This dataset offers a detailed view of population figures and net migration trends for 186 countries over 63 years, from 1960 to 2023. Sourced from the World Bank API, it combines reliable data with global coverage to support diverse research needs.

Key features:

Population Data: Annual population statistics for each country. Net Migration Data: Yearly net migration figures, reflecting population movements. This dataset is perfect for exploring global demographic shifts, analyzing migration patterns, and their correlations with economic, social, and political factors. Suitable for tasks like time series analysis, visualization, and predictive modeling.

Column Description:

• Country: The name of the country or region.
• Year: The year of the data point (1960–2023).
• Population: The exact total population of the country for the given year.
• Population (in millions): The population value in millions, with the decimal part ignored.
• Net Migration: The net migration for the country in the given year, indicating the number of people moving into or out of the country.

Overview: This dataset provides population and migration data for five key South Asian countries: Pakistan, India, Bangladesh, Afghanistan, and Sri Lanka, spanning the years 1960 to 2023. The data, sourced from the World Bank API, sheds light on population growth trends and net migration patterns across these nations, offering rich insights into the region's demographic changes over 63 years.

Key Features: - Total Population: Yearly population data for five countries. - Net Migration: The net effect of immigration and emigration for each year. - Time Span: Covers data from 1960 to 2023. - Source: Extracted from the official World Bank API, ensuring credibility and accuracy.

Use Cases: - Explore regional migration trends and their impact on demographics. - Analyze population growth in South Asia. - Compare migration and population patterns among Pakistan, India, Bangladesh, Afghanistan, and Sri Lanka. - Develop predictive models for demographic and migration forecasts.

About the Data: The dataset is publicly available under the World Bank Open Data License. It can be used freely for educational, research, or commercial purposes with appropriate attribution.

Columns: - Country: Name of the country (Pakistan, India, Bangladesh, Afghanistan, and Sri Lanka). - Year: The year of recorded data. - Total Population: Total population of the country for the given year. - Net Migration: Net migration value (immigration minus emigration).

Key Insights (1960–2023) - Pakistan: Steady growth from 45M (1960) to 240M (2023), with varying migration trends influenced by political and economic changes. - India: Rapid increase from 450M (1960) to 1.43B (2023), with consistently low net migration. - Bangladesh: Population rose from 55M (1960) to 170M (2023), showing negative net migration due to significant emigration. - Afghanistan: Marked by volatile migration due to conflict; population increased from 8M (1960) to 41M (2023). - Sri Lanka: Moderate growth from 10M (1960) to 22M (2023), with net migration losses during periods of civil unrest.

Eurostat's annual collections of statistics on international migration flows are structured as follows:

• NOWCAST: Annual collection of provisional monthly data on live births and deaths covering at least 6 months of the reference year (Article 4.3 of https://eur-lex.europa.eu/eli/reg_impl/2014/205/oj/eng" target="_self">Commission Implementing Regulation (EU) No 205/2014) and provisional monthly data on migrants covering at least 6 months of the reference year on a voluntary basis.
• DEMOBAL (Demographic balance): Annual collection of provisional data on population, total live births and total deaths at national level (Article 4.1 of Commission Implementing Regulation (EU) No 205/2014) and provisional data on total migrants at national level on a voluntary basis.
• POPSTAT (population statistics): The most in-depth annual national and regional data collection on demography and migration, for population, births, deaths, immigrants, emigrants, marriages and divorces by a large number of breakdowns. (Article 3 of Regulation (EU) No 1260/2013 and Article 3 of Regulation (EC) No 862/2007).

The aim is to collect annual mandatory and voluntary data from the national statistical institutes. Mandatory data are those defined by the legislation listed under ‘6.1. Institutional mandate — legal acts and other agreements’.

The quality of the demographic data collected on a voluntary basis depends on the availability and quality of information provided by the national statistical institutes.

For more information on mandatory/voluntary data collection, see 6.1. Institutional mandate — legal acts and other agreements.

The following data on migrants are collected under unified demographic data collection:

• Immigrants by age, sex and:
  • Country of citizenship;
  • Country of birth;
  • Country of previous residence.
• Immigrants by country of citizenship and country of birth.
• Emigrants by age, sex and:
  • Country of citizenship;
  • Country of birth;
  • Country of next residence.

