natural increase. The growth rate peaked at just over 2 per cent a year in the late 1960s and has roughly halved since, but the annual addition is still very large, because each percentage point now applies to a far bigger total. This is population momentum: even if every family had only two children tomorrow, the world's population would keep rising for decades because there are so many young people already of childbearing age.

The pattern is now sharply uneven. Sub-Saharan Africa is growing fastest, led by countries such as Niger, the Democratic Republic of the Congo and Nigeria, where fertility remains high and death rates have fallen. South Asia is still growing but more slowly. Europe, Japan, South Korea and China have fertility below the replacement level, and several of them are now recording natural decrease: China's population has begun to fall, Japan's has been falling for more than a decade, and South Korea has one of the lowest fertility rates ever recorded. India overtook China as the most populous country in 2023.

The factors behind these differences are the same categories you use everywhere in this topic. Environmental factors such as drought, flooding and disease affect both mortality and the decision to have children. Social factors - the education of girls, the age of marriage, the availability of contraception, religious teaching, the status of women - are the strongest single influence on fertility. Economic factors decide whether children are an asset (extra hands on a family farm, support in old age where there is no pension) or a cost (schooling, housing, childcare in a city). Political factors include family planning programmes, healthcare spending, and conflict, which kills and displaces people. Historical factors matter because the age structure a country has today was built by its fertility thirty years ago.

Components of population change: the measures and the factors behind them

The birth rate is the number of live births per 1 000 people per year; the death rate is the number of deaths per 1 000 people per year. Subtract one from the other and you have the rate of natural increase per 1 000. To express it as a percentage, divide by 10: a birth rate of 38 and a death rate of 12 gives a natural increase of 26 per 1 000, which is 2.6 per cent a year. That is a very fast rate - at 2.6 per cent a population doubles in about 27 years.

The total fertility rate (TFR) is the average number of children a woman would have over her lifetime at current age-specific rates. It is not the same as the birth rate: a country can have a high birth rate because it has a huge number of young women, while each individual woman has only two children. Replacement level is about 2.1 children per woman; below that, and without immigration, a population eventually falls. The infant mortality rate (IMR) is the number of deaths of children under one year old per 1 000 live births, and life expectancy is the average number of years a baby born now could expect to live.

These measures vary enormously in space. TFR is highest in sub-Saharan Africa, where several countries record around five or six children per woman, and lowest in East Asia and southern and eastern Europe, where it has fallen below 1.5. IMR is highest in low-income countries and in conflict zones, where it can exceed 50 per 1 000, and lowest in high-income countries, where it is often below 5. Life expectancy at birth reaches the mid-80s in Japan, Switzerland and Singapore and remains below 65 in several countries of sub-Saharan Africa. The IMR is the most sensitive of all these measures, because it responds immediately to clean water, vaccination, nutrition and maternal healthcare.

Fertility is affected by social factors first: the education of girls is the strongest single predictor, because educated women marry later, earn their own income and use contraception; religion and cultural expectations set the acceptable family size; and the status of women decides whether they can act on their own preferences. Economic factors decide the cost of a child and whether children earn; environmental factors such as food insecurity and land shortage push families either towards larger households or away from them; and political factors include the availability and legality of contraception, family planning programmes and pronatalist incentives.

Mortality is affected by income and nutrition, by water supply and sanitation, by the quality and reach of healthcare, by disease environment (malaria, tuberculosis, HIV), by conflict and hazards, and by lifestyle in richer countries. It is also affected by the age structure itself: a country with a large elderly population will have a high crude death rate even with excellent healthcare, which is one reason the crude death rate is a poor guide on its own.

Population structure, dependency and age/sex diagrams

Population structure is the composition of a population by age and gender, together with the dependency that composition creates. It is drawn as an age/sex structure diagram (a population pyramid): five-year age cohorts on the vertical axis, males on the left and females on the right, and either percentages of the total or absolute numbers along the horizontal axis. Always check the axis before you read the shape, because a pyramid drawn in percentages looks very different from the same population drawn in millions.

