Saint Vincent and the Grenadines
VCTCaribbean · Americas · 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?”.
66 metrics for this country
Society & culture
100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
Ranks 77th of 200 · native score 57.11 · reference year 1996
62percentileHow is this calculated?
- Metric
- Adult male height
- Scale
- 100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
- Raw value
- 172.779 cm
- Native score
- 57.11 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 62th percentile — ranks 77th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (172.78 − 159.79) / (182.54 − 159.79) = 57.11Min 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 = highest cocoa supply per person in the dataset, 0 = lowest
Ranks 48th of 191 · native score 13.86 · reference year 2023
75percentileLow 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
- Chocolate supply per person (proxy)
- Scale
- 100 = highest cocoa supply per person in the dataset, 0 = lowest
- Raw value
- 1.94979 kg cocoa per person / year
- Native score
- 13.86 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 75th percentile — ranks 48th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.95 − 0) / (14.07 − 0) = 13.86Min and max are this dataset's lowest (0) and highest (14.07) values, so the score is relative to the current country set.
- Source
- FAO (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier C — Survey / proxy
- Source notes
- Cocoa 'food available for consumption' per capita from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. A supply proxy, not measured consumption — Tier C.
100 = highest female participation in the dataset, 0 = lowest
Ranks 53rd of 186 · native score 69.72 · reference year 2025
72percentileHow is this calculated?
- Metric
- Female labour force participation
- Scale
- 100 = highest female participation in the dataset, 0 = lowest
- Raw value
- 59.217 % of women 15+
- Native score
- 69.72 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 72th percentile — ranks 53rd of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (59.22 − 4.66) / (82.91 − 4.66) = 69.72Min 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 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse
Ranks 75th of 191 · native score 23.57 · reference year 2023
61percentileHow is this calculated?
- Metric
- Fish & seafood supply per capita
- Scale
- 100 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 20.0478 kg per person per year
- Native score
- 23.57 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 61th percentile — ranks 75th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (20.05 − 0.38) / (83.81 − 0.38) = 23.57Min and max are this dataset's lowest (0.38) and highest (83.81) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
Ranks 35th of 191 · native score 23.61 · reference year 2023
82percentileHow is this calculated?
- Metric
- Fruit supply per capita
- Scale
- 100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 128.156 kg per person per year
- Native score
- 23.61 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 82th percentile — ranks 35th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (128.16 − 4.27) / (529.06 − 4.27) = 23.61Min and max are this dataset's lowest (4.27) and highest (529.06) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
Ranks 6th of 191 · native score 74.93 · reference year 2023
97percentileHow is this calculated?
- Metric
- Meat supply per capita
- Scale
- 100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 118.457 kg per person per year
- Native score
- 74.93 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 6th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (118.46 − 3.49) / (156.93 − 3.49) = 74.93Min and max are this dataset's lowest (3.49) and highest (156.93) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = universal social protection coverage, 0 = none
Ranks 112th of 214 · native score 52 · reference year 2019
48percentileHow is this calculated?
- Metric
- Social protection coverage
- Scale
- 100 = universal social protection coverage, 0 = none
- Raw value
- 52 % of population
- Native score
- 52 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 48th percentile — ranks 112th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (52 − 0) / (100 − 0) = 52The index is kept on its own published scale.
- Source
- ILOSTAT (International Labour Organization) · International Labour Organization
- License
- CC BY 4.0
- Reference year
- 2019
- 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 159th of 174 · native score 30.89 · reference year 2019
9percentileHow is this calculated?
- Metric
- International tourist arrivals
- Scale
- 100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
- Raw value
- 84,000 arrivals per year
- Native score
- 30.89 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 9th percentile — ranks 159th of 174. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 84,000 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 30.89Log 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).
100 = highest union density in the dataset, 0 = lowest — descriptive, not better or worse
Ranks 127th of 139 · native score 5.15 · reference year 2010
9percentileHow is this calculated?
- Metric
- Trade union density
- Scale
- 100 = highest union density in the dataset, 0 = lowest — descriptive, not better or worse
- Raw value
- 4.9 % of employees
- Native score
- 5.15 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 9th percentile — ranks 127th of 139. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (4.9 − 0.2) / (91.42 − 0.2) = 5.15Min and max are this dataset's lowest (0.2) and highest (91.42) values, so the score is relative to the current country set.
- Source
- ILOSTAT (International Labour Organization) · International Labour Organization
- License
- CC BY 4.0
- Reference year
- 2010
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- ILOSTAT via the ILO rplumber API (rplumber.ilo.org). CC BY 4.0 for databases published since 3 May 2023.
100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
Ranks 143rd of 191 · native score 11.02 · reference year 2023
25percentileHow is this calculated?
- Metric
- Vegetable supply per capita
- Scale
- 100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 50.2246 kg per person per year
- Native score
- 11.02 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 25th percentile — ranks 143rd of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (50.22 − 5.34) / (412.72 − 5.34) = 11.02Min and max are this dataset's lowest (5.34) and highest (412.72) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
Demographics & migration
100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
Ranks 154th of 215 · native score 35.28 · reference year 2025
29percentileHow is this calculated?
- Metric
- Age dependency ratio
- Scale
- 100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 49.5242 dependents per 100 working-age
- Native score
- 35.28 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 29th percentile — ranks 154th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (49.52 − 20.05) / (103.59 − 20.05) = 35.28Min 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 122nd of 215 · native score 21.65 · reference year 2024
43percentileHow is this calculated?
- Metric
- Fertility rate
- Scale
- 100 = highest fertility, 0 = lowest — descriptive, not better or worse
- Raw value
- 1.761 births per woman
- Native score
- 21.65 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 43th percentile — ranks 122nd of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.76 − 0.58) / (6.03 − 0.58) = 21.65Min 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 74th of 215 · native score 51.54 · reference year 2024
66percentileHow 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
- 5.694 years (female − male)
- Native score
- 51.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 66th percentile — ranks 74th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (5.69 − 0.46) / (10.62 − 0.46) = 51.54Min 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 106th of 237 · native score 43.21 · reference year 2023
55percentileHow is this calculated?
- Metric
- Median age
- Scale
- 100 = oldest median age, 0 = youngest — descriptive, not better or worse
- Raw value
- 33.897 years
- Native score
- 43.21 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 55th percentile — ranks 106th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (33.9 − 14.32) / (59.63 − 14.32) = 43.21Min 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 111th of 214 · native score 4.8 · reference year 2024
48percentileHow is this calculated?
- Metric
- Foreign-born population
- Scale
- 100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
- Raw value
- 4.8 % foreign-born
- Native score
- 4.8 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 48th percentile — ranks 111th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (4.8 − 0) / (100 − 0) = 4.8The 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 196th of 215 · native score 43.9 · reference year 2025
9percentileHow 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
- -7.145 per 1,000 people
- Native score
- 43.9 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 9th percentile — ranks 196th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-7.15 − -46.91) / (43.67 − -46.91) = 43.9Min 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 192nd of 215 · native score 19.7 · reference year 2025
11percentileHow is this calculated?
- Metric
- Total population
- Scale
- 100 = most populous, 0 = least populous — descriptive, not better or worse
- Raw value
- 99,924 people
- Native score
- 19.7 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 11th percentile — ranks 192nd of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 99,924 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 19.7Log 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 49th of 215 · native score 63.29 · reference year 2023
77percentileHow is this calculated?
- Metric
- Population density
- Scale
- 100 = most dense, 0 = least dense — descriptive, not better or worse
- Raw value
- 259.803 people per km²
- Native score
- 63.29 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 77th percentile — ranks 49th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 259.8 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 63.29Log 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 199th of 237 · native score 16.06 · reference year 2050
16percentileHow is this calculated?