Gross in- and out-migration statisitcs are provided in this file for each county (or county equivalent) in the United States. Migrant data are stratified by age, race, and sex. Included for each race/sex/age group are data on college attendance, military status, group quarters status, residence abroad in 1975, and total population. Data on country of birth are listed for race/sex strata.

Population dynamics, its types. Population migration (external, internal), factors determining it, main trends. Impact of migration on population health.

Under the guidance of Moldoev M.I. Sir By Riya Patil and Rutuja Sonar

Abstract

Population dynamics influence development and vice versa, at various scale levels: global, continental/world-regional, national, regional, and local. Debates on how population growth affects development and how development affects population growth have already been subject of intensive debate and controversy since the late 18th century, and this debate is still ongoing. While these two debates initially focused mainly on natural population growth, the impact of migration on both population dynamics and development is also increasingly recognized. While world population will continue growing throughout the 21st century, there are substantial and growing contrasts between and within world-regions in the pace and nature of that growth, including some countries where population is stagnating or even shrinking. Because of these growing contrasts, population dynamics and their interrelationships with development have quite different governance implications in different parts of the world.

1. Population Dynamics

Population dynamics refers to the changes in population size, structure, and distribution over time. These changes are influenced by four main processes:

Birth rate (natality)

Death rate (mortality)

Immigration (inflow of people)

Emigration (outflow of people)

Types of Population Dynamics

Natural population change: Based on birth and death rates.

Migration-based change: Caused by people moving in or out of a region.

Demographic transition: A model that explains changes in population growth as societies industrialize.

Population distribution: Changes in where people live (urban vs rural).

2. Population Migration

Migration refers to the movement of people from one location to another, often across political or geographical boundaries.

Types of Migration

External migration (international):

Movement between countries.

Examples: Refugee relocation, labor migration, education.

Internal migration:

Movement within the same country or region.

Examples: Rural-to-urban migration, inter-state migration.

3. Factors Determining Migration

Migration is influenced by push and pull factors:

Push factors (reasons to leave a place):

Unemployment

Conflict or war

Natural disasters

Poverty

Lack of services or opportunities

Pull factors (reasons to move to a place):

Better job prospects

Safety and security

Higher standard of living

Education and healthcare access

Family reunification

4. Main Trends in Migration

Urbanization: Mass movement to cities for work and better services.

Global labor migration: Movement from developing to developed countries.

Refugee and asylum seeker flows: Due to conflict or persecution.

Circular migration: Repeated movement between two or more locations.

Brain drain/gain: Movement of skilled labor away from (or toward) a country.

5. Impact of Migration on Population Health

Positive Impacts:

Access to better healthcare (for migrants moving to better systems).

Skills and knowledge exchange among health professionals.

Remittances improving healthcare affordability in home countries.

Negative Impacts:

Migrants’ health risks: Increased exposure to stress, poor living conditions, and occupational hazards.

Spread of infectious diseases: Especially when health screening is lacking.

Strain on health services: In receiving areas, especially with sudden or large influxes.

Mental health challenges: Due to cultural dislocation, discrimination, or trauma.

Population dynamics is one of the fundamental areas of ecology, forming both the basis for the study of more complex communities and of many applied questions. Understanding population dynamics is the key to understanding the relative importance of competition for resources and predation in structuring ecological communities, which is a central question in ecology.

Population dynamics plays a central role in many approaches to preserving biodiversity, which until now have been primarily focused on a single species approach. The calculation of the intrinsic growth rate of a species from a life table is often the central piece of conservation plans. Similarly, management of natural resources, such as fisheries, depends on population dynamics as a way to determine appropriate management actions.

