Data

World population growth

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About this data

World population growth
Average exponential rate of growth of the population over a given period. It is calculated as ln(P2/P1) where P1 and P2 are the populations on subsequent years. Available from 1700 to 2100, based on data and estimates from different sources.
Source
HYDE (2023); Gapminder (2022); UN WPP (2024)with major processing by Our World in Data
Last updated
July 15, 2024
Next expected update
July 2026
Date range
1700–2100
Unit
%

Sources and processing

PBL Netherlands Environmental Assessment Agency – History Database of the Global Environment

This database presents an update and expansion of the History Database of the Global Environment (HYDE, v 3.3) and replaces former HYDE 3.2 version from 2017. HYDE is and internally consistent combination of updated historical population estimates and land use. Categories include cropland, with a new distinction into irrigated and rain fed crops (other than rice) and irrigated and rain fed rice. Also grazing lands are provided, divided into more intensively used pasture, converted rangeland and non-converted natural (less intensively used) rangeland. Population is represented by maps of total, urban, rural population and population density as well as built-up area. The period covered is 10 000 BCE to 2023 CE. Spatial resolution is 5 arc minutes (approx. 85 km2 at the equator), the files are in ESRI ASCII grid format.

Retrieved on
January 2, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Utrecht University/PBL Netherlands Environmental Assessment Agency - History Database of the Global Environment (HYDE v 3.3, 2023).
Klein Goldewijk, C.G.M., Beusen, A., Doelman, J., Stehfest, E., 2017, Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953

This database presents an update and expansion of the History Database of the Global Environment (HYDE, v 3.3) and replaces former HYDE 3.2 version from 2017. HYDE is and internally consistent combination of updated historical population estimates and land use. Categories include cropland, with a new distinction into irrigated and rain fed crops (other than rice) and irrigated and rain fed rice. Also grazing lands are provided, divided into more intensively used pasture, converted rangeland and non-converted natural (less intensively used) rangeland. Population is represented by maps of total, urban, rural population and population density as well as built-up area. The period covered is 10 000 BCE to 2023 CE. Spatial resolution is 5 arc minutes (approx. 85 km2 at the equator), the files are in ESRI ASCII grid format.

Retrieved on
January 2, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Utrecht University/PBL Netherlands Environmental Assessment Agency - History Database of the Global Environment (HYDE v 3.3, 2023).
Klein Goldewijk, C.G.M., Beusen, A., Doelman, J., Stehfest, E., 2017, Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953

Gapminder – Population

Gapminder's population data is divided into two chunks: One long historical trend for the global population that goes back to 10,000 BC. And the second chunk is country estimates that only reaches back to 1800.

For the first chunk, several sources were used. You can learn more at https://docs.google.com/spreadsheets/d/1hkLbEilJbl630IG68q-aQJlUjuTFm9b_12nQMVd1sZM/edit#gid=0. For the second chunk, Gapminder uses UN population data between 1950 to 2100 from the UN Population Division World Population Prospects 2019, and the forecast to the year 2100 uses their medium-fertility variant.

For years before 1950, this version uses the data documented in greater detail by Mattias Lindgren in version 3. The main source was Angus Maddison's data, which CLIO Infra Project maintained and improved. Note that when combining version 3 with the new UN data, the trends for a few countries didn't match up in the overlapping year 1950.

Minor adjustments were made to the years before and after to smooth out discrepancies between the two sources and avoid spurious jumps in Gapminder's visualisations.

Visit https://www.gapminder.org/data/documentation/gd003/ to learn more about the methodology used and the data from back to 10,000 BC.

Retrieved on
March 31, 2023
Retrieved from
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Gapminder Population v7 (2022)

Gapminder's population data is divided into two chunks: One long historical trend for the global population that goes back to 10,000 BC. And the second chunk is country estimates that only reaches back to 1800.

For the first chunk, several sources were used. You can learn more at https://docs.google.com/spreadsheets/d/1hkLbEilJbl630IG68q-aQJlUjuTFm9b_12nQMVd1sZM/edit#gid=0. For the second chunk, Gapminder uses UN population data between 1950 to 2100 from the UN Population Division World Population Prospects 2019, and the forecast to the year 2100 uses their medium-fertility variant.