- Metric
- Population change (projection)
- Scale
- 100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
- Raw value
- -11.6 % change 2024→2050
- Native score
- 16.06 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 16th percentile — ranks 199th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-11.6 − -32.9) / (99.7 − -32.9) = 16.06Min 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 135th of 211 · native score 36.26 · reference year 2024
36percentileHow is this calculated?
- Metric
- Refugees (by origin)
- Scale
- 100 = most refugees produced, 0 = fewest — descriptive, not better or worse
- Raw value
- 186 refugees
- Native score
- 36.26 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 36th percentile — ranks 135th of 211. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 186 among 211 countries = 36.26The 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 40th of 193 · native score 16.82 · reference year 2024
80percentileHow is this calculated?
- Metric
- Remittances received
- Scale
- 100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 7.94055 % of GDP
- Native score
- 16.82 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 80th percentile — ranks 40th of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (7.94 − 0.01) / (47.15 − 0.01) = 16.82Min 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 62nd of 215 · native score 52.02 · reference year 2025
71percentileHow is this calculated?
- Metric
- Rural population share
- Scale
- 100 = fully rural, 0 = fully urban — descriptive, not better or worse
- Raw value
- 52.019 % rural
- Native score
- 52.02 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 71th percentile — ranks 62nd of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (52.02 − 0) / (100 − 0) = 52.02The 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 181st of 215 · native score 14.47 · reference year 2024
15percentileHow 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
- 1.033 male births per female birth
- Native score
- 14.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 15th percentile — ranks 181st of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.03 − 1.01) / (1.16 − 1.01) = 14.47Min 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 154th of 215 · native score 47.98 · reference year 2025
29percentileHow is this calculated?
- Metric
- Urbanization
- Scale
- 100 = fully urban, 0 = fully rural — descriptive, not better or worse
- Raw value
- 47.981 % urban
- Native score
- 47.98 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 29th percentile — ranks 154th of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (47.98 − 0) / (100 − 0) = 47.98The 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 55th of 182 · native score 2.31 · reference year 2020
70percentileHow is this calculated?
- Metric
- New business density
- Scale
- 100 = highest new-business density in the dataset, 0 = lowest
- Raw value
- 4.6578 new firms per 1,000 aged 15–64
- Native score
- 2.31 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 55th of 182. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (4.66 − 0.02) / (201.01 − 0.02) = 2.31Min 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
- 2020
- 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 109th of 186 · native score 52.47 · reference year 2025
42percentileHow is this calculated?
- Metric
- Employment-to-population ratio
- Scale
- 100 = highest employment ratio in the dataset, 0 = lowest
- Raw value
- 55.676 % of population 15+
- Native score
- 52.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 42th percentile — ranks 109th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (55.68 − 21.21) / (86.9 − 21.21) = 52.47Min 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 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 14th of 201 · native score 89.27 · reference year 2024
93percentileHow is this calculated?
- Metric
- Foreign direct investment
- Scale
- 100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 12.006 % of GDP (net inflows)
- Native score
- 89.27 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 93th percentile — ranks 14th of 201. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (12.01 − -1,303.11) / (170.05 − -1,303.11) = 89.27Min 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 107th of 189 · native score 15.48 · reference year 2031
44percentileHow is this calculated?
- Metric
- GDP growth (projection)
- Scale
- 100 = highest projected growth, 0 = lowest
- Raw value
- 2.75 % per year (avg 2026–2031)
- Native score
- 15.48 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 44th percentile — ranks 107th of 189. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (2.75 − 0.62) / (14.38 − 0.62) = 15.48Min 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 98th of 202 · native score 59.39 · reference year 2024
52percentileHow is this calculated?
