Population
1.7M persons, 1 July latest value, 2023
Population on 1 July. UN estimate to 2023, medium variant from 2024; past UN revisions for forecast checks.
Kosovo
All indicators of the Macroscope base for Kosovo, with sources. Below: what past UN and IMF releases projected and what actually happened.
GDP per capita, PPP
16,461
constant 2021 international $, 2025
What the data shows
Computed with the same code as the observations under the main chart and in the API (get_insights). Moving together in time does not prove a cause.
How the indicators changed
- Fertility (TFR): 6.95 in 1950 → 1.55 in 2023 (−78%). Threshold: below 2.1 since 2011. The trend broke around 1987 and 1993: −0.08 → −0.22 → −0.04 a year.
- Births: 34.7k in 1950 → 20.5k in 2023 (−41%). Peak: 61.2k in 1988; the latest value is 66% lower. The trend broke around 1987 and 1999: +0.66k → −1.76k → −0.77k a year.
- Population: 779k in 1950 → 1.7M in 2023 (+118%). Peak: 2.2M in 1997; the latest value is 23% lower. The trend broke around 1996 and 2002: +31.6k → −52.6k → −3.45k a year.
- Internet: 83.9% in 2017 → 89.4% in 2018 (+5.5 pp).
- Urban share: 19.1% in 1960 → 50.9% in 2025 (+32 pp). Threshold: above 50% since 2024. The trend broke around 1987 and 2014: +0.63 → +0.07 → +1.2 a year.
- GDP per person (PPP): 7,098 PPP dollars in 2008 → 16,461 PPP dollars in 2025 (+132%).
- GDP growth: on average 3.4% in the 2000s, 4.6% in the 2010s, 3.7% in the 2020s. Lowest: −5.3% in 2020; highest: 10.7% in 2021.
- Inflation: on average 2.8% in the 2000s, 2.0% in the 2010s, 4.3% in the 2020s. Lowest: −2.4% in 2009; highest: 11.7% in 2001.
- Net migration: on average 0.53k a year in the 1950s, −1.08k a year in the 1960s, 0.51k a year in the 1970s, −3.85k a year in the 1980s, −49k a year in the 1990s, −25.3k a year in the 2000s, −21.8k a year in the 2010s, −23.3k a year in the 2020s.
- Life expectancy, men: 43 years in 1950 → 75.8 years in 2023 (+33 years). Low: 41.5 years in 1951; +34 years since then. Threshold: above 70 years since 2002. The trend broke around 2012: change slowed down (+0.51 → +0.04 a year).
What changed at the same time
- The fastest decline of "Fertility (TFR)" was in 1984–1994: 4.41 → 2.52. Over the same years: births 59.4k → 44.3k; population 1.76M → 2.11M; urban share 34.3% → 37.3%; net migration −3.74k a year → 0.44k a year; life expectancy, men 59.7 years → 66.6 years; no data for the others in those years.
- Over the last 10 years (2013–2023): fertility (TFR) 1.95 → 1.55; births 29.9k → 20.5k; population 1.82M → 1.7M; urban share 38.6% → 49.1%; GDP per person (PPP) 8,828 PPP dollars → 14,240 PPP dollars; GDP growth 5.3% → 4.1%; inflation 1.8% → 4.9%; net migration −16.4k a year → −28.8k a year; life expectancy, men 74.3 years → 75.8 years; no data for the others in those years.
How the indicators relate
- Fertility (TFR) and urban share (1960–2023, 64 years): levels are strongly related, in opposite directions (r = −0.94); year-to-year changes show no reliable link (r = 0.10). This looks like a shared trend: both change over time, but not in step from year to year.
- Fertility (TFR) and GDP per person (PPP) (2008–2023, 16 years): levels are strongly related, in opposite directions (r = −0.91); year-to-year changes show no reliable link (r = −0.19). This looks like a shared trend: both change over time, but not in step from year to year.
Against other countries
- Fertility (TFR), adjusted for income: countries with the same GDP per person (14,240 PPP dollars) typically have 2.19; here it is 1.55, lower than in 90% of countries at this income (2023, 197 countries).
- Order of events: fertility below 3: 1992; fertility below 2.1: 2011; half the population online: already in 2017; urban majority: 2024. Fertility fell below 3 after the urban share passed 50% in 69% of 111 countries where the order is known; median gap 9 years. Fertility fell below 2.1 before half the population went online in 88% of 112 countries where the order is known.
Forecasts vs actual
- Fertility (TFR): past UN projections. The outcome was below the projection in 0 of 1 revisions (2022–2022) and above in 1; median gap +2.5%.
- Fertility (TFR): UN 2024 projection (medium): 2050 — 1.51 (−2% vs 2023), 2100 — 1.56 (+1% vs 2023); low variant for 2100: 1.06.
- Births: past UN projections. The outcome was below the projection in 0 of 1 revisions (2022–2022) and above in 1; median gap +11%.
- Births: UN 2024 projection (medium): 2050 — 13.3k (−35% vs 2023), 2100 — 7.46k (−64% vs 2023); low variant for 2100: 1.95k.
- Population: past UN projections. The outcome was below the projection in 0 of 1 revisions (2022–2022) and above in 1; median gap +2.2%.
- Population: UN 2024 projection (medium): 2050 — 1.64M (−3% vs 2023), 2100 — 1.1M (−36% vs 2023); low variant for 2100: 681k.
- Why the UN missed the population. The 2022 projection for 2023: 1.66M; the UN's 2024 estimate: 1.7M (+2.2%). Parts of the gap (plus means more people than projected): the starting population +79k, births +5.3k, deaths −1.1k (more deaths than expected), migration −47.3k; the largest: the starting population.
- Population: the IMF and the UN disagree. The IMF (April 2026) puts it at 1.59M in 2024, the UN (WPP 2024) at 1.69M: the IMF is 6% lower. Part of the gap may come from whom and which territory each counts.
- GDP growth: IMF next-year forecasts (30 editions, 2010–2024). On average the outcome was 0.2 pp below the forecast; below it in 40% of cases; typical error ±1.8 pp. The biggest miss was for 2020: IMF, April 2019 expected 4%, the outcome was −5.3%.
- GDP growth: latest IMF forecast (IMF, April 2026): 2026 — 3.3%, 2028 — 4%, 2031 — 4%.
- Inflation: IMF next-year forecasts (30 editions, 2010–2024). On average the outcome was 0.9 pp above the forecast; below it in 50% of cases; typical error ±1.8 pp. The biggest miss was for 2022: IMF, April 2021 expected 1.5%, the outcome was 11.6%.
- Inflation: latest IMF forecast (IMF, April 2026): 2026 — 5.9%, 2028 — 2.2%, 2031 — 2%.
- Net migration: UN 2024 projection (medium): 2030 — −7.23k a year, 2050 — −3.1k a year, 2100 — −0.55k a year.
- Life expectancy, men: UN 2024 projection (medium): 2030 — 77.2 years, 2050 — 81.2 years, 2100 — 87.8 years.
Wars and births
- War of 1998–1999 on the country's territory (UCDP/PRIO; about 1,754 battle deaths). Against peace-time countries whose fertility was close the year before the war (Albania, Uruguay, Tunisia, Réunion, Vietnam and 5 more), net of each country's pre-war trend: births during the war +9.2%, 1–5 years after it −0.3%, 6–10 years after +14%; fertility (children per woman) during the war +0.65, 1–5 years after it +1.39, 6–10 years after +1.94.
- All wars together: of 101 wars on countries' territory since 1955, births 1–5 years after the end were above comparable peace-time countries in 42% of cases (median −1.6%). No significant post-war rise shows up.
UN projections vs actual
Solid line: actual data, UN WPP 2024 estimates; births and fertility from national statistics from the last year they matched the UN estimate (the UN's figures for the latest years are partly its own projection). Dashed: medium variants of past UN revisions. The table shows what each revision expected for the latest year (or five-year period) with actual data.
