Andorra
ANDSouthern Europe · Europe · UN member
The circle shows each metric's percentile rank (position among countries with data), which is comparable across metrics. Each metric's native score uses its own scale and is not comparable between metrics — see it (and the full formula) in “How is this calculated?”.
54 metrics for this country
Society & culture
100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
Ranks 44th of 200 · native score 71.53 · reference year 1996
78percentileHow is this calculated?
- Metric
- Adult male height
- Scale
- 100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
- Raw value
- 176.06 cm
- Native score
- 71.53 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 78th percentile — ranks 44th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (176.06 − 159.79) / (182.54 − 159.79) = 71.53Min and max are this dataset's lowest (159.79) and highest (182.54) values, so the score is relative to the current country set.
- Source
- NCD Risk Factor Collaboration (via Our World in Data) · NCD Risk Factor Collaboration (NCD-RisC)
- License
- CC BY 4.0
- Reference year
- 1996
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Pooled analysis of population-based measured-height studies, retrieved via the Our World in Data mirror. Indexed by year of birth.
100 = universal social protection coverage, 0 = none
Ranks 50th of 214 · native score 86.7 · reference year 2022
77percentileHow is this calculated?
- Metric
- Social protection coverage
- Scale
- 100 = universal social protection coverage, 0 = none
- Raw value
- 86.7 % of population
- Native score
- 86.7 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 77th percentile — ranks 50th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (86.7 − 0) / (100 − 0) = 86.7The index is kept on its own published scale.
- Source
- ILOSTAT (International Labour Organization) · International Labour Organization
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- ILOSTAT via the ILO rplumber API (rplumber.ilo.org). CC BY 4.0 for databases published since 3 May 2023.
- Social tolerance (proxy)Tier C
100 = most accepting (fewest object to different-religion neighbours), 0 = least
Ranks 17th of 94 · native score 96.12 · reference year 2022
82percentileLow reliability (Tier C — Survey / proxy). Survey-based, patchy, or proxy metric. Indicative only — coverage gaps and methodology limits are significant. Not a definitive ranking.
How is this calculated?
- Metric
- Social tolerance (proxy)
- Scale
- 100 = most accepting (fewest object to different-religion neighbours), 0 = least
- Raw value
- 3.88446 % who object to different-religion neighbours
- Native score
- 96.12 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 82th percentile — ranks 17th of 94. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 − [ 100 · (3.88 − 0) / (100 − 0) ] = 96.12The index is kept on its own published scale. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Values Survey (via Our World in Data) · World Values Survey Association / Integrated Values Surveys
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier C — Survey / proxy
- Source notes
- Share of survey respondents who mention 'people of a different religion' when asked which groups they would not want as neighbours (World Values Survey / Integrated Values Surveys), via the Our World in Data mirror. A single attitudinal proxy — Tier C.
100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
Ranks 63rd of 174 · native score 66.55 · reference year 2019
64percentileHow is this calculated?
- Metric
- International tourist arrivals
- Scale
- 100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
- Raw value
- 3,090,000 arrivals per year
- Native score
- 66.55 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 63rd of 174. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 3,090,000 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 66.55Log scale (values are heavily skewed). 0 and 100 are the dataset's min (3,700) and max (90,914,000) — relative, not absolute or year-over-year comparable.
- Source
- UN Tourism (via Our World in Data) · UN Tourism (UNWTO)
- License
- CC BY 4.0
- Reference year
- 2019
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- International tourist arrivals — overnight visitors — from UN Tourism (UNWTO), retrieved via the Our World in Data mirror (OWID's processing layer is CC BY; underlying values are UN Tourism).
Demographics & migration
100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
Ranks 200th of 215 · native score 22.97 · reference year 2025
7percentileHow is this calculated?
- Metric
- Age dependency ratio
- Scale
- 100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 39.2385 dependents per 100 working-age
- Native score
- 22.97 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 7th percentile — ranks 200th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (39.24 − 20.05) / (103.59 − 20.05) = 22.97Min and max are this dataset's lowest (20.05) and highest (103.59) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest fertility, 0 = lowest — descriptive, not better or worse
Ranks 206th of 215 · native score 9.27 · reference year 2024
4percentileHow is this calculated?