Population dynamics can be characterized by a nonlinear system of difference or differential equations between the birth sizes of consecutive periods. In such a nonlinear system, when the feedback elasticity of previous events on current birth size is larger, the more likely the dynamics will be volatile. Depending on the classification criteria of the population, the revealed cyclical behavior has various interpretations. Under different contextual scenarios, Malthusian cycles, Easterlin cycles, predator–prey cycles, dynastic cycles, and capitalist–laborer cycles have been introduced and analyzed

Generally, population dynamics is a nonlinear stochastic process. Nonlinearities tend to be complicated to deal with, both when we want to do analytic stochastic modelling and when analysing data. The way around the problem is to approximate the nonlinear model with a linear one, for which the mathematical and statistical theories are more developed and tractable. Let us assume that the population process is described as:

(1)Nt=f(Nt−1,εt)

where Nt is population density at time t and εt is a series of random variables with identical distributions (mean and variance). Function f specifies how the population density one time step back, plus the stochastic environment εt, is mapped into the current time step. Let us assume that the (deterministic) stationary (equilibrium) value of the population is N* and that ε has mean ε*. The linear approximation of Eq. (1) close to N* is then:

(2)xt=axt−1+bϕt

where xt=Nt−N*, a=f

f(N*,ε*)/f

N, b=ff(N*,ε*)/fε, and ϕt=εt−ε*

The term population refers to the members of a single species that can interact with each other. Thus, the fish in a lake, or the moose on an island, are clear examples of a population. In other cases, such as trees in a forest, it may not be nearly so clear what a population is, but the concept of population is still very useful.

Population dynamics is essentially the study of the changes in the numbers through time of a single species. This is clearly a case where a quantitative description is essential, since the numbers of individuals in the population will be counted. One could begin by looking at a series of measurements of the numbers of particular species through time. However, it would still be necessary to decide which changes in numbers through time are significant, and how to determine what causes the changes in numbers. Thus, it is more sensible to begin with models that relate changes in population numbers through time to underlying assumptions. The models will provide indications of what features of changes in numbers are important and what measurements are critical to make, and they will help determine what the cause of changes in population levels might be.

To understand the dynamics of biological populations, the study starts with the simplest possibility and determines what the dynamics of the population would be in that case. Then, deviations in observed populations from the predictions of that simplest case would provide information about the kinds of forces shaping the dynamics of populations. Therefore, in describing the dynamics in this simplest case it is essential to be explicit and clear about the assumptions made. It would not be argued that the idealized population described here would ever be found, but that focusing on the idealized population would provide insight into real populations, just as the study of Newtonian mechanics provides understanding of more realistic situations in physics.

Population migration

The vast majority of people continue to live in the countries where they were born —only one in 30 are migrants.

In most discussions on migration, the starting point is usually numbers. Understanding changes in scale, emerging trends, and shifting demographics related to global social and economic transformations, such as migration, help us make sense of the changing world we live in and plan for the future. The current global estimate is that there were around 281 million international migrants in the world in 2020, which equates to 3.6 percent of the global population.

Overall, the estimated number of international migrants has increased over the past five decades. The total estimated 281 million people living in a country other than their countries of birth in 2020 was 128 million more than in 1990 and over three times the estimated number in 1970.

There is currently a larger number of male than female international migrants worldwide and the growing gender gap has increased over the past 20 years. In 2000, the male to female split was 50.6 to 49.4 per cent (or 88 million male migrants and 86 million female migrants). In 2020 the split was 51.9 to 48.1 per cent, with 146 million male migrants and 135 million female migrants. The share of

Projected Net International Migration by Single Year of Age, Sex, Race, and Hispanic Origin for the United States: 2016-2060 // Source: U.S. Census Bureau, Population Division // There are four projection scenarios: 1. Main series, 2. High Immigration series, 3. Low Immigration series, and 4. Zero Immigration series. // Note: Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. // For detailed information about the methods used to create the population projections, see https://www2.census.gov/programs-surveys/popproj/technical-documentation/methodology/methodstatement17.pdf. // Population projections are estimates of the population for future dates. They are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. The Population Estimates and Projections Program provides additional information on its website: https://www.census.gov/programs-surveys/popproj.html.

Abstract

Monitoring of External Migration Situation in Armenia through Sample Survey Program commissioned by the State Committee of Science of the Republic of Armenia and being currently implemented by Russian–Armenian (Slavonic) University.

The Socio-Demographic Research Center of the Slavonic University (“Research Center”) has been engaged in analyzing migration decisions in Armenia as part of its ongoing Three-Year Program on monitoring migration through collection of household survey data and is therefore uniquely placed to analyze the situation with regards to migration in 2017. The 2017 household survey of migration conducted by “Research Center” is a follow-up survey (repeated cross-section) to those conducted in the years 2015 and 2016.