Population
persons, 1 July
- Actual
- UN 2022
- UN 2024, medium
| Release | Target period | Horizon | Expected | Actual | Actual vs expected |
|---|---|---|---|---|---|
| UN 2022 | 2023 | 1 year | 1.66M | 1.7M | +2.2% |
Births
births per year
- Actual
- UN 2022
- UN 2024, medium
| Release | Target period | Horizon | Expected | Actual | Actual vs expected |
|---|---|---|---|---|---|
| UN 2022 | 2023 | 1 year | 18.5k | 20.5k | +10.6% |
Total fertility rate
children per woman
- Actual
- UN 2022
- UN 2024, medium
| Release | Target period | Horizon | Expected | Actual | Actual vs expected |
|---|---|---|---|---|---|
| UN 2022 | 2023 | 1 year | 1.51 | 1.55 | +2.5% |
Deaths
thousand deaths per year
- Actual
- UN 2022
- UN 2024, medium
| Release | Target period | Horizon | Expected | Actual | Actual vs expected |
|---|---|---|---|---|---|
| UN 2022 | 2023 | 1 year | 10 | 10 | +3% |
Infant mortality
deaths under age 1 per 1,000 live births
- Actual
- UN 2022
- UN 2024, medium
| Release | Target period | Horizon | Expected | Actual | Actual vs expected |
|---|---|---|---|---|---|
| UN 2022 | 2023 | 1 year | 6 | 8.1 | +34.6% |
Net migration
persons per year
- Actual
- UN 2022
- UN 2024, medium
| Release | Target period | Horizon | Expected | Actual | Actual vs expected |
|---|---|---|---|---|---|
| UN 2022 | 2023 | 1 year | −5k | −28.8k | −24k a year |
Life expectancy at birth, women
years
- Actual
- UN 2022
- UN 2024, medium
| Release | Target period | Horizon | Expected | Actual | Actual vs expected |
|---|---|---|---|---|---|
| UN 2022 | 2023 | 1 year | 81.9 | 80.1 | −1.8 yrs |
Life expectancy at birth, men
years
- Actual
- UN 2022
- UN 2024, medium
| Release | Target period | Horizon | Expected | Actual | Actual vs expected |
|---|---|---|---|---|---|
| UN 2022 | 2023 | 1 year | 77.4 | 75.8 | −1.6 yrs |
* The five-year period is not over: the projection is compared with the mean of its years so far (UN facts end in 2023).
IMF forecasts vs actual
Solid line: actual values from the latest IMF edition (data get revised, so we use the newest). Dashed: April editions, current year and five years ahead. The table covers next-year forecasts from all editions: mean error shows bias, mean absolute error shows accuracy.
Real GDP growth
% per year
- Actual (IMF)
- WEO, April editions
| Indicator | Forecasts | Mean error | Mean absolute error | Actual below forecast |
|---|---|---|---|---|
| Real GDP growth | 30 | −0.2 pp | 1.8 pp | 40% |
| Inflation | 30 | +0.9 pp | 1.8 pp | 50% |
| Government gross debt | 17 | −5.5 pp | 6.2 pp | 88% |
| Government budget balance | 27 | +1 pp | 1.7 pp | 22% |
All indicators
Demography
Births
20.5k births per year latest value, 2023
Live births per calendar year. UN WPP 2024 and national statistics (64 countries, 2015-2025).
Deaths
10 thousand deaths per year latest value, 2023
Deaths per calendar year (UN estimate to 2023, medium variant from 2024); past UN revisions for forecast checks.
Natural change
10.5 thousand persons per year latest value, 2023
Births minus deaths in the year (UN). Negative: natural decrease, more deaths than births.
Rate of natural change
6.2 per 1,000 population per year latest value, 2023
Births minus deaths in the year per 1,000 people (UN). With the net migration rate it makes up population growth.
Life expectancy at 65
16.9 years latest value, 2023
Years a person aged 65 would still live at the mortality rates of the year; both sexes (UN).
Infant mortality
8.1 deaths under age 1 per 1,000 live births latest value, 2023
Children per 1,000 live births who die before their first birthday (UN); past UN revisions for forecast checks.
Total fertility rate
1.55 children per woman latest value, 2023
Average number of children a woman would have at the age-specific fertility rates of the year.
Life expectancy at birth, women
80.1 years latest value, 2023
Years a newborn girl would live at the mortality rates of the year (UN).
Life expectancy at birth, men
75.8 years latest value, 2023
Years a newborn boy would live at the mortality rates of the year (UN).
Median age
31.4 years latest value, 2023
Age that divides the population in two halves (UN).
Mean age of mothers at childbirth
29.7 years latest value, 2023
Mean age of mothers at the birth of their children of any order (UN).
Sex ratio at birth
107.1 boys per 100 girls latest value, 2023
Boys born per 100 girls born (UN).
Crude marriage rate
8.21 marriages per 1,000 people latest value, 2025
Marriages in the year per 1,000 people: marriages from national offices (Korea, Japan, Taiwan, China, the USA, the UK, Russia, Brazil and others, where they publish more than the international databases), Eurostat and the UN, divided by the UN WPP 2024 population. Where most births are within marriage, marriages come before births.
Source: Kosovo Agency of Statistics
Marriages
13.7k marriages a year latest value, 2025
Marriages in the year (couples). National offices (Korea, Japan, Taiwan, China, the USA, the UK, Russia, Brazil and others), Eurostat for Europe, the UN for the rest; by year of registration or of occurrence, as each country counts.
Source: Kosovo Agency of Statistics
Adolescent fertility rate
7.7 births per 1,000 women aged 15-19 latest value, 2024
Births to women aged 15-19 per 1,000 women of that age (World Bank, from UN World Population Prospects).
Old-age dependency
14.7 persons 65+ per 100 aged 20-64 latest value, 2020
Persons aged 65+ per 100 aged 20-64, every five years (UN).
Children under 15
362 thousand persons, 1 July latest value, 2023
Children aged 0-14 on 1 July: the sum of the five-year groups 0-4, 5-9 and 10-14 (UN; estimate to 2023, medium variant from 2024).
Children under 5
102 thousand persons, 1 July latest value, 2023
Children aged 0-4 on 1 July (UN; estimate to 2023, medium variant from 2024).
People aged 65 and over
164 thousand persons, 1 July latest value, 2023
People aged 65 and over on 1 July: the sum of the five-year groups from 65-69 to 100+ (UN; estimate to 2023, medium variant from 2024).
People aged 80 and over
28 thousand persons, 1 July latest value, 2023
People aged 80 and over on 1 July: the sum of the five-year groups from 80-84 to 100+ (UN; estimate to 2023, medium variant from 2024).
Migration
Net migration
−28.8k persons per year latest value, 2023
Immigrants minus emigrants per year (UN estimate and projection). Past UN revisions for forecast checks.
Net migration rate
−16.94 per 1,000 population per year latest value, 2023
Immigrants minus emigrants per year per 1,000 people: UN net migration divided by the population on 1 July. Comparable across countries of any size.
Personal remittances received
17.3 % of GDP latest value, 2025
Money sent home by people working or living abroad, percent of the receiving country's GDP (World Bank, from IMF balance of payments data).
Citizens under temporary protection in Europe
0 thousand persons, end of year latest value, 2026
Citizens of the country under temporary protection in the EU, Iceland, Liechtenstein, Norway and Switzerland (all 31 report from 2022), end of December. For the running year: the latest month all have published. Granted from March 2022 to people fleeing the war in Ukraine: almost all are Ukrainians; for other countries, their citizens who lived in Ukraine. Eurostat, migr_asytpsm.
Economy
GDP per capita, PPP
16,461 constant 2021 international $ latest value, 2025
Gross domestic product per person at purchasing power parity, constant 2021 international dollars (World Bank, ICP).