- Metric
- Fertility rate
- Scale
- 100 = highest fertility, 0 = lowest — descriptive, not better or worse
- Raw value
- 1.087 births per woman
- Native score
- 9.27 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 4th percentile — ranks 206th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.09 − 0.58) / (6.03 − 0.58) = 9.27Min and max are this dataset's lowest (0.58) and highest (6.03) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
Ranks 164th of 215 · native score 34.7 · reference year 2024
24percentileHow is this calculated?
- Metric
- Life expectancy gap (female − male)
- Scale
- 100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
- Raw value
- 3.982 years (female − male)
- Native score
- 34.7 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 24th percentile — ranks 164th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.98 − 0.46) / (10.62 − 0.46) = 34.7Min and max are this dataset's lowest (0.46) and highest (10.62) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = oldest median age, 0 = youngest — descriptive, not better or worse
Ranks 29th of 237 · native score 63.66 · reference year 2023
88percentileHow is this calculated?
- Metric
- Median age
- Scale
- 100 = oldest median age, 0 = youngest — descriptive, not better or worse
- Raw value
- 43.162 years
- Native score
- 63.66 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 88th percentile — ranks 29th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (43.16 − 14.32) / (59.63 − 14.32) = 63.66Min and max are this dataset's lowest (14.32) and highest (59.63) values, so the score is relative to the current country set.
- Source
- UN World Population Prospects (via Our World in Data) · UN DESA, Population Division
- License
- CC BY 3.0 IGO
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- UN World Population Prospects (median age; medium-variant projections), retrieved via the Our World in Data mirror.
100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
Ranks 12th of 214 · native score 59.1 · reference year 2024
95percentileHow is this calculated?
- Metric
- Foreign-born population
- Scale
- 100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
- Raw value
- 59.1 % foreign-born
- Native score
- 59.1 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 12th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (59.1 − 0) / (100 − 0) = 59.1The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse
Ranks 11th of 215 · native score 63.01 · reference year 2025
95percentileHow is this calculated?
- Metric
- Net migration rate
- Scale
- 100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse
- Raw value
- 10.168 per 1,000 people
- Native score
- 63.01 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 11th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (10.17 − -46.91) / (43.67 − -46.91) = 63.01Min and max are this dataset's lowest (-46.91) and highest (43.67) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most populous, 0 = least populous — descriptive, not better or worse
Ranks 195th of 215 · native score 18.14 · reference year 2025
10percentileHow is this calculated?
- Metric
- Total population
- Scale
- 100 = most populous, 0 = least populous — descriptive, not better or worse
- Raw value
- 82,904 people
- Native score
- 18.14 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 10th percentile — ranks 195th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 82,904 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 18.14Log scale (values are heavily skewed). 0 and 100 are the dataset's min (9,492) and max (1,463,865,525) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most dense, 0 = least dense — descriptive, not better or worse
Ranks 68th of 215 · native score 59.83 · reference year 2023
69percentileHow is this calculated?
- Metric
- Population density
- Scale
- 100 = most dense, 0 = least dense — descriptive, not better or worse
- Raw value
- 172.034 people per km²
- Native score
- 59.83 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 69th percentile — ranks 68th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 172.03 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 59.83Log scale (values are heavily skewed). 0 and 100 are the dataset's min (0.14) and max (20,569.7) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
Ranks 163rd of 237 · native score 25.04 · reference year 2050
31percentileHow is this calculated?
- Metric
- Population change (projection)
- Scale
- 100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
- Raw value
- 0.3 % change 2024→2050
- Native score
- 25.04 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 31th percentile — ranks 163rd of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.3 − -32.9) / (99.7 − -32.9) = 25.04Min and max are this dataset's lowest (-32.9) and highest (99.7) values, so the score is relative to the current country set.
- Source
- UN World Population Prospects (via Our World in Data) · UN DESA, Population Division
- License
- CC BY 3.0 IGO
- Reference year
- 2050
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- UN World Population Prospects (median age; medium-variant projections), retrieved via the Our World in Data mirror.
100 = most refugees produced, 0 = fewest — descriptive, not better or worse
Ranks 183rd of 211 · native score 10.19 · reference year 2024
10percentileHow is this calculated?
- Metric
- Refugees (by origin)
- Scale
- 100 = most refugees produced, 0 = fewest — descriptive, not better or worse
- Raw value
- 5 refugees
- Native score
- 10.19 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 10th percentile — ranks 183rd of 211. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 5 among 211 countries = 10.19The score is the country's position in the distribution.