Dependency is the share of the population outside the economically active ages, conventionally the under-15s and the over-65s, supported by the 15-64 age group. The dependency ratio expresses this as the number of dependants per 100 people of working age: (population aged 0-14 + population aged 65+) divided by population aged 15-64, multiplied by 100. A ratio of 90 means there are 90 dependants for every 100 potential workers, which is a heavy burden; a ratio of 45 means the reverse. The ratio is a crude measure, because not everyone aged 15-64 works and some older people do, but it is the standard way to compare countries.

Reading the shape is a skill in itself. A broad base tapering sharply means high fertility and high mortality at each age: a youthful population. A narrow base with a wide top means low fertility and long life: an ageing population. Bulges record a baby boom or a wave of immigration, and they move up the pyramid as that cohort ages. Notches record a sudden loss of a cohort - war, famine, epidemic, or a change in policy such as a sharp fall in births. Asymmetry between the sexes usually means migration (young men leaving or arriving for work), war (young men killed), or the fact that women live longer than men in old age.

The structure of a country is produced by two things and only two: its history of natural increase and its history of net migration. High fertility twenty years ago gives a bulge of young adults today; sustained in-migration of young male workers can give a country a pyramid that looks nothing like its own birth and death rates would suggest, as in the Gulf states, where the majority of residents in some countries are foreign-born.

• Youthful structure: broad base, steep sides, narrow top; high birth rate and high child mortality; typical of Niger, Somalia, the Democratic Republic of the Congo.
• Ageing structure: narrow base, bulging middle, wide top; low fertility and long life expectancy; typical of Japan, Italy, Germany.
• Bulge: a cohort born in a baby boom, or a wave of young immigrants, tracked upwards over time.
• Notch: a missing cohort - war, famine, epidemic, or a policy that cut births sharply.
• Dependency ratio = (0-14 + 65 and over) / 15-64 x 100.
• Migration distortion: heavy in-migration of young workers, often male, can reshape a pyramid completely - the Gulf states are the clearest case.

The demographic transition model: purpose, stages and critical evaluation

The demographic transition model (DTM) describes how birth rates and death rates change as a country develops, and what that does to its total population. It was built from the experience of western Europe, where death rates fell first as agriculture, medicine, water supply and sanitation improved, and birth rates followed later as families adjusted to lower child mortality and to urban, industrial life. The gap between the two rates is natural increase, which is why population grows fastest in the middle of the transition, not at the start.

Its purpose is descriptive and comparative: it summarises a sequence that many countries have followed, it explains why populations grow fastest when death rates have fallen but birth rates have not, and it allows you to place countries at different points and predict the pressures they will face - schools now, jobs in fifteen years, pensions in forty. That predictive use is why governments and aid agencies still use it.

Its limitations are what the evaluation question is really about. It is Eurocentric: it was derived from a transition driven by industrialisation and is applied to countries whose fertility fell for different reasons - family planning programmes, female education, or, in China, direct policy. It assumes all countries pass through the same stages in the same order, which some have not: fertility has fallen in poor countries such as Bangladesh and Sri Lanka without the economic development the model implies. It allows no place for migration, although migration is the main driver of population change in many countries today, including the Gulf states and much of Europe. Stage 5 was added later and was not part of the original model. It does not handle reversals: conflict and the HIV/AIDS epidemic raised death rates and disrupted the sequence in parts of southern Africa. It works with national averages and hides enormous internal differences between regions of the same country. And it describes the past rather than predicts the future, so a country placed in stage 2 is not thereby fated to move to stage 3.

A judgement worth writing: the DTM is a useful descriptive summary and a rough comparative tool, especially for the broad contrast between a youthful, fast-growing population and an ageing, stable one, but it is a poor predictive model and it must be used with named countries and with migration in mind.