The survey gives an opportunity to: - Assess the influence of external migration on living conditions of households; - Restructure the whole timetable of trips done by migrant members of households prior to the monitoring; - Measure migration potential of population; - Analyze separate survey questionnaires for returned migrants and migrants staying abroad to reveal the issues they face abroad and after arrival to Armenia, a cause–effect relationship of the phenomenon, etc.

Geographic coverage

National

Analysis unit

Individuals and Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Similar to the studies done in 2015 and 2016, this year methodology of the study has been based on multistage stratified and cluster sampling. At the primary stage of sampling the research group has determined that unit of observation is a household. The sample size: 2100 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The main instrument of the study is the survey questionnaire, which consists of the Tittle Page and 5 sections: Section 1. Welfare and remittances Section 2. Socio-demographic and economic characteristics of household members Section 3. The schedule of migration departures and arrivals from the given settlement of present and absent h/h members since 2014 Section 4. Returnees from abroad Section 5. Those who are abroad

Population in The Netherlands on 1 January by sex, age, marital status, generation and migration background.

CBS is in transition towards a new classification of the population by origin. Greater emphasis is now placed on where a person was born, aside from where that person’s parents were born. The term ‘migration background’ is no longer used in this regard. The main categories western/non-western are being replaced by categories based on continents and a few countries that share a specific migration history with the Netherlands. The new classification is being implemented gradually in tables and publications on population by origin.

Data available from 1996 to 2022.

Status of the figures: All figures in the table are final.

Changes per 13 January 2023: None, this table was discontinued.

When will new figures be published? No longer applicable. This table is succeeded by the table Population; sex, age, country of origin, country of birth, 1 January. See section 3.

Bell Ringer activities designed to support Advanced Placement Human Geography.

The number of people living in urban neighborhoods has been rising in recent decades. This Commentary investigates changes in the number, ages, and financial status of those who have been moving into and out of urban neighborhoods, using data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel. I find that since 2000, the increase in urban populations is the result of young adults migrating into urban neighborhoods and senior citizens aging in place. Urban populations have also become more educated and well to do. While declining urban neighborhoods may still outnumber growing urban neighborhoods within some regions, urban leaders there can work toward population or tax base growth knowing that consumer tastes and national trends are favorable to those goals.

In Arab States, migrants made up more than ********** of the total population. Moreover, migrant workers made up over 40 percent of the total workforce in the region. Migrants made up nearly ** percent of the population aged 15 years or more in North America, and ** percent in Western, Southern, and Northern Europe.

The three indicators are all expressed as the change in the number of persons per 1000 persons of average population: total change, natural change (live births minus deaths) and net migration (including statistical adjustment). The net migration plus adjustment is calculated as the difference between the total change and the natural change of the population.

Estimate of net migrations for area from Washington Data and Research, Office of Financial Management, Washington(April 1, 2018 press release and data products).

In 2020, there was an estimated migrant stock in the world of over *** million people. Of these, *** million resided in Europe or North America. North Africa and the Middle East were the second most common destination of migrants in the world. Moreover, a high number of migrants live within the same region as their country of origin. This is especially the case in Europe and North America, as well as Central and South Asia, North Africa and the Middle East, and Sub-Saharan Africa. There are varying reasons for people to emigrate from their country of origin, from poverty and unemployment to war and persecution.

3-for-3 activities designed to support Advanced Placement Human Geography.

Countries used for estimates of bilateral international migration flows based on methods presented in Abel & Cohen (2019) and Abel & Cohen (2022). The countries in the list correspond to both the estimates in the Figshare collection for the total bilateral international migration flow estimates and the Figshare collection for the sex-specifc bilateral international migration flow estimates.Version DetailsThe countries in the list are for the update of estimates of international migration flows based on the most recent published UN DESA International Migrant Stock (IMS2024) and World Population Prospects (WPP2024) data inputs. Refer to the version history for previous country list files based on older versions of the IMS and WPP data.