- Source
- UNHCR (via Our World in Data) · UN High Commissioner for Refugees (UNHCR)
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Refugee population by country of origin, retrieved via the Our World in Data mirror.
100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 119th of 193 · native score 2.72 · reference year 2024
38percentileHow is this calculated?
- Metric
- Remittances received
- Scale
- 100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 1.29408 % of GDP
- Native score
- 2.72 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 38th percentile — ranks 119th of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.29 − 0.01) / (47.15 − 0.01) = 2.72Min and max are this dataset's lowest (0.01) and highest (47.15) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fully rural, 0 = fully urban — descriptive, not better or worse
Ranks 180th of 215 · native score 11.05 · reference year 2025
17percentileHow is this calculated?
- Metric
- Rural population share
- Scale
- 100 = fully rural, 0 = fully urban — descriptive, not better or worse
- Raw value
- 11.0507 % rural
- Native score
- 11.05 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 17th percentile — ranks 180th of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (11.05 − 0) / (100 − 0) = 11.05The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse
Ranks 46th of 215 · native score 34.21 · reference year 2024
78percentileHow is this calculated?
- Metric
- Sex ratio at birth
- Scale
- 100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 1.063 male births per female birth
- Native score
- 34.21 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 78th percentile — ranks 46th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.06 − 1.01) / (1.16 − 1.01) = 34.21Min and max are this dataset's lowest (1.01) and highest (1.16) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fully urban, 0 = fully rural — descriptive, not better or worse
Ranks 36th of 215 · native score 88.95 · reference year 2025
83percentileHow is this calculated?
- Metric
- Urbanization
- Scale
- 100 = fully urban, 0 = fully rural — descriptive, not better or worse
- Raw value
- 88.9493 % urban
- Native score
- 88.95 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 83th percentile — ranks 36th of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (88.95 − 0) / (100 − 0) = 88.95The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Environment & infrastructure
- Climate vulnerabilityTier B
100 = least climate-vulnerable (best), 0 = most vulnerable
Ranks 26th of 190 · native score 77.71 · reference year 2024
87percentileHow is this calculated?
- Metric
- Climate vulnerability
- Scale
- 100 = least climate-vulnerable (best), 0 = most vulnerable
- Raw value
- 0.350781 index (0–1, higher = more vulnerable)
- Native score
- 77.71 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 87th percentile — ranks 26th of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (0.35 − 0.26) / (0.66 − 0.26) ] = 77.71Min and max are this dataset's lowest (0.26) and highest (0.66) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- ND-GAIN Country Index (University of Notre Dame) · University of Notre Dame Global Adaptation Initiative
- License
- CC BY 3.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- ND-GAIN vulnerability score. The source ZIP is version-stamped (no stable 'latest' URL), so the snapshot is pinned to a specific release; refreshes are a manual, documented step.
- CO₂ emissions per capitaTier A
100 = lowest emissions per capita (best), 0 = highest
Ranks 151st of 214 · native score 29.67 · reference year 2024
30percentileHow is this calculated?
- Metric
- CO₂ emissions per capita
- Scale
- 100 = lowest emissions per capita (best), 0 = highest
- Raw value
- 5.18166 tonnes CO₂ per capita
- Native score
- 29.67 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 30th percentile — ranks 151st of 214. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 5.18 among 214 countries ] = 29.67The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- Global Carbon Project (via Our World in Data) · Global Carbon Project
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita CO₂ emissions from the Global Carbon Project's Global Carbon Budget, retrieved via the Our World in Data mirror.
- Access to electricityTier A
100 = universal electricity access, 0 = none
Ranks 1st of 214 · native score 100 · reference year 2023
70percentileHow is this calculated?
- Metric
- Access to electricity
- Scale
- 100 = universal electricity access, 0 = none
- Raw value
- 100 % of population
- Native score
- 100 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 1st of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (100 − 0) / (100 − 0) = 100The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most fixed-broadband subscriptions per capita, 0 = fewest
Ranks 4th of 208 · native score 85.86 · reference year 2024
98percentileHow is this calculated?