Real GDP growth
3.6 % per year latest value, 2025
Annual change of GDP at constant prices. Actual values and forecasts from IMF WEO editions.
Inflation
3.9 % per year, average latest value, 2025
Change of the annual average consumer price index (IMF WEO).
Government gross debt
17.9 % of GDP latest value, 2024
General government gross debt, percent of GDP (IMF WEO).
Unemployment rate
10.9 % of labour force latest value, 2023
Unemployed as a share of the labour force (IMF WEO; national definitions).
GDP per capita, US dollars
7,902 current US dollars latest value, 2025
GDP per person in current US dollars at market exchange rates (IMF WEO).
Government budget balance
−0.3 % of GDP latest value, 2024
General government net lending (+, surplus) or borrowing (−, deficit), percent of GDP (IMF WEO).
Current account balance
−9.2 % of GDP latest value, 2025
Balance of trade in goods and services, income and transfers with the rest of the world, percent of GDP: plus means the country earns abroad more than it spends (IMF WEO).
Society
Urban population
50.9 % of population latest value, 2025
Share of people living in urban areas as defined by national statistical offices (World Bank, from UN World Urbanization Prospects).
Life expectancy at birth
78.2 years latest value, 2024
Life expectancy at birth, both sexes (World Bank, from UN and national statistics).
Digitalisation
Internet users
89.4 % of population latest value, 2018
Share of individuals who used the Internet in the last three months from any device. ITU data.
Mobile cellular subscriptions
34.5 per 100 people latest value, 2022
Active mobile cellular subscriptions per 100 people; can exceed 100 when people have several SIM cards. ITU data.
Generative AI use, age 16–74
44.85 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Use of generative AI tools: in the last 3 months.
Generative AI for private use, age 16–74
41.24 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Use of generative AI tools: for private purposes.
Generative AI for work, age 16–74
24.29 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Use of generative AI tools: for professional (work) purposes.
Generative AI for formal education, age 16–74
20.39 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Use of generative AI tools: for formal education.
Social networking, age 16–74
83.18 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: participating in social networks (creating user profile, posting messages or other contributions to facebook, twitter, etc.).
Instant messaging, age 16–74
92.94 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: instant messaging, i.e. exchanging messages, for example, via Skype, Messenger, WhatsApp, Viber.
Internet calls, age 16–74
97.6 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: telephoning or video calls.
Finding goods and services online, age 16–74
49.39 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: finding information about goods and services.
Online news, age 16–74
76.43 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: reading online news sites/newspapers/news magazines.
Podcasts, age 16–74
19.08 % of individuals aged 16–74 latest value, 2024
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: listening to or downloading podcasts (last 3 months).
Playing or downloading games, age 16–74
31.89 % of individuals aged 16–74 latest value, 2024
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: playing or downloading games.
Online music and downloads, age 16–74
64.41 % of individuals aged 16–74 latest value, 2024
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: listening to music (e.g. web radio, music streaming) or downloading music.
Streamed TV and video, age 16–74
78.45 % of individuals aged 16–74 latest value, 2024
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: watching internet streamed TV or videos.
Internet TV, age 16–74
56.37 % of individuals aged 16–74 latest value, 2024
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: watching internet streamed TV (live or catch-up) from TV broadcasters.
Video on demand, age 16–74
34.42 % of individuals aged 16–74 latest value, 2024
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: watching video on demand from commercial services.
Video-sharing services, age 16–74
69.81 % of individuals aged 16–74 latest value, 2024
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: watching video content from sharing services.
Online courses, age 16–74
10.83 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: doing an online course (of any subject).
Email, age 16–74
48.8 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: sending/receiving e-mails.
Health information online, age 16–74
68.06 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Internet use: seeking health information.
Daily internet use, age 16–74
98.04 % of individuals aged 16–74 latest value, 2025
Eurostat survey, all individuals aged 16–74, both sexes, not only internet users. Use during the last three months; year denotes survey year. Categories overlap; gaps and definition changes are not filled, source flags are retained in the typed dataset. Frequency of internet access: daily.
At least basic digital skills: low education, ages 16–74
51.05 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
At least basic digital skills: high education, ages 16–74
91.97 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Above basic digital skills: ages 16–74
9.14 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
At least basic digital skills: ages 16–74
75.59 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Communication: at least basic digital skills: ages 16–74
98.26 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Content creation: at least basic skills: ages 16–74
97.69 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Information literacy: at least basic skills: ages 16–74
85.71 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Problem solving: at least basic digital skills: ages 16–74
85.46 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Safety: at least basic digital skills: ages 16–74
97.02 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
At least basic digital skills: ages 16–24
93.13 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
At least basic digital skills: ages 65–74
29.46 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Generative AI use: low education, ages 16–74
18.59 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Generative AI use: high education, ages 16–74
74.56 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Generative AI use: ages 16–24
85.33 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Generative AI use: ages 65–74
5.45 % of individuals in the stated group latest value, 2025
Eurostat survey of individuals aged 16–74; percent of everyone in the stated group, not only internet users. Survey year. DSI 2.0 is a proxy based on reported activities in five areas, not an examination; at least basic overall skills require at least basic skills in all five areas. Education: ISCED 0–2, 3–4, 5–8. Other group characteristics are not controlled. AI use refers to the last three months; purposes can overlap. Source flags and missing values retained; groups and components must not be added.
Energy
Electricity demand per person
4,432 kWh per person a year latest value, 2025
Electricity demand (generation plus net imports, Ember) divided by the UN WPP 2024 population. A physical measure that is hard to dress up.
Source: Ember, Yearly Electricity Data
Electricity demand growth
1.8 % per year latest value, 2025
Change in electricity demand from the previous year (Ember). Useful to set against official GDP growth.
Source: Ember, Yearly Electricity Data
Wind and solar share of electricity
6.8 % of generation latest value, 2025
Share of wind and solar power in electricity generation (Ember).
Source: Ember, Yearly Electricity Data
Low-carbon share of electricity
10.9 % of generation latest value, 2025
Share of renewables and nuclear power in electricity generation (Ember).
Source: Ember, Yearly Electricity Data
Coal share of electricity
88.9 % of generation latest value, 2025
Share of coal power in electricity generation (Ember).
Source: Ember, Yearly Electricity Data
Carbon intensity of electricity
902 g CO2e per kWh latest value, 2025
Greenhouse gas emissions of electricity generation per kilowatt-hour (Ember).
Source: Ember, Yearly Electricity Data
Electricity generation
5.9 TWh per year latest value, 2025
Total electricity generation in the country (Ember). Imports are excluded. A volume, not the share of a fuel.
Source: Ember, Yearly Electricity Data
Electricity generation emissions
5.3 Mt CO2e per year latest value, 2025
Greenhouse gas emissions of electricity generation (Ember), not of the whole economy.
Source: Ember, Yearly Electricity Data
Security
Military expenditure
1.5 % of GDP latest value, 2024
Government military expenditure, percent of GDP (World Bank, from SIPRI).
Deaths in organised violence
0 persons a year latest value, 2025
Deaths in state-based conflict, non-state conflict and one-sided violence against civilians, by where the events took place (UCDP GED, best estimate). 0 means no organised violence above UCDP thresholds (25 deaths a year in one conflict). Events in Gaza and the West Bank are counted for Palestine.
Deaths in organised violence per 100,000
0 per 100,000 people a year latest value, 2025
Deaths in organised violence (UCDP GED) per 100,000 people (population: UN WPP 2024).
Armed conflict in the country
0 0 none, 1 minor, 2 war latest value, 2025
Strongest armed conflict of the year in which the government or territory of the country is disputed (UCDP/PRIO ACD): 1 = 25-999 battle-related deaths, 2 = war, 1,000 or more. In interstate conflicts every primary party is marked even if the fighting was elsewhere (the USA in Iraq, 2003). Historical states are mapped to present-day countries by territory (USSR, Yugoslavia, South Vietnam and others).