This data collection provides net migration estimates by age, race, and sex for counties of the United States. Population data are included along with absolute net migration data and net migration ratios (rates) for the period 1970-1980. Summary records for states, divisions, regions and the United States are also supplied. Several data categories are presented in the collection. Vital Statistics data tabulate births by sex and race (white and non white) for the periods 1970-1974 and 1975-1979 and deaths by race from 1970-1979 as well as adjusted total population for 1970 and 1980 by race. The Enumerated and Adjusted 1970 and 1980 Population categories offer population totals by race and sex and further subdivide these totals into 16 5-year age ranges. Net Migration Estimates and Net Migration Rates are available also, with totals by sex and race presented along with the 16 age divisions.

By 2050, internal climate migrants may account for more than *** percent of the population in North Africa and roughly *** percent of the population of Sub-Saharan Africa. This estimate is based on a pessimistic scenario of high greenhouse gases emission and unequal development. Across the *** regions studied, over *** percent of the population is projected to be displaced by the mid-century. Who are the climate migrants? Climate migrants leave their homes due to unfavorable or harsh environmental changes influenced by global climate change. Estimating or pinpointing new regions where these climate stressors are the causal link for migration requires complex models or calculations. As migration is not solely based on climate change, socio-economic factors, such as political stability, failing economies, or human rights abuses play a substantial role. Concerns of rising temperatures Since the Industrial Revolution, the global average surface temperature has risen by over *** degree Celsius. This temperature rise brings unfamiliar local weather patterns, making some types of extreme weather events more frequent. In recent years, the number of people displaced by weather disasters has increased due to unfavorable conditions such as heatwaves, droughts, increased rainfall, flooding, and sea-level rise.

Update of estimates of international migration flows Abel & Cohen (2019) based on newly published WPP (WPP2019) demographic inputs by the United Nations.A description of the changes in the estimates can be found here

Data Details:

Row for each migration corridor - period combination (200 origins x 200 destinations x 5 periods = 200,000).year0 - first year of five year periodorig - origin ISO three letter country codedest - destination ISO three letter country Columns for estimates based on the following migration flow estimation methods:Stock Differencing Approaches:sd_drop_neg - see for example Beine, M., Docquier, F., & Özden, Ç. (2011). Diasporas. Journal of Development Economics, 95(1), 30–41. https://doi.org/10.1016/j.jdeveco.2009.11.004sd_rev_neg - see for example Beine, M., & Parsons, C. R. (2015). Climatic Factors as Determinants of International Migration. The Scandinavian Journal of Economics, 117(2), 723–767. https://doi.org/10.1111/sjoe.12098

Migration Rate Approach:mig_rate - see Dennett, A. (2016). Estimating an Annual Time Series of Global Migration Flows - An Alternative Methodology for Using Migrant Stock Data. In Global Dynamics (pp. 125–142). Chichester, UK: John Wiley & Sons, Ltd. https://doi.org/10.1002/9781118937464.ch7

Demographic Accounting Approaches:da_min_open - see Abel, G. J. (2013). Estimating global migration flow tables using place of birth data. Demographic Research, 28(March), 505–546. https://doi.org/10.4054/DemRes.2013.28.18

da_min_closed - see Abel, G. J. (2018). Estimates of Global Bilateral Migration Flows by Gender between 1960 and 2015. International Migration Review, 52(3), 809–852. https://doi.org/10.1111/imre.12327

da_pb_closed - see Azose, J. J., & Raftery, A. E. (2019). Estimation of emigration, return migration, and transit migration between all pairs of countries. Proceedings of the National Academy of Sciences, 116(1), 116–122. https://doi.org/10.1073/PNAS.1722334116

Argentina AR: Net Migration data was reported at 3,454.000 Person in 2024. This records a decrease from the previous number of 4,133.000 Person for 2023. Argentina AR: Net Migration data is updated yearly, averaging 4,931.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 47,659.000 Person in 1984 and a record low of -23,687.000 Person in 2001. Argentina AR: Net Migration data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Argentina – Table AR.World Bank.WDI: Population and Urbanization Statistics. Net migration is the net total of migrants during the period, that is, the number of immigrants minus the number of emigrants, including both citizens and noncitizens.;United Nations Population Division. World Population Prospects: 2024 Revision.;Sum;