- Metric
- GDP per capita (PPP)
- Scale
- 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
- Raw value
- 21,272.1 international $ (PPP, current)
- Native score
- 59.39 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 52th percentile — ranks 98th of 202. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 21,272.08 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 59.39Log 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 76th of 155 · native score 20.03 · reference year 2017
51percentileHow is this calculated?
- Metric
- Government revenue
- Scale
- 100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 25.5657 % of GDP
- Native score
- 20.03 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 51th percentile — ranks 76th of 155. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (25.57 − 3.03) / (115.55 − 3.03) = 20.03Min 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
- 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.
100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
Ranks 158th of 192 · native score 17.97 · reference year 2025
18percentileHow is this calculated?
- Metric
- Inflation rate
- Scale
- 100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
- Raw value
- 0.815323 % annual change (CPI)
- Native score
- 17.97 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 18th percentile — ranks 158th of 192. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 0.82 among 192 countries = 17.97The score is the country's position in the distribution.
- 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.
- Labour productivityTier A
100 = highest output per worker, 0 = lowest
Ranks 93rd of 177 · native score 61.08 · reference year 2024
48percentileHow is this calculated?
- Metric
- Labour productivity
- Scale
- 100 = highest output per worker, 0 = lowest
- Raw value
- 42,666.3 constant PPP$ per worker
- Native score
- 61.08 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 48th percentile — ranks 93rd of 177. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 42,666.27 − ln 2,444.23) / (ln 263,863.91 − ln 2,444.23) = 61.08Log 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
- 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 15th of 193 · native score 36.73 · reference year 2025
92percentileHow is this calculated?
- Metric
- Government debt
- Scale
- 100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
- Raw value
- 113.4 % of GDP
- Native score
- 36.73 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 92th percentile — ranks 15th of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (113.4 − 0) / (308.7 − 0) = 36.73Min 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).
- Unemployment rateTier A
100 = lowest unemployment in the dataset, 0 = highest
Ranks 176th of 186 · native score 47.54 · reference year 2025
6percentileHow is this calculated?
- Metric
- Unemployment rate
- Scale
- 100 = lowest unemployment in the dataset, 0 = highest
- Raw value
- 18.003 % of labour force
- Native score
- 47.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 6th percentile — ranks 176th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (18 − 0.13) / (34.2 − 0.13) ] = 47.54Min 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 181st of 186 · native score 45.63 · reference year 2025
3percentileHow is this calculated?
- Metric
- Youth unemployment rate
- Scale
- 100 = lowest youth unemployment (best), 0 = highest
- Raw value
- 41.947 % of labour force 15–24
- Native score
- 45.63 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 3th percentile — ranks 181st of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (41.95 − 0.46) / (76.77 − 0.46) ] = 45.63Min 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.
Environment & infrastructure
- Climate vulnerabilityTier B
100 = least climate-vulnerable (best), 0 = most vulnerable
Ranks 71st of 190 · native score 60.63 · reference year 2024
63percentileHow is this calculated?
- Metric
- Climate vulnerability
- Scale
- 100 = least climate-vulnerable (best), 0 = most vulnerable
- Raw value
- 0.417672 index (0–1, higher = more vulnerable)
- Native score
- 60.63 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 63th percentile — ranks 71st of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (0.42 − 0.26) / (0.66 − 0.26) ] = 60.63Min 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 94th of 214 · native score 56.31 · reference year 2024
56percentileHow is this calculated?
- Metric
- CO₂ emissions per capita
- Scale
- 100 = lowest emissions per capita (best), 0 = highest
- Raw value
- 2.54056 tonnes CO₂ per capita
- Native score
- 56.31 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 56th percentile — ranks 94th of 214. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 2.54 among 214 countries ] = 56.31The 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 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
Ranks 121st of 177 · native score 56.11 · reference year 2007
32percentileHow is this calculated?