Battle deaths
0 persons a year latest value, 2025
Soldiers and civilians killed in combat in state-based armed conflicts on the territory of the country. 1946-1988: PRIO Battle Deaths (best estimate, else the low one; a conflict of several countries split equally); from 1989: UCDP GED by place of the events. For the same conflicts in 1989-2008 PRIO is 1.6 times UCDP, so the drop in 1989 is partly a change of source. One-sided violence against civilians is not included.
Battle deaths per 100,000
0 per 100,000 people a year latest value, 2025
Battle deaths on the territory of the country (PRIO to 1988, UCDP GED from 1989) per 100,000 people (population: UN WPP 2024), from 1950.
Intentional homicides (per 100,000 people)
1.9 per 100,000 people latest value, 2021
An intentional homicide is defined as an unlawful death inflicted upon a person with the intent to cause death or serious injury.
Purchases and money
Commercial bank branches (per 100,000 adults)
19.7 per 100,000 adults latest value, 2024
Commercial bank branches are retail locations of resident commercial banks and other resident banks that function as commercial banks that provide financial services to customers and are physically separated from the main office but not organized as legally separated subsidiaries.
Account ownership at a financial institution or with a mobile-money-service provider (% of population ages 15+)
64.2 % of people aged 15+ latest value, 2024
Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (% age 15+).
Account ownership at a financial institution or with a mobile-money-service provider, male (% of population ages 15+)
68.8 % of men aged 15+ latest value, 2024
Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (male, % age 15+).
Account ownership at a financial institution or with a mobile-money-service provider, female (% of population ages 15+)
59.8 % of women aged 15+ latest value, 2024
Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (female, % age 15+).
Six or more online purchases in three months
4.6 % of people aged 16-74 latest value, 2025
ICT survey, all individuals aged 16-74, not only internet users or buyers. Reference window is defined by the selected Eurostat category; since 2020.
Households and NPISHs final consumption expenditure (% of GDP)
82.3 % of GDP latest value, 2025
This field includes expenditure on goods and services by the Household and NPISH sector for the direct satisfaction of human needs or wants, whether individual or collective. This indicator is expressed as a percentage of Gross Domestic Product (GDP) which is the total income earned through the production of goods and services in an economic territory during an accounting period.
Source: Households and NPISHs final consumption expenditure (% of GDP)
Households and NPISHs Final consumption expenditure per capita (constant 2015 US$)
5,124.5 constant 2015 US dollars latest value, 2025
This field includes expenditure on goods and services by the Household and NPISH sector for the direct satisfaction of human needs or wants, whether individual or collective. The core indicator has been divided by the general population to achieve a per capita estimate.This indicator is expressed in constant prices, meaning the series has been adjusted to account for price changes over time. The reference year for this adjustment is 2015. This indicator is expressed in United States dollars.
Source: Households and NPISHs Final consumption expenditure per capita (constant 2015 US$)
Income share held by lowest 20%
4.5 % of income or consumption latest value, 2022
Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.
Source: Income share held by lowest 20%
Gini index
38.3 index, 0-100 latest value, 2022
Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.
Source: Gini index
Income quintile share ratio S80/S20
15.6 ratio latest value, 2018
Equivalised disposable income of the top population quintile divided by the bottom quintile, EU-SILC. Survey and income reference years may differ.
Source: Income quintile share ratio S80/S20 for disposable income by sex and age group
Income share held by highest 20%
42.4 % of income or consumption latest value, 2022
Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.
Source: Income share held by highest 20%
Adjusted savings: net national savings (% of GNI)
13.8 % of gross national income latest value, 2021
Net national savings are equal to gross national savings less the value of consumption of fixed capital. This indicator is expressed as a percentage of Gross National Income (GNI) which is the total income earned by all residents within an economic territory during an accounting period. It is equal to gross domestic product plus earned income receivable from abroad minus earned income payable abroad.
Never bought online
32 % of people aged 16-74 latest value, 2025
ICT survey, all individuals aged 16-74, not only internet users or buyers. Reference window is defined by the selected Eurostat category; since 2020.
Online purchase in the last year
58.4 % of people aged 16-74 latest value, 2025
ICT survey, all individuals aged 16-74, not only internet users or buyers. Reference window is defined by the selected Eurostat category; since 2020.
Online purchase in the last three months
42.1 % of people aged 16-74 latest value, 2025
ICT survey, all individuals aged 16-74, not only internet users or buyers. Reference window is defined by the selected Eurostat category; since 2020.
Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population)
10 % of population, 2021 PPP latest value, 2022
Poverty headcount ratio at $3.00 a day is the percentage of the population living on less than $3.00 a day at 2021 purchasing power adjusted prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.
Source: Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population)
Health
Diabetes prevalence (% of population ages 20 to 79)
10.4 % of people aged 20-79 latest value, 2024
Diabetes prevalence refers to the percentage of people ages 20-79 who have type 1 or type 2 diabetes. It is calculated by adjusting to a standard population age-structure.
Bad or very bad self-rated health
11.3 % of people aged 16+ in group latest value, 2018
Self-rated bad or very bad health, EU-SILC, both sexes aged 16+. Not a medical diagnosis.
Source: Self-perceived health by sex, age and income quintile
Bad or very bad self-rated health in the highest income quintile
7.6 % of people aged 16+ in group latest value, 2018
Self-rated bad or very bad health, EU-SILC, both sexes aged 16+. Not a medical diagnosis.
Source: Self-perceived health by sex, age and income quintile
Bad or very bad self-rated health in the lowest income quintile
16.6 % of people aged 16+ in group latest value, 2018
Self-rated bad or very bad health, EU-SILC, both sexes aged 16+. Not a medical diagnosis.
Source: Self-perceived health by sex, age and income quintile
Unmet medical examination needs
5.2 % of people aged 16+ in group latest value, 2019
Self-reported unmet medical examination needs due to cost, distance or waiting lists, EU-SILC, age 16+. Source flags and questionnaire changes are preserved; do not add reasons.
Unmet medical examination needs in the highest income quintile
3 % of people aged 16+ in group latest value, 2019
Self-reported unmet medical examination needs due to cost, distance or waiting lists, EU-SILC, age 16+. Source flags and questionnaire changes are preserved; do not add reasons.
Unmet medical examination needs in the lowest income quintile
9.2 % of people aged 16+ in group latest value, 2019
Self-reported unmet medical examination needs due to cost, distance or waiting lists, EU-SILC, age 16+. Source flags and questionnaire changes are preserved; do not add reasons.
Land and housing
People in housing rented at market price
0.5 % of population latest value, 2018
Population by housing tenure, all household types and income groups, EU-SILC. Denominator is people, not dwellings.
Source: Distribution of population by tenure status, type of household and income group
People in housing with a mortgage
4.7 % of population latest value, 2018
Population by housing tenure, all household types and income groups, EU-SILC. Denominator is people, not dwellings.
Source: Distribution of population by tenure status, type of household and income group
Housing cost overburden
11.3 % of population latest value, 2018
People in households with housing costs exceeding 40% of disposable income, EU-SILC; all ages and sexes.
Source: Housing cost overburden rate by age, sex and poverty status
Housing overcrowding
64.1 % of population latest value, 2018
People in overcrowded dwellings under the EU-SILC room-based definition; all ages and sexes.
Source: Overcrowding rate by age, sex and poverty status - total population
People in owner-occupied housing
97.8 % of population latest value, 2018
Population by housing tenure, all household types and income groups, EU-SILC. Denominator is people, not dwellings.
Source: Distribution of population by tenure status, type of household and income group
Everyday environment
Unable to keep home adequately warm
40.2 % of population in group latest value, 2018
Self-reported inability to keep home adequately warm, EU-SILC. The at-risk group has income below 60% of the national median.
Unable to keep home adequately warm (at risk of poverty)
53.1 % of population in group latest value, 2018
Self-reported inability to keep home adequately warm, EU-SILC. The at-risk group has income below 60% of the national median.
Access to electricity (% of population)
100 % of population latest value, 1999
Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.
Household electricity price
0.08 euro per kWh, mean of both half-years latest value, 2025
Arithmetic mean of both half-year prices including taxes in the selected Eurostat consumption band. Partial years excluded; not a sales-weighted annual price.
Source: Electricity prices for household consumers - bi-annual data (from 2007 onwards)
Municipal waste generated
267 kg per inhabitant latest value, 2024
Municipal waste by treatment operation, Eurostat, kg per inhabitant. National scope of municipal waste differs.
Municipal waste landfilled
267 kg per inhabitant latest value, 2024
Municipal waste by treatment operation, Eurostat, kg per inhabitant. National scope of municipal waste differs.
Municipal waste recycled
0 kg per inhabitant latest value, 2024
Municipal waste by treatment operation, Eurostat, kg per inhabitant. National scope of municipal waste differs.
Work and skills
Learning poverty: Share of Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)
37.9 % of children of end-of-primary age latest value, 2021
The share of 10-year-olds who cannot read and understand a short passage of age-appropriate material—in other words, those who are below the “minimum proficiency” threshold for reading. This measure is defined as the union of two deprivations: 1) schooling deprivation and 2) learning deprivation. A child is considered schooling-deprived (SD) if he or she is of primary school age and out-of-school. The dimension of learning deprivation (LD) applies only for children in school, and identifies those pupils who are below the minimum proficiency level (MPL) for reading, as defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. This “union approach” to measurement reflects the choice that, as presented in the SDGs, all age 10 children must be both in school and learning. The final learning poverty measure combines the two dimensions in a single indicator using the following formula: LP = SD + [(1-SD) x LD]
New business density (new registrations per 1,000 people ages 15-64)
8.3 per 1,000 people aged 15-64 latest value, 2024
The number of newly registered firms with limited liability per 1,000 working-age people (ages 15-64) per calendar year.
Source: New business density (new registrations per 1,000 people ages 15-64)
Share of youth not in education, employment or training, total (% of youth population)
30 % of youth aged 15-24 latest value, 2024
The share of youth not in education, employment or training (also known as “the NEET rate”) conveys the number of young persons not in education, employment or training as a percentage of the total youth population. Youth not in education are those who were neither enrolled in school nor in a formal training program (e.g. vocational training). For the purposes of this indicator, youth is defined as all persons between the ages of 15 and 24 (inclusive).
Source: Share of youth not in education, employment or training, total (% of youth population)
Science, space and technology
New cars: battery-electric (BEV), share
1.4 % of new car registrations latest value, 2025
Share of first registrations of new passenger cars in the year (close to sales; not the whole stock). Battery-electric: battery and electric motor only, no petrol or diesel engine (Eurostat code ELC). Eurostat, road_eqr_carpda.
New cars: plug-in hybrids (PHEV), share
0.5 % of new car registrations latest value, 2025
Share of first registrations of new passenger cars in the year (close to sales; not the whole stock). Plug-in hybrids: a battery charged from the grid plus a petrol or diesel engine (ELC_PET_PI + ELC_DIE_PI). Eurostat, road_eqr_carpda.
New cars: hybrids without a plug, share
7.6 % of new car registrations latest value, 2025
Share of first registrations of new passenger cars in the year (close to sales; not the whole stock). Ordinary hybrids without a plug (full and mild): the engine charges the battery; these are not electric cars (ELC_PET_HYB + ELC_DIE_HYB). Eurostat, road_eqr_carpda.
New cars: petrol, excluding hybrids, share
9.6 % of new car registrations latest value, 2025
Share of first registrations of new passenger cars in the year (close to sales; not the whole stock). Petrol cars without any hybrid drive (PET_X_HYB). Eurostat, road_eqr_carpda.
New cars: diesel, excluding hybrids, share
81 % of new car registrations latest value, 2025
Share of first registrations of new passenger cars in the year (close to sales; not the whole stock). Diesel cars without any hybrid drive (DIE_X_HYB). Eurostat, road_eqr_carpda.
New battery-electric cars (BEV): registrations
539 cars a year latest value, 2025
First registrations of new battery-electric passenger cars in the year (close to sales). Battery-electric: battery and electric motor only, no petrol or diesel engine (Eurostat code ELC). Eurostat, road_eqr_carpda.
All cars on the road: battery-electric (BEV), share
0.3 % of all passenger cars latest value, 2025
Share of all registered passenger cars at the end of the year (the stock, not the sales of the year). Battery-electric: battery and electric motor only, no petrol or diesel engine (Eurostat code ELC). Eurostat, road_eqs_carpda.
All cars on the road: plug-in hybrids (PHEV), share
0.3 % of all passenger cars latest value, 2025
Share of all registered passenger cars at the end of the year (the stock, not the sales of the year). Plug-in hybrids: a battery charged from the grid plus a petrol or diesel engine (ELC_PET_PI + ELC_DIE_PI). Eurostat, road_eqs_carpda.
All cars on the road: hybrids without a plug, share
2.6 % of all passenger cars latest value, 2025
Share of all registered passenger cars at the end of the year (the stock, not the sales of the year). Ordinary hybrids without a plug (full and mild): the engine charges the battery; these are not electric cars (ELC_PET_HYB + ELC_DIE_HYB). Eurostat, road_eqs_carpda.
Religion and beliefs
Christians — population share
5.6 % of population latest value, 2020
Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Christians — population
100 thousand persons latest value, 2020
Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Muslims — population share
94.3 % of population latest value, 2020
Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Muslims — population
1,650 thousand persons latest value, 2020
Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Religiously unaffiliated — population share
0.1 % of population latest value, 2020
Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Religious diversity — country rank
152 rank among 201 latest value, 2020
Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Religious diversity index
1.3 index points (0–10) latest value, 2020
Pew index, 0–10, based on seven broad groups. 10 means seven equal groups; 0 means everyone belongs to one group. Does not measure religious freedom, intensity of belief or conflict. Values below 0.1 are retained as bounds in the table. Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Religious composition: balance between two groups
2.2 index points (0–10) latest value, 2020
Pew index, 0–10, based on seven broad groups. 10 means two equal groups, which may be any two religions. It is not an affiliated/unaffiliated index. Does not measure religious freedom, intensity of belief or conflict. Values below 0.1 are retained as bounds in the table. Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Religiously affiliated — population share
99.9 % of population latest value, 2020
Macroscope calculation: total population minus Unaffiliated. A subtotal of six religious groups, not an eighth group or a count of believers in God. Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Religiously affiliated — population
1,750 thousand persons latest value, 2020
Macroscope calculation: total population minus Unaffiliated. A subtotal of six religious groups, not an eighth group or a count of believers in God. Pew estimates for all ages in 2010 and 2020 from the same revised 2025 release. Harmonised census/survey religious identification, not practising believers. Unaffiliated does not mean atheist or without beliefs. Other religions include folk traditions, Sikhs, Jains, Baha’is and others. The 2026 appendix displays shares below 0.1% as <0.1%; the interactive table displays populations below 10,000 as <10,000; these are retained as bounds in dimensions.operator and omitted from exact chart points. Other counts are rounded to 10,000 and shares to 0.1 percentage point. No intervening years are filled. Affiliated is a derived subtotal of the six religious groups and must not be added to them. Regions/world overlap with countries and must not be summed. Diversity ranks describe only the seven broad groups; a larger rank means less diversity, not less freedom.
Source: Pew Research Center: religious composition, 2010 and 2020
Government restrictions on religion
3.4 index points (0–10) latest value, 2023
Pew coding of published materials for 2023, 198 countries and territories. Scores from 0 to 10, not population percentages. GRI covers government restrictions; SHI covers hostile acts by private individuals and groups. They measure different things and must not be summed. North Korea is not scored due to insufficient reliable observations; missing is not no restrictions. Released June 15, 2026.
Source: Pew Research Center: religious restrictions and social hostilities
Social hostilities involving religion
3.5 index points (0–10) latest value, 2023
Pew coding of published materials for 2023, 198 countries and territories. Scores from 0 to 10, not population percentages. GRI covers government restrictions; SHI covers hostile acts by private individuals and groups. They measure different things and must not be summed. North Korea is not scored due to insufficient reliable observations; missing is not no restrictions. Released June 15, 2026.
Source: Pew Research Center: religious restrictions and social hostilities
Catholics — population, 2010 estimate
50 thousand persons latest value, 2010
Historical all-age estimates for 2010 from Pew’s 2011 release, 232 countries/territories. Pew’s 2025 revision does not update this detailed split: do not splice into the revised Christian total series. Affiliation, not practice. Protestant includes Anglicans and independent churches; Orthodox includes Eastern and Oriental Orthodox churches. Other Christians include, among others, Latter-day Saints and Jehovah’s Witnesses under the source classification. Counts of at least 10,000 are rounded to 10,000; <1,000 and <10,000 remain bounds in the typed table only. The source states that <10,000 means 1,000–9,999, not zero. World is the sum of the five regions in the same release. Netherlands Antilles and Channel Islands are not assigned to a single present-day country. Geography follows the 2011 release; South Sudan is separate. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: Christian traditions, 2010 estimates (2011 release)
Eastern and Oriental Orthodox — population, 2010 estimate
140 thousand persons latest value, 2010
Historical all-age estimates for 2010 from Pew’s 2011 release, 232 countries/territories. Pew’s 2025 revision does not update this detailed split: do not splice into the revised Christian total series. Affiliation, not practice. Protestant includes Anglicans and independent churches; Orthodox includes Eastern and Oriental Orthodox churches. Other Christians include, among others, Latter-day Saints and Jehovah’s Witnesses under the source classification. Counts of at least 10,000 are rounded to 10,000; <1,000 and <10,000 remain bounds in the typed table only. The source states that <10,000 means 1,000–9,999, not zero. World is the sum of the five regions in the same release. Netherlands Antilles and Channel Islands are not assigned to a single present-day country. Geography follows the 2011 release; South Sudan is separate. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: Christian traditions, 2010 estimates (2011 release)
Sunni — adult Muslim self-identification
24 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Shia — adult Muslim self-identification
1 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Ahmadiyya — adult Muslim self-identification
0 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Alevi — adult Muslim self-identification
0 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Bektashi — adult Muslim self-identification
2 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Aliran Kepercayaan — adult Muslim self-identification
0 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Something else — adult Muslim self-identification
0 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Nothing in particular — adult Muslim self-identification
4 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Just a Muslim — adult Muslim self-identification
58 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Don’t know or refused — adult Muslim self-identification
11 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Affiliated with a Sufi order — adult Muslim self-identification
3 % of Muslim adults latest value, 2012
Published weighted responses among Muslim adults aged 18+, Q31 and the published Q32 subtotal; not shares of all residents or all-age population counts. Chart year is the fieldwork end year; exact dates are in the table. Fourteen African samples date to 2008–2009 and the remaining samples to 2011–2012. Sunni/Shia self-identification differs from Pew’s 2009 ethnographic classification: “just a Muslim” is not reassigned to either. Zero is a rounded survey answer, not proof of an absent community. Ahmadiyya, Alevi, Bektashi and Aliran Kepercayaan are volunteered (VOL.) responses. Sufi affiliation is a separate question and overlaps Sunni/Shia identities; do not add it to Q31. Thailand covers only five southern provinces and is a region, never a country chart point. Chad and DR Congo samples are disproportionately urban; some countries exclude inaccessible areas. Several major Muslim populations, including India, Iran and Saudi Arabia, were not surveyed. No world total can be inferred. See the source methodology for country-specific sampling exclusions and margins of error. Macroscope analysis. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here. The opinions expressed herein, including any implications for policy, are those of the author and not of Pew Research Center. Pew Research Center has published the original content in English but has not reviewed or approved this translation.
Source: Pew: adult Muslim self-identification, surveys in 2008–2012
Markets and valuations
Private-sector credit / GDP
65.62 % of GDP latest value, 2025
Financial resources supplied to the private sector by financial corporations relative to GDP. Includes loans and other debt claims; country coverage differs. Neither government debt nor mortgages alone. Source definition: Domestic credit to private sector refers to financial resources provided to the private sector by financial corporations, such as through loans, purchases of nonequity securities, and trade credits and other accounts receivable, that establish a claim for repayment. For some countries these claims include credit to public enterprises. The financial corporations include monetary authorities and deposit money banks, as well as other financial corporations where data are available (including corporations that do not accept transferable deposits but do incur such liabilities as time and savings deposits). Examples of other financial corporations are finance and leasing companies, money lenders, insurance corporations, pension funds, and foreign exchange companies. This indicator is expressed as a percentage of Gross Domestic Product (GDP) which is the total income earned through the production of goods and services in an economic territory during an accounting period.
Bank nonperforming loans
2.03 % of gross loans latest value, 2025
Loans 90+ days overdue or unlikely to be repaid in full divided by gross loans, before provisions and collateral deductions. National rules and coverage can differ. Source definition: The indicator measures the proportion of a deposit taker’s loan portfolio that is impaired or at risk of default. It is calculated as the ratio of non-performing loans (NPLs) to total gross loans, where NPLs are defined as loans that are past due by 90 days or more or are otherwise considered unlikely to be repaid in full without the realization of collateral. Both non-performing loans and total gross loans should be reported at their gross book value, without deducting for loan-loss provisions or collateral. This indicator provides a key measure of asset quality and potential credit risk in the banking system.
Industry and waste
All waste per person (all activities and households)
1,862 kg per person a year latest value, 2022
All waste generated in the year by all economic activities and households per inhabitant, including mineral waste from construction and mining (soil, rock), usually the largest part. Reported every two years (2004-2022). Not municipal waste, which covers only household and similar waste collected by municipalities. Eurostat, env_wasgen.
Waste excluding major mineral waste per person
1,812 kg per person a year latest value, 2022
Waste from all activities and households excluding major mineral wastes (soil, rock, construction and demolition waste) per inhabitant; Eurostat uses it to compare countries with different construction and mining. Reported every two years (2004-2022). Not municipal waste, which covers only household and similar waste collected by municipalities. Eurostat, env_wasgen.
Household waste per person
0 kg per person a year latest value, 2022
Waste generated by households themselves per inhabitant. Not equal to municipal waste, which also includes similar waste from shops and offices. Reported every two years (2004-2022). Not municipal waste, which covers only household and similar waste collected by municipalities. Eurostat, env_wasgen.
Manufacturing waste per person
189 kg per person a year latest value, 2022
Waste generated by manufacturing (NACE section C) per inhabitant of the country. Reported every two years (2004-2022). Not municipal waste, which covers only household and similar waste collected by municipalities. Eurostat, env_wasgen.
Manufacturing, share of GDP
12.5 % of GDP latest value, 2025
Manufacturing value added (ISIC section C: factories, excluding mining, utilities and construction) as a percentage of GDP. The share can fall while output grows if the rest of the economy grows faster. World Bank, WDI. Source note: Manufacturing includes industries classified in ISIC (Rev. 3) major division C and is defined as the physical or chemical transformation of materials or components into new products. Value added is the contribution to the economy by a producer or an industry or an institutional sector, which is estimated by the total value of output produced and deducting the total value of intermediate consumption of goods and services used to produce that output. This indicator is expressed as a percentage of Gross Domestic Product (GDP) which is the total income earned through the production of goods and services in an economic territory during an accounting period.
