Marshall Islands

MHL

Micronesia · Oceania · 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?”.

63 metrics for this country

Education

Adult literacy rateTier A
100 = highest adult literacy in the dataset, 0 = lowest
Ranks 65th of 155 · native score 94.21 · reference year 2021
58percentile
How is this calculated?
Metric
Adult literacy rate
Scale
100 = highest adult literacy in the dataset, 0 = lowest
Raw value
95.7629 % of adults
Native score
94.21 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
58th percentile — ranks 65th of 155. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (95.76 − 26.83) / (100 − 26.83) = 94.21
Min and max are this dataset's lowest (26.83) and highest (100) values, so the score is relative to the current country set.
Source
World Bank · World Bank
License
CC BY 4.0
Reference year
2021
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.
Government education spendingTier A
100 = highest education spending (% GDP) in the dataset, 0 = lowest
Ranks 10th of 200 · native score 46.98 · reference year 2022
95percentile
How is this calculated?
Metric
Government education spending
Scale
100 = highest education spending (% GDP) in the dataset, 0 = lowest
Raw value
7.70088 % of GDP
Native score
46.98 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
95th percentile — ranks 10th of 200. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (7.7 − 0) / (16.39 − 0) = 46.98
Min 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
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.
Pupil–teacher ratio (primary)Tier A
100 = lowest pupil–teacher ratio (best), 0 = highest
Ranks 82nd of 197 · native score 86.92 · reference year 2002
59percentile
How is this calculated?
Metric
Pupil–teacher ratio (primary)
Scale
100 = lowest pupil–teacher ratio (best), 0 = highest
Raw value
16.9381 pupils per teacher
Native score
86.92 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
59th percentile — ranks 82nd of 197. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 − [ 100 · (16.94 − 6.93) / (83.41 − 6.93) ] = 86.92
Min 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
2002
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.
Lower-secondary completion rateTier A
100 = highest completion in the dataset, 0 = lowest
Ranks 5th of 192 · native score 75.55 · reference year 2024
98percentile
How is this calculated?
Metric
Lower-secondary completion rate
Scale
100 = highest completion in the dataset, 0 = lowest
Raw value
114.055 % of relevant age group
Native score
75.55 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
98th percentile — ranks 5th of 192. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (114.05 − 8.89) / (148.09 − 8.89) = 75.55
Min 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.
Tertiary enrollment ratioTier A
100 = highest tertiary enrollment in the dataset, 0 = lowest
Ranks 105th of 195 · native score 21.95 · reference year 2024
46percentile
How is this calculated?
Metric
Tertiary enrollment ratio
Scale
100 = highest tertiary enrollment in the dataset, 0 = lowest
Raw value
37.6853 % gross enrollment
Native score
21.95 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
46th percentile — ranks 105th of 195. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (37.69 − 1.84) / (165.11 − 1.84) = 21.95
Min and max are this dataset's lowest (1.84) and highest (165.11) values, so the score is relative to the current country set.
Source
World Bank · World Bank
License
CC BY 4.0
Reference year
2024
Retrieved
2026-07-12
Confidence
Tier A — Official / robust
Source notes
World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.