- Metric
- Fixed broadband subscriptions
- Scale
- 100 = most fixed-broadband subscriptions per capita, 0 = fewest
- Raw value
- 52.3554 per 100 people
- Native score
- 85.86 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 98th percentile — ranks 4th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (52.36 − 0) / (60.97 − 0) = 85.86Min and max are this dataset's lowest (0) and highest (60.97) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most forested, 0 = least — descriptive, not better or worse
Ranks 94th of 213 · native score 34.04 · reference year 2023
56percentileHow is this calculated?
- Metric
- Forest area
- Scale
- 100 = most forested, 0 = least — descriptive, not better or worse
- Raw value
- 34.0426 % of land area
- Native score
- 34.04 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 56th percentile — ranks 94th of 213. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (34.04 − 0) / (100 − 0) = 34.04The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Internet usersTier A
100 = whole population online, 0 = none
Ranks 33rd of 209 · native score 94.4 · reference year 2024
84percentileHow is this calculated?
- Metric
- Internet users
- Scale
- 100 = whole population online, 0 = none
- Raw value
- 94.3976 % of population
- Native score
- 94.4 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 84th percentile — ranks 33rd of 209. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (94.4 − 0) / (100 − 0) = 94.4The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- PM2.5 air pollutionTier A
100 = cleanest air (lowest PM2.5), 0 = most polluted
Ranks 40th of 200 · native score 80.25 · reference year 2023
80percentileHow is this calculated?
- Metric
- PM2.5 air pollution
- Scale
- 100 = cleanest air (lowest PM2.5), 0 = most polluted
- Raw value
- 8.88302 µg/m³
- Native score
- 80.25 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 80th percentile — ranks 40th of 200. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 8.88 among 200 countries ] = 80.25The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Protected land areaTier A
100 = most land protected, 0 = least
Ranks 52nd of 212 · native score 27.3 · reference year 2025
76percentileHow is this calculated?
- Metric
- Protected land area
- Scale
- 100 = most land protected, 0 = least
- Raw value
- 27.3 % of land area
- Native score
- 27.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 52nd of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (27.3 − 0) / (100 − 0) = 27.3The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Renewable energy shareTier A
100 = all energy renewable, 0 = none
Ranks 113th of 212 · native score 18.7 · reference year 2022
47percentileHow is this calculated?
- Metric
- Renewable energy share
- Scale
- 100 = all energy renewable, 0 = none
- Raw value
- 18.7 % of final energy
- Native score
- 18.7 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 47th percentile — ranks 113th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (18.7 − 0) / (100 − 0) = 18.7The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Safety & crime
100 = fewest conflict deaths (most at peace), 0 = most
Ranks 1st of 197 · native score 63.71 · reference year 2025
64percentileHow is this calculated?
- Metric
- Deaths in armed conflicts
- Scale
- 100 = fewest conflict deaths (most at peace), 0 = most
- Raw value
- 0 deaths per year
- Native score
- 63.71 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 1st of 197. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 0 among 197 countries ] = 63.71The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- Uppsala Conflict Data Program (via Our World in Data) · Uppsala Conflict Data Program (UCDP)
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Deaths in armed conflicts, best estimate, retrieved via the Our World in Data mirror.
- Homicide rateTier A
100 = safest (fewest homicides), 0 = most homicides
Ranks 96th of 193 · native score 50.52 · reference year 2020
51percentileHow is this calculated?
- Metric
- Homicide rate
- Scale
- 100 = safest (fewest homicides), 0 = most homicides
- Raw value
- 2.58465 per 100,000 population
- Native score
- 50.52 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 51th percentile — ranks 96th of 193. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 2.58 among 193 countries ] = 50.52The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- UNODC (via World Bank) · UN Office on Drugs and Crime / World Bank
- License
- CC BY 4.0
- Reference year
- 2020
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Intentional homicide victims per 100,000, indicator VC.IHR.PSRC.P5, retrieved via the World Bank API. Primary source is UNODC; the World Bank redistributes the series under CC BY 4.0.
- Road-traffic deathsTier B
100 = lowest road-death rate (best), 0 = highest
Ranks 46th of 190 · native score 88.24 · reference year 2013
76percentileHow is this calculated?
- Metric
- Road-traffic deaths
- Scale
- 100 = lowest road-death rate (best), 0 = highest
- Raw value
- 7.6 deaths per 100,000
- Native score
- 88.24 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 46th of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (7.6 − 0) / (64.6 − 0) ] = 88.24Min and max are this dataset's lowest (0) and highest (64.6) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2013
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Health
- Diabetes prevalenceTier A
100 = lowest diabetes prevalence (best), 0 = highest
Ranks 125th of 208 · native score 71.24 · reference year 2024
40percentileHow is this calculated?
- Metric
- Diabetes prevalence
- Scale
- 100 = lowest diabetes prevalence (best), 0 = highest
- Raw value
- 10.1 % of adults 20–79
- Native score
- 71.24 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 40th percentile — ranks 125th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (10.1 − 1.5) / (31.4 − 1.5) ] = 71.24Min and max are this dataset's lowest (1.5) and highest (31.4) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest health spending per capita, 0 = lowest
Ranks 26th of 193 · native score 80.17 · reference year 2023
87percentileHow is this calculated?
- Metric
- Health expenditure per capita
- Scale
- 100 = highest health spending per capita, 0 = lowest
- Raw value
- 3,605.2 current US$ per capita
- Native score
- 80.17 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 87th percentile — ranks 26th of 193. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 3,605.2 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 80.17Log scale (values are heavily skewed). 0 and 100 are the dataset's min (17.44) and max (13,473.19) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Hospital beds per 1,000Tier A
100 = most hospital beds per capita in the dataset, 0 = fewest
Ranks 81st of 191 · native score 11.03 · reference year 2008
58percentileHow is this calculated?
- Metric
- Hospital beds per 1,000
- Scale
- 100 = most hospital beds per capita in the dataset, 0 = fewest
- Raw value
- 2.56 per 1,000 people
- Native score
- 11.03 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 58th percentile — ranks 81st of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (2.56 − 0.15) / (21.99 − 0.15) = 11.03Min and max are this dataset's lowest (0.15) and highest (21.99) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2008
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = full DTP3 coverage, 0 = none
Ranks 20th of 193 · native score 98 · reference year 2024
88percentileHow is this calculated?
- Metric
- Immunization coverage (DTP3)
- Scale
- 100 = full DTP3 coverage, 0 = none
- Raw value
- 98 % of children aged 12–23 months
- Native score
- 98 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 88th percentile — ranks 20th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (98 − 0) / (100 − 0) = 98The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Infant mortality rateTier A
100 = lowest infant mortality in the dataset, 0 = highest
Ranks 18th of 195 · native score 98.3 · reference year 2024
91percentileHow is this calculated?
- Metric
- Infant mortality rate
- Scale
- 100 = lowest infant mortality in the dataset, 0 = highest
- Raw value
- 2.4 per 1,000 live births
- Native score
- 98.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 91th percentile — ranks 18th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (2.4 − 1.2) / (71.9 − 1.2) ] = 98.3Min and max are this dataset's lowest (1.2) and highest (71.9) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Life expectancy at birthTier A
100 = longest life expectancy in the dataset, 0 = shortest
Ranks 8th of 215 · native score 92.75 · reference year 2024
97percentileHow is this calculated?
- Metric
- Life expectancy at birth
- Scale
- 100 = longest life expectancy in the dataset, 0 = shortest
- Raw value
- 84.188 years
- Native score
- 92.75 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 8th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (84.19 − 54.64) / (86.5 − 54.64) = 92.75Min and max are this dataset's lowest (54.64) and highest (86.5) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Maternal mortality ratioTier A
100 = lowest maternal mortality (best), 0 = highest
Ranks 47th of 194 · native score 75.26 · reference year 2023
75percentileHow is this calculated?
- Metric
- Maternal mortality ratio
- Scale
- 100 = lowest maternal mortality (best), 0 = highest
- Raw value
- 11 deaths per 100,000 live births
- Native score
- 75.26 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 75th percentile — ranks 47th of 194. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 11 among 194 countries ] = 75.26The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Physicians per 1,000Tier A
100 = most physicians per capita in the dataset, 0 = fewest
Ranks 10th of 195 · native score 52.93 · reference year 2023
95percentileHow is this calculated?
- Metric
- Physicians per 1,000
- Scale
- 100 = most physicians per capita in the dataset, 0 = fewest
- Raw value
- 5.068 per 1,000 people
- Native score
- 52.93 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 10th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (5.07 − 0.04) / (9.54 − 0.04) = 52.93Min and max are this dataset's lowest (0.04) and highest (9.54) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Safe sanitationTier A
100 = universal safe sanitation, 0 = none
Ranks 1st of 145 · native score 100 · reference year 2024
98percentileHow is this calculated?
- Metric
- Safe sanitation
- Scale
- 100 = universal safe sanitation, 0 = none
- Raw value
- 100 % of population
- Native score
- 100 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 98th percentile — ranks 1st of 145. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (100 − 0) / (100 − 0) = 100The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Safe drinking waterTier A
100 = universal safe drinking water, 0 = none
Ranks 60th of 151 · native score 90.64 · reference year 2024
61percentileHow is this calculated?
- Metric
- Safe drinking water
- Scale
- 100 = universal safe drinking water, 0 = none
- Raw value
- 90.64 % of population
- Native score
- 90.64 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 61th percentile — ranks 60th of 151. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (90.64 − 0) / (100 − 0) = 90.64The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Tobacco useTier A
100 = lowest tobacco use (best), 0 = highest
Ranks 154th of 166 · native score 29.1 · reference year 2024
7percentileHow is this calculated?
- Metric
- Tobacco use
- Scale
- 100 = lowest tobacco use (best), 0 = highest
- Raw value
- 35.5 % of adults
- Native score
- 29.1 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 7th percentile — ranks 154th of 166. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (35.5 − 3.1) / (48.8 − 3.1) ] = 29.1Min and max are this dataset's lowest (3.1) and highest (48.8) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Under-5 mortality rateTier A
100 = lowest under-5 mortality (best), 0 = highest
Ranks 10th of 195 · native score 94.62 · reference year 2024
95percentileHow is this calculated?
- Metric
- Under-5 mortality rate
- Scale
- 100 = lowest under-5 mortality (best), 0 = highest
- Raw value
- 2.5 deaths per 1,000 live births
- Native score
- 94.62 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 10th of 195. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 2.5 among 195 countries ] = 94.62The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Education
100 = highest education spending (% GDP) in the dataset, 0 = lowest
Ranks 184th of 200 · native score 11.58 · reference year 2023
8percentileHow is this calculated?
- Metric
- Government education spending
- Scale
- 100 = highest education spending (% GDP) in the dataset, 0 = lowest
- Raw value
- 1.89868 % of GDP
- Native score
- 11.58 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 8th percentile — ranks 184th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.9 − 0) / (16.39 − 0) = 11.58Min and max are this dataset's lowest (0) and highest (16.39) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = lowest pupil–teacher ratio (best), 0 = highest
Ranks 17th of 197 · native score 95.34 · reference year 2018
92percentileHow is this calculated?
- Metric
- Pupil–teacher ratio (primary)
- Scale
- 100 = lowest pupil–teacher ratio (best), 0 = highest
- Raw value
- 10.4976 pupils per teacher
- Native score
- 95.34 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 92th percentile — ranks 17th of 197. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (10.5 − 6.93) / (83.41 − 6.93) ] = 95.34Min and max are this dataset's lowest (6.93) and highest (83.41) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2018
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest completion in the dataset, 0 = lowest
Ranks 76th of 192 · native score 60.7 · reference year 2024
61percentileHow is this calculated?
- Metric
- Lower-secondary completion rate
- Scale
- 100 = highest completion in the dataset, 0 = lowest
- Raw value
- 93.3768 % of relevant age group
- Native score
- 60.7 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 61th percentile — ranks 76th of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (93.38 − 8.89) / (148.09 − 8.89) = 60.7Min and max are this dataset's lowest (8.89) and highest (148.09) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest tertiary enrollment in the dataset, 0 = lowest
Ranks 57th of 195 · native score 40.32 · reference year 2024
71percentileHow is this calculated?
- Metric
- Tertiary enrollment ratio
- Scale
- 100 = highest tertiary enrollment in the dataset, 0 = lowest
- Raw value
- 67.6768 % gross enrollment
- Native score
- 40.32 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 71th percentile — ranks 57th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (67.68 − 1.84) / (165.11 − 1.84) = 40.32Min and max are this dataset's lowest (1.84) and highest (165.11) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Economy
100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 33rd of 201 · native score 88.91 · reference year 2024
84percentileHow is this calculated?
- Metric
- Foreign direct investment
- Scale
- 100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 6.63543 % of GDP (net inflows)
- Native score
- 88.91 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 84th percentile — ranks 33rd of 201. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (6.64 − -1,303.11) / (170.05 − -1,303.11) = 88.91Min and max are this dataset's lowest (-1,303.11) and highest (170.05) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- GDP growth (projection)Tier B
100 = highest projected growth, 0 = lowest
Ranks 160th of 189 · native score 7.85 · reference year 2031
16percentileHow is this calculated?
- Metric
- GDP growth (projection)
- Scale
- 100 = highest projected growth, 0 = lowest
- Raw value
- 1.7 % per year (avg 2026–2031)
- Native score
- 7.85 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 16th percentile — ranks 160th of 189. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.7 − 0.62) / (14.38 − 0.62) = 7.85Min and max are this dataset's lowest (0.62) and highest (14.38) values, so the score is relative to the current country set.
- Source
- IMF (World Economic Outlook) · International Monetary Fund
- License
- IMF terms (reuse with attribution)
- Reference year
- 2031
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- IMF World Economic Outlook via the IMF DataMapper API (imf.org/external/datamapper).
- GDP per capita (PPP)Tier A
100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
Ranks 21st of 202 · native score 85.06 · reference year 2024
90percentileHow is this calculated?
- Metric
- GDP per capita (PPP)
- Scale
- 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
- Raw value
- 74,939.5 international $ (PPP, current)
- Native score
- 85.06 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 90th percentile — ranks 21st of 202. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 74,939.47 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 85.06Log scale (values are heavily skewed). 0 and 100 are the dataset's min (1,154.89) and max (155,941.29) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 51st of 155 · native score 23.78 · reference year 2024
67percentileHow is this calculated?
- Metric
- Government revenue
- Scale
- 100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 29.7848 % of GDP
- Native score
- 23.78 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 67th percentile — ranks 51st of 155. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (29.78 − 3.03) / (115.55 − 3.03) = 23.78Min and max are this dataset's lowest (3.03) and highest (115.55) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
Ranks 154th of 193 · native score 9.82 · reference year 2025
20percentileHow is this calculated?
- Metric
- Government debt
- Scale
- 100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
- Raw value
- 30.3 % of GDP
- Native score
- 9.82 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 20th percentile — ranks 154th of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (30.3 − 0) / (308.7 − 0) = 9.82Min and max are this dataset's lowest (0) and highest (308.7) values, so the score is relative to the current country set.
- Source
- IMF (World Economic Outlook) · International Monetary Fund
- License
- IMF terms (reuse with attribution)
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- IMF World Economic Outlook via the IMF DataMapper API (imf.org/external/datamapper).
Governance & institutions
- Government effectivenessTier A
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Ranks 34th of 204 · native score 73.18 · reference year 2024
84percentileHow is this calculated?
- Metric
- Government effectiveness
- Scale
- 100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
- Raw value
- 1.15904 index (−2.5 to +2.5)
- Native score
- 73.18 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 84th percentile — ranks 34th of 204. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (1.16 − -2.5) / (2.5 − -2.5) = 73.18The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Women in parliamentTier A
100 = all seats held by women, 0 = none (≈50 = parity)
Ranks 6th of 193 · native score 50 · reference year 2025
97percentileHow is this calculated?
- Metric
- Women in parliament
- Scale
- 100 = all seats held by women, 0 = none (≈50 = parity)
- Raw value
- 50 % of seats
- Native score
- 50 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 6th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (50 − 0) / (100 − 0) = 50The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Quality of life & wellbeing
- Human Development IndexTier A
100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
Ranks 32nd of 193 · native score 91.3 · reference year 2023
83percentileHow is this calculated?
- Metric
- Human Development Index
- Scale
- 100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
- Raw value
- 0.913 HDI (0–1)
- Native score
- 91.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 83th percentile — ranks 32nd of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.91 − 0) / (1 − 0) = 91.3The index is kept on its own published scale.
- Source
- UNDP — Human Development Report · United Nations Development Programme
- License
- CC BY 3.0 IGO
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Human Development Index, retrieved via the Our World in Data mirror (ourworldindata.org/grapher/human-development-index), which republishes the UNDP HDR series. Primary source and methodology owner is UNDP.