- Metric
- Energy use per capita
- Scale
- 100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
- Raw value
- 627.628 kg oil-equivalent per capita
- Native score
- 56.11 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 32th percentile — ranks 121st of 177. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 627.63 − ln 9.73) / (ln 16,343.04 − ln 9.73) = 56.11Log scale (values are heavily skewed). 0 and 100 are the dataset's min (9.73) and max (16,343.04) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2007
- 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 63rd of 208 · native score 48.32 · reference year 2024
70percentileHow is this calculated?
- Metric
- Fixed broadband subscriptions
- Scale
- 100 = most fixed-broadband subscriptions per capita, 0 = fewest
- Raw value
- 29.4605 per 100 people
- Native score
- 48.32 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 63rd of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (29.46 − 0) / (60.97 − 0) = 48.32Min 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 13th of 213 · native score 73.18 · reference year 2023
94percentileHow is this calculated?
- Metric
- Forest area
- Scale
- 100 = most forested, 0 = least — descriptive, not better or worse
- Raw value
- 73.1795 % of land area
- Native score
- 73.18 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 94th percentile — ranks 13th of 213. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (73.18 − 0) / (100 − 0) = 73.18The 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 120th of 209 · native score 76.19 · reference year 2024
43percentileHow is this calculated?
- Metric
- Internet users
- Scale
- 100 = whole population online, 0 = none
- Raw value
- 76.1901 % of population
- Native score
- 76.19 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 43th percentile — ranks 120th of 209. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (76.19 − 0) / (100 − 0) = 76.19The 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 49th of 200 · native score 75.75 · reference year 2023
76percentileHow is this calculated?
- Metric
- PM2.5 air pollution
- Scale
- 100 = cleanest air (lowest PM2.5), 0 = most polluted
- Raw value
- 10.603 µg/m³
- Native score
- 75.75 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 49th of 200. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 10.6 among 200 countries ] = 75.75The 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 70th of 212 · native score 22.6 · reference year 2025
67percentileHow is this calculated?
- Metric
- Protected land area
- Scale
- 100 = most land protected, 0 = least
- Raw value
- 22.6 % of land area
- Native score
- 22.6 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 67th percentile — ranks 70th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (22.6 − 0) / (100 − 0) = 22.6The 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 168th of 212 · native score 5.1 · reference year 2022
21percentileHow is this calculated?
- Metric
- Renewable energy share
- Scale
- 100 = all energy renewable, 0 = none
- Raw value
- 5.1 % of final energy
- Native score
- 5.1 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 21th percentile — ranks 168th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (5.1 − 0) / (100 − 0) = 5.1The 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 191st of 193 · native score 1.3 · reference year 2023
1percentileHow is this calculated?
- Metric
- Homicide rate
- Scale
- 100 = safest (fewest homicides), 0 = most homicides
- Raw value
- 51.3213 per 100,000 population
- Native score
- 1.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 1th percentile — ranks 191st of 193. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 51.32 among 193 countries ] = 1.3The 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
- 2023
- 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 43rd of 190 · native score 88.54 · reference year 2019
78percentileHow is this calculated?
- Metric
- Road-traffic deaths
- Scale
- 100 = lowest road-death rate (best), 0 = highest
- Raw value
- 7.4 deaths per 100,000
- Native score
- 88.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 78th percentile — ranks 43rd of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (7.4 − 0) / (64.6 − 0) ] = 88.54Min 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
- 2019
- 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.
Governance & institutions
100 = cleanest (least corrupt), 0 = most corrupt
Ranks 32nd of 180 · native score 63 · reference year 2024
82percentileHow is this calculated?
- Metric
- Corruption Perceptions Index
- Scale
- 100 = cleanest (least corrupt), 0 = most corrupt
- Raw value
- 63 CPI score (0–100)
- Native score
- 63 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 82th percentile — ranks 32nd of 180. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (63 − 0) / (100 − 0) = 63The index is kept on its own published scale.