For years before 1950, this version uses the data documented in greater detail by Mattias Lindgren in version 3. The main source was Angus Maddison's data, which CLIO Infra Project maintained and improved. Note that when combining version 3 with the new UN data, the trends for a few countries didn't match up in the overlapping year 1950.

Minor adjustments were made to the years before and after to smooth out discrepancies between the two sources and avoid spurious jumps in Gapminder's visualisations.

Visit https://www.gapminder.org/data/documentation/gd003/ to learn more about the methodology used and the data from back to 10,000 BC.

Retrieved on
March 31, 2023
Retrieved from
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Gapminder Population v7 (2022)

United Nations – World Population Prospects

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

Retrieved on
July 11, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

Retrieved on
July 11, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

United Nations – World Population Prospects - Interim Update

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

This is an interim update containing revised medium-variant estimates and projections for Togo.

Retrieved on
March 31, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

This is an interim update containing revised medium-variant estimates and projections for Togo.

Retrieved on
March 31, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

Gapminder – Systema Globalis

Data by Gapminder on population and other indicators. It provides data on former countries and regions.

Retrieved on
March 31, 2023
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Gapminder - Systema Globalis (2023)

Data by Gapminder on population and other indicators. It provides data on former countries and regions.

Retrieved on
March 31, 2023
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Gapminder - Systema Globalis (2023)

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator

Combination of different sources

We construct our long-run data by combining multiple sources:

  • 10,000 BCE–1799: historical estimates by HYDE (v3.3). Growth rate estimated over 50-year periods.

  • 1800–1949: historical estimates by Gapminder (v7). Growth rate estimated over 1-year periods.

  • 1950–2023: population records from the United Nations World Population Prospects (2024 revision). We use the UN's published growth rates directly (based on mid-year population estimates).

Display filtering

To reduce noise in sparse historical data, growth rates are selectively displayed:

  • 1700–1799: Only 100-year intervals (1700, 1800)

  • 1800–1899: Only 100-year intervals (1800, 1900)

  • 1900–1949: Only 5-year intervals (1900, 1905, 1910, etc.)

  • 1950 onwards: All years (annual data)

  • 2024-2100: Projections based on Medium variant by the UN World Population Prospects (2024 revision). Growth rate estimated over 1-year periods.

Geographical aggregates

  • For most years, we calculate aggregates by summing the population of member countries.
  • We do this based on our definition of continents and the World Bank’s income groups.
  • The only exception is before 1800, where we use HYDE's estimates for continents (but not income groups).

For most of the years, we've estimated regional aggregates by summing the population of countries in each region. We've relied on our continents and World Bank income group definitions. The only exception is before 1800, where we've used HYDE's estimates on continents (but not income groups).

World

  • Before 1800: we use data from HYDE.
  • 1800-1950: we estimate the global population by summing all available countries in the dataset.
  • After 1950, we rely on estimates from the United Nations World Population Prospects.

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: World population growth”, part of the following publication: Hannah Ritchie, Lucas Rodés-Guirao, Edouard Mathieu, Marcel Gerber, Esteban Ortiz-Ospina, Joe Hasell, and Max Roser (2023) - “Population Growth”. Data adapted from PBL Netherlands Environmental Assessment Agency, Gapminder, United Nations. Retrieved from https://archive.ourworldindata.org/20260402-163007/grapher/population-growth-rate.html [online resource] (archived on April 2, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

HYDE (2023); Gapminder (2022); UN WPP (2024) – with major processing by Our World in Data

Full citation

HYDE (2023); Gapminder (2022); UN WPP (2024) – with major processing by Our World in Data. “World population growth” [dataset]. PBL Netherlands Environmental Assessment Agency, “History Database of the Global Environment 3.3”; Gapminder, “Population v7”; United Nations, “World Population Prospects”; United Nations, “World Population Prospects - Interim Update”; Gapminder, “Systema Globalis” [original data]. Retrieved April 3, 2026 from https://archive.ourworldindata.org/20260402-163007/grapher/population-growth-rate.html (archived on April 2, 2026).

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/population-growth-rate.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/population-growth-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/population-growth-rate.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/population-growth-rate.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/population-growth-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/population-growth-rate.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/population-growth-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/population-growth-rate.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear