United States Virgin Islands
VIRCaribbean · Americas
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?”.
34 metrics for this country
Demographics & migration
100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
Ranks 55th of 215 · native score 54.42 · reference year 2025
75percentileHow is this calculated?
- Metric
- Age dependency ratio
- Scale
- 100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 65.5137 dependents per 100 working-age
- Native score
- 54.42 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 75th percentile — ranks 55th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (65.51 − 20.05) / (103.59 − 20.05) = 54.42Min 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 102nd of 215 · native score 25.49 · reference year 2024
53percentileHow is this calculated?
- Metric
- Fertility rate
- Scale
- 100 = highest fertility, 0 = lowest — descriptive, not better or worse
- Raw value
- 1.97 births per woman
- Native score
- 25.49 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 53th percentile — ranks 102nd of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.97 − 0.58) / (6.03 − 0.58) = 25.49Min 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 42nd of 215 · native score 59.47 · reference year 2024
80percentileHow 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
- 6.5 years (female − male)
- Native score
- 59.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 80th percentile — ranks 42nd of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (6.5 − 0.46) / (10.62 − 0.46) = 59.47Min 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 20th of 237 · native score 66.98 · reference year 2023
92percentileHow is this calculated?
- Metric
- Median age
- Scale
- 100 = oldest median age, 0 = youngest — descriptive, not better or worse
- Raw value
- 44.667 years
- Native score
- 66.98 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 92th percentile — ranks 20th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (44.67 − 14.32) / (59.63 − 14.32) = 66.98Min 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 8th of 214 · native score 66.9 · reference year 2024
97percentileHow is this calculated?
- Metric
- Foreign-born population
- Scale
- 100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
- Raw value
- 66.9 % foreign-born
- Native score
- 66.9 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 8th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (66.9 − 0) / (100 − 0) = 66.9The 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 179th of 215 · native score 47.99 · reference year 2025
17percentileHow 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
- -3.44 per 1,000 people
- Native score
- 47.99 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 17th percentile — ranks 179th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-3.44 − -46.91) / (43.67 − -46.91) = 47.99Min 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 190th of 215 · native score 20.02 · reference year 2025
12percentileHow is this calculated?
- Metric
- Total population
- Scale
- 100 = most populous, 0 = least populous — descriptive, not better or worse
- Raw value
- 103,792 people
- Native score
- 20.02 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 12th percentile — ranks 190th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 103,792 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 20.02Log 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 41st of 215 · native score 64.49 · reference year 2023
81percentileHow is this calculated?
- Metric
- Population density
- Scale
- 100 = most dense, 0 = least dense — descriptive, not better or worse
- Raw value
- 299.763 people per km²
- Native score
- 64.49 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 81th percentile — ranks 41st of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 299.76 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 64.49Log 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 215th of 237 · native score 12.67 · reference year 2050
9percentileHow is this calculated?
- Metric
- Population change (projection)
- Scale
- 100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
- Raw value
- -16.1 % change 2024→2050
- Native score
- 12.67 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 9th percentile — ranks 215th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-16.1 − -32.9) / (99.7 − -32.9) = 12.67Min 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 = fully rural, 0 = fully urban — descriptive, not better or worse
Ranks 198th of 215 · native score 4.61 · reference year 2025
8percentileHow is this calculated?
- Metric
- Rural population share
- Scale
- 100 = fully rural, 0 = fully urban — descriptive, not better or worse
- Raw value
- 4.61142 % rural
- Native score
- 4.61 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 8th percentile — ranks 198th of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (4.61 − 0) / (100 − 0) = 4.61The 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 159th of 215 · native score 18.42 · reference year 2024
25percentileHow 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
- 1.039 male births per female birth
- Native score
- 18.42 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 25th percentile — ranks 159th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.04 − 1.01) / (1.16 − 1.01) = 18.42Min 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 18th of 215 · native score 95.39 · reference year 2025
92percentileHow is this calculated?
- Metric
- Urbanization
- Scale
- 100 = fully urban, 0 = fully rural — descriptive, not better or worse
- Raw value
- 95.3886 % urban
- Native score
- 95.39 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 92th percentile — ranks 18th of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (95.39 − 0) / (100 − 0) = 95.39The 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.
Economy
- New business densityTier A
100 = highest new-business density in the dataset, 0 = lowest
Ranks 7th of 182 · native score 9.92 · reference year 2024
96percentileHow is this calculated?
- Metric
- New business density
- Scale
- 100 = highest new-business density in the dataset, 0 = lowest
- Raw value
- 19.9606 new firms per 1,000 aged 15–64
- Native score
- 9.92 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 96th percentile — ranks 7th of 182. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (19.96 − 0.02) / (201.01 − 0.02) = 9.92Min and max are this dataset's lowest (0.02) and highest (201.01) 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 employment ratio in the dataset, 0 = lowest
Ranks 151st of 186 · native score 40.99 · reference year 2025
19percentileHow is this calculated?