Industry incl. construction, share of GDP
25 % of GDP latest value, 2025
Value added of industry in the broad sense (mining, manufacturing, utilities and construction; ISIC B-F) as a percentage of GDP. World Bank, WDI. Source note: Industry (including construction) corresponds to ISIC (Rev.4) divisions 05-43. It is comprised of mining, manufacturing, construction, electricity, water, and gas industries. Value added is the contribution to the economy by a producer or an industry or an institutional sector, which is estimated by the total value of output produced and deducting the total value of intermediate consumption of goods and services used to produce that output. This indicator is expressed as a percentage of Gross Domestic Product (GDP) which is the total income earned through the production of goods and services in an economic territory during an accounting period.
Manufacturing value added per person
786 constant 2015 US$ per person latest value, 2025
Manufacturing value added at constant 2015 US dollars divided by population (UN WPP 2024): factory output net of inputs, not revenue. World Bank, WDI. Source note: Manufacturing includes industries classified in ISIC (Rev. 3) major division C and is defined as the physical or chemical transformation of materials or components into new products. Value added is the contribution to the economy by a producer or an industry or an institutional sector, which is estimated by the total value of output produced and deducting the total value of intermediate consumption of goods and services used to produce that output. This indicator is expressed in constant prices, meaning the series has been adjusted to account for price changes over time. The reference year for this adjustment is 2015. This indicator is expressed in United States dollars.
Manufacturing value added per person (UNIDO)
873 constant 2020 US$ per person latest value, 2025
Manufacturing value added (ISIC section C) per person at constant 2020 US dollars. UNIDO National Accounts Database via the UN SDG database (indicator 9.2.1). Differs from the World Bank series by its base year (2020 rather than 2015) and UNIDO estimates for countries without recent accounts. Series: Manufacturing value added per capita (constant 2020 United States dollars).
Source: UNIDO via the UN SDG database: manufacturing value added
Manufacturing, share of GDP (UNIDO)
14.5 % of GDP latest value, 2025
Manufacturing value added as a percentage of GDP, constant prices. UNIDO via the UN SDG database (indicator 9.2.1). Series: Manufacturing value added (constant 2020 United States dollars) as a proportion of GDP (%).
Source: UNIDO via the UN SDG database: manufacturing value added
Municipal waste per person (World Bank)
290 kg per person a year latest value, 2022
Municipal solid waste generation, kg per person a year (kg a day × 365). Municipal solid waste: households plus similar waste from shops, institutions and streets — excluding industrial, construction and mining waste. One reported year a country, the years differ. World Bank, What a Waste 3.0 (2026).
Municipal waste sent to recycling
3 % of municipal waste latest value, 2022
Share of municipal waste sent to recycling, as reported by the country. Sent is not the same as recycled: sorting rejects and exports are included; composting and incineration are not. Municipal solid waste: households plus similar waste from shops, institutions and streets — excluding industrial, construction and mining waste. One reported year a country, the years differ. World Bank, What a Waste 3.0 (2026).
Education and skills
PISA: reading, mean score of 15-year-olds
342 PISA points latest value, 2022
Mean score in the OECD PISA test of reading literacy. Tested: 15-year-old students (aged 15y3m-16y2m, grade 7 or above), a sample in each country; every three years, the 2021 cycle postponed to 2022 because of COVID. PISA scale: in the cycle when the domain was first the major one (2000) the OECD mean = 500, standard deviation = 100; the series is comparable from 2000. A 10-15 point change between cycles is often within the error (standard errors and significance are in the education_pisa dataset). In 2015 the test moved from paper to computer and to a new scaling model: the link to earlier cycles holds, with a link error of a few points. In 2022 several countries (United States, United Kingdom, Canada, Netherlands, Ireland, Denmark, Australia, New Zealand and others) missed sampling standards — compare with caution. Values come from the trend tables of the latest OECD report listing the country (PISA 2022, else 2018, 2015, 2012, 2009 Vol. V). China took part only as provinces (B-S-J-G/Z, Shanghai), not shown here; Russia took part 2000-2018, not in 2022; Argentina, Kazakhstan and Malaysia 2015 are not comparable and not shown, nor is Viet Nam reading 2022. Source: OECD, PISA 2022 Results, Vol. I.
PISA: mathematics, mean score of 15-year-olds
355 PISA points latest value, 2022
Mean score in the OECD PISA test of mathematical literacy. Tested: 15-year-old students (aged 15y3m-16y2m, grade 7 or above), a sample in each country; every three years, the 2021 cycle postponed to 2022 because of COVID. PISA scale: in the cycle when the domain was first the major one (2003) the OECD mean = 500, standard deviation = 100; the series is comparable from 2003. A 10-15 point change between cycles is often within the error (standard errors and significance are in the education_pisa dataset). In 2015 the test moved from paper to computer and to a new scaling model: the link to earlier cycles holds, with a link error of a few points. In 2022 several countries (United States, United Kingdom, Canada, Netherlands, Ireland, Denmark, Australia, New Zealand and others) missed sampling standards — compare with caution. Values come from the trend tables of the latest OECD report listing the country (PISA 2022, else 2018, 2015, 2012, 2009 Vol. V). China took part only as provinces (B-S-J-G/Z, Shanghai), not shown here; Russia took part 2000-2018, not in 2022; Argentina, Kazakhstan and Malaysia 2015 are not comparable and not shown, nor is Viet Nam reading 2022. Source: OECD, PISA 2022 Results, Vol. I.
PISA: science, mean score of 15-year-olds
357 PISA points latest value, 2022
Mean score in the OECD PISA test of scientific literacy. Tested: 15-year-old students (aged 15y3m-16y2m, grade 7 or above), a sample in each country; every three years, the 2021 cycle postponed to 2022 because of COVID. PISA scale: in the cycle when the domain was first the major one (2006) the OECD mean = 500, standard deviation = 100; the series is comparable from 2006. A 10-15 point change between cycles is often within the error (standard errors and significance are in the education_pisa dataset). In 2015 the test moved from paper to computer and to a new scaling model: the link to earlier cycles holds, with a link error of a few points. In 2022 several countries (United States, United Kingdom, Canada, Netherlands, Ireland, Denmark, Australia, New Zealand and others) missed sampling standards — compare with caution. Values come from the trend tables of the latest OECD report listing the country (PISA 2022, else 2018, 2015, 2012, 2009 Vol. V). China took part only as provinces (B-S-J-G/Z, Shanghai), not shown here; Russia took part 2000-2018, not in 2022; Argentina, Kazakhstan and Malaysia 2015 are not comparable and not shown, nor is Viet Nam reading 2022. Source: OECD, PISA 2022 Results, Vol. I.
PISA: reading, share of 15-year-olds below baseline
83.1 % of students latest value, 2022
Share of 15-year-olds who did not reach Level 2 in the PISA reading literacy test (below 407 points) — the level the OECD treats as the baseline for full participation in life and learning. Tested: 15-year-old students (aged 15y3m-16y2m, grade 7 or above), a sample in each country; every three years, the 2021 cycle postponed to 2022 because of COVID. Shares are comparable from 2009 (for reading, the latest OECD reports give shares only from 2009). In 2015 the test moved from paper to computer and to a new scaling model: the link to earlier cycles holds, with a link error of a few points. In 2022 several countries (United States, United Kingdom, Canada, Netherlands, Ireland, Denmark, Australia, New Zealand and others) missed sampling standards — compare with caution. Values come from the trend tables of the latest OECD report listing the country (PISA 2022, else 2018, 2015, 2012, 2009 Vol. V). China took part only as provinces (B-S-J-G/Z, Shanghai), not shown here; Russia took part 2000-2018, not in 2022; Argentina, Kazakhstan and Malaysia 2015 are not comparable and not shown, nor is Viet Nam reading 2022. Source: OECD, PISA 2022 Results, Vol. I.