Youthful and ageing population structures: impacts

A youthful population has a high proportion of children and young adults, produced by high fertility that has only recently begun to fall. Its first impact is dependency: a large share of the population is too young to work, so a smaller workforce must fund schools, clinics and childcare. Socially, the pressure falls on schools, housing and health services, and on the labour market, which must create jobs for a wave of young people every year; where it cannot, youth unemployment and emigration follow. Economically, the country spends heavily on services that produce no immediate output and saves less, but if the fertility fall continues the same cohort becomes a demographic dividend - a large, productive workforce supporting relatively few dependants, which is the window that East Asia used to grow rapidly. Environmentally, a growing population puts pressure on land, water and forests, and young households starting out increase demand for housing and energy. Politically, governments face constant pressure to expand services, and a large unemployed youth cohort can be a source of instability and protest.

An ageing population has a growing share of people over 65, produced by sustained low fertility combined with rising life expectancy. The dependency problem is reversed in direction but not in severity: fewer workers support more retired people, and the ratio worsens each year. Economically, pension systems and health and social care absorb a rising share of public spending, the labour force shrinks, and growth slows unless productivity rises or workers are brought in; the tax base narrows exactly as costs rise. Socially, care falls on families, often on middle-aged women, and there may be too few places in care homes and too few carers; loneliness and the needs of the very old become public issues. Environmentally, the effects are mixed: fewer births and smaller households reduce some pressures, while heating, healthcare and pharmaceutical waste rise, and sparsely populated rural areas lose services. Politically, governments raise retirement ages, reform pensions, subsidise childcare and consider immigration policy - all of which are unpopular, which is why ageing is as much a political problem as an economic one.

The two structures are not opposites to be memorised but two ends of a continuous range, and most countries are somewhere in between with sharp internal differences. A country can have a youthful national structure and an ageing city, or the reverse.

Government attempts to manage natural increase

Governments try to manage natural increase when its consequences outrun their capacity to cope. Fast growth means more children needing schools, more families needing housing and water, more job-seekers each year, and more pressure on land and forests; it can also threaten food supply and political stability. Governments in the opposite position intervene for the opposite reason: where fertility has fallen well below replacement, a shrinking workforce and rising pension costs become the problem, and policy turns pronatalist.

Antinatalist policy: China. From 1979 China restricted most urban couples to one child, using a mixture of incentives (priority in housing, healthcare and schooling for families with one child), penalties (fines, loss of promotion, loss of benefits), propaganda, and later marriage. Rural families were often allowed a second child if the first was a girl, and ethnic minority groups were largely exempt. Fertility fell from around six children per woman in the late 1960s to below replacement by the 1990s, and the policy was relaxed to two children in 2016 and three in 2021. It is a genuine success in its own terms - growth slowed and hundreds of millions of births were avoided - but the costs are now the story: a rapidly ageing population with too few workers, a distorted sex ratio from a preference for sons, and a generation of only children each supporting two parents and four grandparents.

Pronatalist policy: Singapore. Singapore reversed direction. Its Stop at Two campaign in the 1970s was designed to slow growth; by the 1980s fertility had fallen so far that the government launched Have Three or More (if you can afford it) in 1987, backed by baby bonuses, subsidised childcare, priority in public housing allocation, paid parental leave and tax relief. Fertility nevertheless stayed among the lowest in the world, which shows the limits of policy that pulls against the cost of living, later marriage and changed expectations. Japan, South Korea and much of Europe run similar pronatalist packages with similar modest results.

Which is more successful? China's policy achieved its stated aim more completely than almost any other population policy in history, which is why it is the standard example - but success has to be judged against the aim and against the unintended consequences, and few governments would now choose that instrument. The general lesson is that governments can influence fertility when they control incentives, information and coercion, and that fertility is very hard to raise once it has fallen, because the decision to have children is shaped by housing costs, careers and expectations that no bonus can quickly change.

Migration: types, causes and constraints

Migration is the movement of people from one place to another to live, and international migration crosses a national border. It is classified in three ways that overlap. By motive, it is voluntary when the migrant chooses to move - economic migration for work or pay, or social migration for family reunification, marriage, education or retirement - and non-voluntary (forced) when the migrant has no real choice. By duration, it is temporary (seasonal work, a fixed contract, a posting, study) or permanent (settlement, family reunification). By direction and legality, it includes regular and irregular flows, and people who are trafficked.

The forced category has precise meanings that examiners expect. A refugee is a person who has crossed an international border and cannot return because of a well-founded fear of persecution on grounds of race, religion, nationality, political opinion or membership of a particular social group, as defined in the 1951 Refugee Convention; the United Nations High Commissioner for Refugees (UNHCR) has the mandate to protect them. An asylum seeker is someone who has crossed a border and applied for protection as a refugee, but whose claim has not yet been decided. Both differ from an internally displaced person, who has been forced out of their home but has not crossed a border. Turkey hosts one of the largest refugee populations in the world, most of them Syrians who fled the civil war that began in 2011; Colombia hosts large numbers of Venezuelans; and the war in Ukraine produced one of the fastest forced movements of people in Europe since the Second World War.

Causes are usually sorted into push and pull factors, each of which can be environmental, economic, cultural, demographic or political. Environmental pushes include drought, flooding, sea-level rise and land degradation; economic pushes include unemployment, low wages and land shortage, while the economic pull is higher wages and labour demand. Cultural factors include religious or ethnic persecution and the pull of a community already established abroad. Demographic factors matter because migration is concentrated among young adults: a country with a large youth cohort and few jobs generates migration, and an ageing country generates demand for care workers. Political pushes include war, persecution and instability; political pulls include safety, citizenship and rights, while policy at both ends - visas, quotas, border control - can push as well as pull.

Constraints are the obstacles that stop a push and a pull from producing a move, and they are the part students forget. Physical constraints include distance, oceans, deserts and mountains. Environmental constraints include the cost and danger of the journey and the hazards along the route. Social constraints include family ties, language, religion and the fear of discrimination. Economic constraints are the largest: the cost of transport, visa fees, recruitment fees and the debt taken on to pay them. Political constraints include visa requirements, quotas, closed borders, employer-tied visas such as the kafala system in parts of the Gulf, detention and deportation. A migration stream exists only where the pull is strong enough to overcome these obstacles, which is why a wage gap between two countries can persist for decades without producing much movement.

Impacts of migration: source areas, destinations, migrants and the detailed example

Impacts are always asked in three directions, and each has environmental, social, economic, political and demographic dimensions. On the source area, the gain is remittances - money sent home, which raises household incomes, pays for housing, school fees and healthcare, and enters the national economy as foreign exchange. Migration also relieves unemployment and land pressure, and returning migrants bring skills, savings and ideas. The loss is brain drain: the nurses, doctors, teachers and engineers a poor country has paid to train leave for better pay, and the workers left behind are disproportionately young, which accelerates ageing in the source area. Families are separated, children are raised by relatives, and the economy becomes dependent on money earned abroad rather than on production at home.

On the destination, migrants fill labour shortages in care, health, construction, agriculture, hospitality and technology, pay taxes, and often accept work that local workers will not do at the going wage, which keeps costs down. Against that, rapid arrival can put pressure on housing, school places and health services, hold down wages at the bottom of the labour market, and create social tension where integration is poor. Migrants can also be exploited - tied to one employer, paid below the minimum, housed in poor conditions - which is a cost to them and a regulatory problem for the state.

For the migrants themselves, the gain is usually a much higher income, better schooling for their children, and safety. The costs are separation from family, dangerous or degrading work, discrimination, loss of legal status if a visa lapses, and deskilling, where a qualified teacher or engineer works as a cleaner because their qualification is not recognised.

How large the impact is depends on four sets of factors. The source area's population structure (a very young population can spare migrants; an ageing one cannot), its income classification (a poor country feels the loss of a doctor far more than a rich one), and the level of education and skill of its population decide how much is lost. The migrant's own age, ability to finance travel and skill level decide whether they succeed and whether they stay. The flow itself matters - its volume and its type (temporary labour migration has different effects from permanent family settlement or a refugee influx). And the destination's population structure, income level and skill profile decide whether migrants fill a gap or compete for scarce jobs.