- Metric
- Employment-to-population ratio
- Scale
- 100 = highest employment ratio in the dataset, 0 = lowest
- Raw value
- 48.136 % of population 15+
- Native score
- 40.99 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 19th percentile — ranks 151st of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (48.14 − 21.21) / (86.9 − 21.21) = 40.99Min and max are this dataset's lowest (21.21) and highest (86.9) 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 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 11th of 192 · native score 48.46 · reference year 2022
95percentileHow is this calculated?
- Metric
- Exports of goods & services
- Scale
- 100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 97.3673 % of GDP
- Native score
- 48.46 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 11th of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (97.37 − 1.1) / (199.76 − 1.1) = 48.46Min and max are this dataset's lowest (1.1) and highest (199.76) values, so the score is relative to the current country set.
- 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.
- GDP per capita (PPP)Tier A
100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
Ranks 51st of 202 · native score 76.73 · reference year 2022
75percentileHow is this calculated?
- Metric
- GDP per capita (PPP)
- Scale
- 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
- Raw value
- 49,793 international $ (PPP, current)
- Native score
- 76.73 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 75th percentile — ranks 51st of 202. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 49,793.03 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 76.73Log 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
- 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.
- Labour productivityTier A
100 = highest output per worker, 0 = lowest
Ranks 23rd of 177 · native score 82.47 · reference year 2022
87percentileHow is this calculated?
- Metric
- Labour productivity
- Scale
- 100 = highest output per worker, 0 = lowest
- Raw value
- 116,146 constant PPP$ per worker
- Native score
- 82.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 87th percentile — ranks 23rd of 177. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 116,146.46 − ln 2,444.23) / (ln 263,863.91 − ln 2,444.23) = 82.47Log scale (values are heavily skewed). 0 and 100 are the dataset's min (2,444.23) and max (263,863.91) — relative, not absolute or year-over-year comparable.
- 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.
- Unemployment rateTier A
100 = lowest unemployment in the dataset, 0 = highest
Ranks 157th of 186 · native score 66.8 · reference year 2025
16percentileHow is this calculated?
- Metric
- Unemployment rate
- Scale
- 100 = lowest unemployment in the dataset, 0 = highest
- Raw value
- 11.443 % of labour force
- Native score
- 66.8 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 16th percentile — ranks 157th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (11.44 − 0.13) / (34.2 − 0.13) ] = 66.8Min and max are this dataset's lowest (0.13) and highest (34.2) 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
- 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.
- Youth unemployment rateTier A
100 = lowest youth unemployment (best), 0 = highest
Ranks 151st of 186 · native score 68.89 · reference year 2025
19percentileHow is this calculated?
- Metric
- Youth unemployment rate
- Scale
- 100 = lowest youth unemployment (best), 0 = highest
- Raw value
- 24.196 % of labour force 15–24
- Native score
- 68.89 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 19th percentile — ranks 151st of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (24.2 − 0.46) / (76.77 − 0.46) ] = 68.89Min and max are this dataset's lowest (0.46) and highest (76.77) 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
- 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.
Health
- Diabetes prevalenceTier A
100 = lowest diabetes prevalence (best), 0 = highest
Ranks 112th of 208 · native score 74.58 · reference year 2024
46percentileHow is this calculated?
- Metric
- Diabetes prevalence
- Scale
- 100 = lowest diabetes prevalence (best), 0 = highest
- Raw value
- 9.1 % of adults 20–79
- Native score
- 74.58 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 46th percentile — ranks 112th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (9.1 − 1.5) / (31.4 − 1.5) ] = 74.58Min 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.
- Life expectancy at birthTier A
100 = longest life expectancy in the dataset, 0 = shortest
Ranks 48th of 215 · native score 82.03 · reference year 2024
78percentileHow is this calculated?
- Metric
- Life expectancy at birth
- Scale
- 100 = longest life expectancy in the dataset, 0 = shortest
- Raw value
- 80.7707 years
- Native score
- 82.03 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 78th percentile — ranks 48th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (80.77 − 54.64) / (86.5 − 54.64) = 82.03Min 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.
- Safe drinking waterTier A
100 = universal safe drinking water, 0 = none
Ranks 35th of 151 · native score 98.68 · reference year 2024
77percentileHow is this calculated?
- Metric
- Safe drinking water
- Scale
- 100 = universal safe drinking water, 0 = none
- Raw value
- 98.6775 % of population
- Native score
- 98.68 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 77th percentile — ranks 35th of 151. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (98.68 − 0) / (100 − 0) = 98.68The 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.