- Source
- Transparency International · Transparency International
- License
- CC BY-ND 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- CPI retrieved via the Our World in Data mirror (ourworldindata.org/grapher/ti-corruption-perception-index), which republishes the official TI CPI series verbatim. Snapshot verified against Transparency International's official CPI 2024 figures and matches exactly (spot-checked: DNK 90, FIN 88, SGP 84, DEU 75, USA 65, ESP 56, SSD 8). We were unable to fetch TI's primary file directly (their CDN returns an access-denied stub for the CPI xlsx and no clean CSV is offered), so the OWID mirror is the machine-readable source; primary source and methodology owner is Transparency International.
- Government effectivenessTier A
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Ranks 79th of 204 · native score 55.36 · reference year 2024
61percentileHow is this calculated?
- Metric
- Government effectiveness
- Scale
- 100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
- Raw value
- 0.26823 index (−2.5 to +2.5)
- Native score
- 55.36 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 61th percentile — ranks 79th of 204. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.27 − -2.5) / (2.5 − -2.5) = 55.36The 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 160th of 193 · native score 13.33 · reference year 2025
17percentileHow is this calculated?
- Metric
- Women in parliament
- Scale
- 100 = all seats held by women, 0 = none (≈50 = parity)
- Raw value
- 13.3333 % of seats
- Native score
- 13.33 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 17th percentile — ranks 160th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (13.33 − 0) / (100 − 0) = 13.33The 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.
Health
- Diabetes prevalenceTier A
100 = lowest diabetes prevalence (best), 0 = highest
Ranks 107th of 208 · native score 76.25 · reference year 2024
48percentileHow is this calculated?
- Metric
- Diabetes prevalence
- Scale
- 100 = lowest diabetes prevalence (best), 0 = highest
- Raw value
- 8.6 % of adults 20–79
- Native score
- 76.25 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 48th percentile — ranks 107th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (8.6 − 1.5) / (31.4 − 1.5) ] = 76.25Min 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 98th of 193 · native score 49.51 · reference year 2023
49percentileHow is this calculated?
- Metric
- Health expenditure per capita
- Scale
- 100 = highest health spending per capita, 0 = lowest
- Raw value
- 469.207 current US$ per capita
- Native score
- 49.51 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 49th percentile — ranks 98th of 193. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 469.21 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 49.51Log 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 62nd of 191 · native score 14.01 · reference year 2022
68percentileHow is this calculated?
- Metric
- Hospital beds per 1,000
- Scale
- 100 = most hospital beds per capita in the dataset, 0 = fewest
- Raw value
- 3.21 per 1,000 people
- Native score
- 14.01 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 68th percentile — ranks 62nd of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.21 − 0.15) / (21.99 − 0.15) = 14.01Min 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
- 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 = full DTP3 coverage, 0 = none
Ranks 1st of 193 · native score 99 · reference year 2024
95percentileHow is this calculated?
- Metric
- Immunization coverage (DTP3)
- Scale
- 100 = full DTP3 coverage, 0 = none
- Raw value
- 99 % of children aged 12–23 months
- Native score
- 99 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 1st of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (99 − 0) / (100 − 0) = 99The 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 82nd of 195 · native score 87.27 · reference year 2024
58percentileHow is this calculated?
- Metric
- Infant mortality rate
- Scale
- 100 = lowest infant mortality in the dataset, 0 = highest
- Raw value
- 10.2 per 1,000 live births
- Native score
- 87.27 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 58th percentile — ranks 82nd of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (10.2 − 1.2) / (71.9 − 1.2) ] = 87.27Min 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 141st of 215 · native score 52.56 · reference year 2024
35percentileHow is this calculated?
- Metric
- Life expectancy at birth
- Scale
- 100 = longest life expectancy in the dataset, 0 = shortest
- Raw value
- 71.382 years
- Native score
- 52.56 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 35th percentile — ranks 141st of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (71.38 − 54.64) / (86.5 − 54.64) = 52.56Min 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 104th of 194 · native score 46.65 · reference year 2023
47percentileHow is this calculated?
- Metric
- Maternal mortality ratio
- Scale
- 100 = lowest maternal mortality (best), 0 = highest
- Raw value
- 56 deaths per 100,000 live births
- Native score
- 46.65 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 47th percentile — ranks 104th of 194. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 56 among 194 countries ] = 46.65The 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 122nd of 195 · native score 9.47 · reference year 2012
38percentileHow is this calculated?
- Metric
- Physicians per 1,000
- Scale
- 100 = most physicians per capita in the dataset, 0 = fewest
- Raw value
- 0.938 per 1,000 people
- Native score
- 9.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 38th percentile — ranks 122nd of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.94 − 0.04) / (9.54 − 0.04) = 9.47Min 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
- 2012
- 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 81st of 195 · native score 58.46 · reference year 2024
58percentileHow is this calculated?
- Metric
- Under-5 mortality rate
- Scale
- 100 = lowest under-5 mortality (best), 0 = highest
- Raw value
- 11.3 deaths per 1,000 live births
- Native score
- 58.46 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 58th percentile — ranks 81st of 195. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 11.3 among 195 countries ] = 58.46The 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.
- UndernourishmentTier A
100 = lowest undernourishment (best), 0 = highest
Ranks 92nd of 169 · native score 93.04 · reference year 2023
46percentileHow is this calculated?
- Metric
- Undernourishment
- Scale
- 100 = lowest undernourishment (best), 0 = highest
- Raw value
- 6.1 % of population
- Native score
- 93.04 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 46th percentile — ranks 92nd of 169. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (6.1 − 2.5) / (54.2 − 2.5) ] = 93.04Min and max are this dataset's lowest (2.5) and highest (54.2) 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
- 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.
Education
100 = highest education spending (% GDP) in the dataset, 0 = lowest
Ranks 21st of 200 · native score 39.4 · reference year 2023
90percentileHow is this calculated?
- Metric
- Government education spending
- Scale
- 100 = highest education spending (% GDP) in the dataset, 0 = lowest
- Raw value
- 6.45827 % of GDP
- Native score
- 39.4 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 90th percentile — ranks 21st of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (6.46 − 0) / (16.39 − 0) = 39.4Min 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 58th of 197 · native score 90.24 · reference year 2018
71percentileHow is this calculated?
- Metric
- Pupil–teacher ratio (primary)
- Scale
- 100 = lowest pupil–teacher ratio (best), 0 = highest
- Raw value
- 14.3926 pupils per teacher
- Native score
- 90.24 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 71th percentile — ranks 58th of 197. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (14.39 − 6.93) / (83.41 − 6.93) ] = 90.24Min 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 7th of 192 · native score 72.55 · reference year 2024
97percentileHow is this calculated?
- Metric
- Lower-secondary completion rate
- Scale
- 100 = highest completion in the dataset, 0 = lowest
- Raw value
- 109.88 % of relevant age group
- Native score
- 72.55 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 7th of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (109.88 − 8.89) / (148.09 − 8.89) = 72.55Min 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 100th of 195 · native score 24.29 · reference year 2022
49percentileHow is this calculated?
- Metric
- Tertiary enrollment ratio
- Scale
- 100 = highest tertiary enrollment in the dataset, 0 = lowest
- Raw value
- 41.4983 % gross enrollment
- Native score
- 24.29 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 49th percentile — ranks 100th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (41.5 − 1.84) / (165.11 − 1.84) = 24.29Min 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
- 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.
Quality of life & wellbeing
- Human Development IndexTier A
100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
Ranks 76th of 193 · native score 79.8 · reference year 2023
61percentileHow is this calculated?
- Metric
- Human Development Index
- Scale
- 100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
- Raw value
- 0.798 HDI (0–1)
- Native score
- 79.8 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 61th percentile — ranks 76th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.8 − 0) / (1 − 0) = 79.8The 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.