PISA: mathematics, share of 15-year-olds below baseline
85 % of students latest value, 2022
Share of 15-year-olds who did not reach Level 2 in the PISA mathematical literacy test (below 420 points) — the level the OECD treats as the baseline for full participation in life and learning. Tested: 15-year-old students (aged 15y3m-16y2m, grade 7 or above), a sample in each country; every three years, the 2021 cycle postponed to 2022 because of COVID. Shares are comparable from 2003 (for reading, the latest OECD reports give shares only from 2009). In 2015 the test moved from paper to computer and to a new scaling model: the link to earlier cycles holds, with a link error of a few points. In 2022 several countries (United States, United Kingdom, Canada, Netherlands, Ireland, Denmark, Australia, New Zealand and others) missed sampling standards — compare with caution. Values come from the trend tables of the latest OECD report listing the country (PISA 2022, else 2018, 2015, 2012, 2009 Vol. V). China took part only as provinces (B-S-J-G/Z, Shanghai), not shown here; Russia took part 2000-2018, not in 2022; Argentina, Kazakhstan and Malaysia 2015 are not comparable and not shown, nor is Viet Nam reading 2022. Source: OECD, PISA 2022 Results, Vol. I.
PISA: science, share of 15-year-olds below baseline
79.3 % of students latest value, 2022
Share of 15-year-olds who did not reach Level 2 in the PISA scientific literacy test (below 410 points) — the level the OECD treats as the baseline for full participation in life and learning. Tested: 15-year-old students (aged 15y3m-16y2m, grade 7 or above), a sample in each country; every three years, the 2021 cycle postponed to 2022 because of COVID. Shares are comparable from 2006 (for reading, the latest OECD reports give shares only from 2009). In 2015 the test moved from paper to computer and to a new scaling model: the link to earlier cycles holds, with a link error of a few points. In 2022 several countries (United States, United Kingdom, Canada, Netherlands, Ireland, Denmark, Australia, New Zealand and others) missed sampling standards — compare with caution. Values come from the trend tables of the latest OECD report listing the country (PISA 2022, else 2018, 2015, 2012, 2009 Vol. V). China took part only as provinces (B-S-J-G/Z, Shanghai), not shown here; Russia took part 2000-2018, not in 2022; Argentina, Kazakhstan and Malaysia 2015 are not comparable and not shown, nor is Viet Nam reading 2022. Source: OECD, PISA 2022 Results, Vol. I.
PISA: mathematics, share of top performers (Levels 5-6)
0 % of students latest value, 2022
Share of 15-year-olds reaching Level 5 or 6 in the PISA mathematics test (607 points or more): they solve complex modelling and reasoning tasks. Tested: 15-year-old students (aged 15y3m-16y2m, grade 7 or above), a sample in each country; every three years, the 2021 cycle postponed to 2022 because of COVID. Shares are comparable from 2003. In 2015 the test moved from paper to computer and to a new scaling model: the link to earlier cycles holds, with a link error of a few points. In 2022 several countries (United States, United Kingdom, Canada, Netherlands, Ireland, Denmark, Australia, New Zealand and others) missed sampling standards — compare with caution. Values come from the trend tables of the latest OECD report listing the country (PISA 2022, else 2018, 2015, 2012, 2009 Vol. V). China took part only as provinces (B-S-J-G/Z, Shanghai), not shown here; Russia took part 2000-2018, not in 2022; Argentina, Kazakhstan and Malaysia 2015 are not comparable and not shown, nor is Viet Nam reading 2022. Source: OECD, PISA 2022 Results, Vol. I.
TIMSS: mathematics, grade 4
451 TIMSS score latest value, 2023
Average score of students in their fourth year of school (usually grade 4, about 10 years old) in the international TIMSS mathematics test. The TIMSS scale was set in 1995: 500 is the mean of that cycle's countries and 100 points is one standard deviation; the test is repeated every 4 years, and a country's scores from different cycles are comparable when IEA includes them in its trend table. Year is the test year. In 2019 about half the countries tested on computer (eTIMSS), linked to paper through a bridge sample; in 2023 almost all did. Some countries test the next grade up (Norway, South Africa, Turkey) to keep the average age above the IEA minimum. Values IEA flags as not reliably measured (more than 25% of students too low to estimate) are left out. Russia took part until 2019 and is not in TIMSS 2023. Figures come from the TIMSS 2023 trend tables; for countries absent in 2023, from the TIMSS 2019 report. Source: IEA, TIMSS & PIRLS International Study Center.
Source: IEA Trends in International Mathematics and Science Study (TIMSS)
TIMSS: science, grade 4
403 TIMSS score latest value, 2023
Average score of students in their fourth year of school (usually grade 4, about 10 years old) in the international TIMSS science test. The TIMSS scale was set in 1995: 500 is the mean of that cycle's countries and 100 points is one standard deviation; the test is repeated every 4 years, and a country's scores from different cycles are comparable when IEA includes them in its trend table. Year is the test year. In 2019 about half the countries tested on computer (eTIMSS), linked to paper through a bridge sample; in 2023 almost all did. Some countries test the next grade up (Norway, South Africa, Turkey) to keep the average age above the IEA minimum. Values IEA flags as not reliably measured (more than 25% of students too low to estimate) are left out. Russia took part until 2019 and is not in TIMSS 2023. Figures come from the TIMSS 2023 trend tables; for countries absent in 2023, from the TIMSS 2019 report. Source: IEA, TIMSS & PIRLS International Study Center.
Source: IEA Trends in International Mathematics and Science Study (TIMSS)
PIRLS: reading, grade 4
421 PIRLS score latest value, 2021
Average score of students in their fourth year of school (usually grade 4, about 10 years old) in the international PIRLS reading comprehension test. The PIRLS scale was set in 2001: 500 is the mean of that cycle's countries and 100 points is one standard deviation; the test is repeated every 5 years, and a country's scores from different cycles are comparable when IEA includes them in its trend table. Year is the cycle year. In 2021, because of COVID-19, some countries tested the same children at the beginning of grade 5 (at least 4 months older: the United States, Ireland, Hungary, Croatia, Lithuania and others) and six tested a year later (England, Australia, Brazil, Iran, Israel, South Africa); about half the countries tested on computer (digitalPIRLS). Some countries test the next grade up (Norway, grade 5). Values IEA flags as not reliably measured (more than 25% of students too low to estimate) are left out. Russia took part in every cycle 2001-2021; Moscow City is a separate participant. Figures come from the PIRLS 2021 trend tables; for countries absent there, from the PIRLS 2016 report. Source: IEA, TIMSS & PIRLS International Study Center.
Source: IEA Progress in International Reading Literacy Study (PIRLS)
PIRLS: grade 4 students below the Low reading benchmark
38 % of students latest value, 2021
Share of students in their fourth year of school (about 10) who score below 400 PIRLS points, the Low International Benchmark: finding an explicitly stated detail in a simple text. Computed as 100 minus the IEA-published percentage reaching 400 (whole percentages). The PIRLS scale was set in 2001: 500 is the mean of that cycle's countries and 100 points is one standard deviation; the test is repeated every 5 years, and a country's scores from different cycles are comparable when IEA includes them in its trend table. Year is the cycle year. In 2021, because of COVID-19, some countries tested the same children at the beginning of grade 5 (at least 4 months older: the United States, Ireland, Hungary, Croatia, Lithuania and others) and six tested a year later (England, Australia, Brazil, Iran, Israel, South Africa); about half the countries tested on computer (digitalPIRLS). Some countries test the next grade up (Norway, grade 5). Values IEA flags as not reliably measured (more than 25% of students too low to estimate) are left out. Russia took part in every cycle 2001-2021; Moscow City is a separate participant. Figures come from the PIRLS 2021 trend tables; for countries absent there, from the PIRLS 2016 report. Source: IEA, TIMSS & PIRLS International Study Center.
Source: IEA Progress in International Reading Literacy Study (PIRLS)
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