Environment & infrastructure
- 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 118th of 208 · native score 16.51 · reference year 2022
43percentileHow is this calculated?
- Metric
- Fixed broadband subscriptions
- Scale
- 100 = most fixed-broadband subscriptions per capita, 0 = fewest
- Raw value
- 10.0662 per 100 people
- Native score
- 16.51 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 43th percentile — ranks 118th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (10.07 − 0) / (60.97 − 0) = 16.51Min 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
- 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.
100 = most forested, 0 = least — descriptive, not better or worse
Ranks 30th of 213 · native score 58.17 · reference year 2023
86percentileHow is this calculated?
- Metric
- Forest area
- Scale
- 100 = most forested, 0 = least — descriptive, not better or worse
- Raw value
- 58.1714 % of land area
- Native score
- 58.17 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 86th percentile — ranks 30th of 213. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (58.17 − 0) / (100 − 0) = 58.17The 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 146th of 209 · native score 64.38 · reference year 2017
30percentileHow is this calculated?
- Metric
- Internet users
- Scale
- 100 = whole population online, 0 = none
- Raw value
- 64.3775 % of population
- Native score
- 64.38 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 30th percentile — ranks 146th of 209. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (64.38 − 0) / (100 − 0) = 64.38The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2017
- 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 23rd of 200 · native score 88.75 · reference year 2023
89percentileHow is this calculated?
- Metric
- PM2.5 air pollution
- Scale
- 100 = cleanest air (lowest PM2.5), 0 = most polluted
- Raw value
- 6.79264 µg/m³
- Native score
- 88.75 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 89th percentile — ranks 23rd of 200. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 6.79 among 200 countries ] = 88.75The 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 136th of 212 · native score 13.3 · reference year 2025
36percentileHow is this calculated?
- Metric
- Protected land area
- Scale
- 100 = most land protected, 0 = least
- Raw value
- 13.3 % of land area
- Native score
- 13.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 36th percentile — ranks 136th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (13.3 − 0) / (100 − 0) = 13.3The 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 165th of 212 · native score 5.9 · reference year 2022
22percentileHow is this calculated?
- Metric
- Renewable energy share
- Scale
- 100 = all energy renewable, 0 = none
- Raw value
- 5.9 % of final energy
- Native score
- 5.9 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 22th percentile — ranks 165th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (5.9 − 0) / (100 − 0) = 5.9The 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.
Society & culture
100 = highest female participation in the dataset, 0 = lowest
Ranks 98th of 186 · native score 61.48 · reference year 2025
48percentileHow is this calculated?
- Metric
- Female labour force participation
- Scale
- 100 = highest female participation in the dataset, 0 = lowest
- Raw value
- 52.768 % of women 15+
- Native score
- 61.48 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 48th percentile — ranks 98th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (52.77 − 4.66) / (82.91 − 4.66) = 61.48Min and max are this dataset's lowest (4.66) and highest (82.91) 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 = universal social protection coverage, 0 = none
Ranks 79th of 214 · native score 66.7 · reference year 2022
63percentileHow is this calculated?
- Metric
- Social protection coverage
- Scale
- 100 = universal social protection coverage, 0 = none
- Raw value
- 66.7 % of population
- Native score
- 66.7 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 63th percentile — ranks 79th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (66.7 − 0) / (100 − 0) = 66.7The 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.
100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
Ranks 115th of 174 · native score 48.81 · reference year 2019
34percentileHow is this calculated?
- Metric
- International tourist arrivals
- Scale
- 100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
- Raw value
- 514,000 arrivals per year
- Native score
- 48.81 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 34th percentile — ranks 115th of 174. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 514,000 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 48.81Log 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).
Governance & institutions
- Government effectivenessTier A
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Ranks 73rd of 204 · native score 57.5 · reference year 2024
64percentileHow is this calculated?
- Metric
- Government effectiveness
- Scale
- 100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
- Raw value
- 0.374791 index (−2.5 to +2.5)
- Native score
- 57.5 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 73rd of 204. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.37 − -2.5) / (2.5 − -2.5) = 57.5The 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.
Safety & crime
- Homicide rateTier A
100 = safest (fewest homicides), 0 = most homicides
Ranks 190th of 193 · native score 1.81 · reference year 2012
2percentileHow is this calculated?
- Metric
- Homicide rate
- Scale
- 100 = safest (fewest homicides), 0 = most homicides
- Raw value
- 49.8571 per 100,000 population
- Native score
- 1.81 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 2th percentile — ranks 190th of 193. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 49.86 among 193 countries ] = 1.81The 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
- 2012
- 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.