Society & culture

Adult male heightTier ADescriptive
100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
Ranks 193rd of 200 · native score 13.27 · reference year 1996
4percentile
How is this calculated?
Metric
Adult male height
Scale
100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
Raw value
162.809 cm
Native score
13.27 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
4th percentile — ranks 193rd of 200. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (162.81 − 159.79) / (182.54 − 159.79) = 13.27
Min 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.
Chocolate supply per person (proxy)Tier C
100 = highest cocoa supply per person in the dataset, 0 = lowest
Ranks 118th of 191 · native score 3.41 · reference year 2023
38percentile
Low 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
0.479765 kg cocoa per person / year
Native score
3.41 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
38th percentile — ranks 118th of 191. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (0.48 − 0) / (14.07 − 0) = 3.41
Min 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.
Fish & seafood supply per capitaTier ADescriptive
100 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse
Ranks 17th of 191 · native score 52.94 · reference year 2023
91percentile
How 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
44.5482 kg per person per year
Native score
52.94 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
91th percentile — ranks 17th of 191. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (44.55 − 0.38) / (83.81 − 0.38) = 52.94
Min 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.
Fruit supply per capitaTier ADescriptive
100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
Ranks 176th of 191 · native score 4.03 · reference year 2023
8percentile
How is this calculated?
Metric
Fruit supply per capita
Scale
100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
Raw value
25.4076 kg per person per year
Native score
4.03 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
8th percentile — ranks 176th of 191. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (25.41 − 4.27) / (529.06 − 4.27) = 4.03
Min 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.
Informal employmentTier A
100 = lowest informal employment (best), 0 = highest
Ranks 46th of 145 · native score 67.68 · reference year 2021
69percentile
How is this calculated?
Metric
Informal employment
Scale
100 = lowest informal employment (best), 0 = highest
Raw value
32.575 % of employment
Native score
67.68 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
69th percentile — ranks 46th of 145. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 − [ 100 · (32.58 − 1.09) / (98.49 − 1.09) ] = 67.68
Min and max are this dataset's lowest (1.09) and highest (98.49) 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
ILOSTAT (International Labour Organization) · International Labour Organization
License
CC BY 4.0
Reference year
2021
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.
Meat supply per capitaTier ADescriptive
100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
Ranks 3rd of 191 · native score 79.59 · reference year 2023
99percentile
How is this calculated?
Metric
Meat supply per capita
Scale
100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
Raw value
125.619 kg per person per year
Native score
79.59 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
99th percentile — ranks 3rd of 191. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (125.62 − 3.49) / (156.93 − 3.49) = 79.59
Min 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.
Social protection coverageTier A
100 = universal social protection coverage, 0 = none
Ranks 148th of 214 · native score 25.2 · reference year 2019
31percentile
How is this calculated?
Metric
Social protection coverage
Scale
100 = universal social protection coverage, 0 = none
Raw value
25.2 % of population
Native score
25.2 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
31th percentile — ranks 148th of 214. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (25.2 − 0) / (100 − 0) = 25.2
The 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.
International tourist arrivalsTier BDescriptive
100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
Ranks 173rd of 174 · native score 4.95 · reference year 2019
1percentile
How is this calculated?
Metric
International tourist arrivals
Scale
100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
Raw value
6,100 arrivals per year
Native score
4.95 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
1th percentile — ranks 173rd of 174. Comparable across metrics.
Normalization
Log + min–max (log scale, for skewed data)
score = 100 · (ln 6,100 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 4.95
Log 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).
Vegetable supply per capitaTier ADescriptive
100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
Ranks 106th of 191 · native score 21.37 · reference year 2023
45percentile
How is this calculated?
Metric
Vegetable supply per capita
Scale
100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
Raw value
92.4048 kg per person per year
Native score
21.37 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
45th percentile — ranks 106th of 191. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (92.4 − 5.34) / (412.72 − 5.34) = 21.37
Min 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

Age dependency ratioTier ADescriptive
100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
Ranks 60th of 215 · native score 51.8 · reference year 2025
72percentile
How is this calculated?
Metric
Age dependency ratio
Scale
100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
Raw value
63.3221 dependents per 100 working-age
Native score
51.8 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
72th percentile — ranks 60th of 215. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (63.32 − 20.05) / (103.59 − 20.05) = 51.8
Min 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.
Fertility rateTier ADescriptive
100 = highest fertility, 0 = lowest — descriptive, not better or worse
Ranks 59th of 215 · native score 41.9 · reference year 2024
73percentile
How is this calculated?
Metric
Fertility rate
Scale
100 = highest fertility, 0 = lowest — descriptive, not better or worse
Raw value
2.864 births per woman
Native score
41.9 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
73th percentile — ranks 59th of 215. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (2.86 − 0.58) / (6.03 − 0.58) = 41.9
Min 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.
Life expectancy gap (female − male)Tier ADescriptive
100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
Ranks 132nd of 215 · native score 39.3 · reference year 2024
39percentile
How 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
4.45 years (female − male)
Native score
39.3 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
39th percentile — ranks 132nd of 215. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (4.45 − 0.46) / (10.62 − 0.46) = 39.3
Min 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.
Median ageTier ADescriptive
100 = oldest median age, 0 = youngest — descriptive, not better or worse
Ranks 189th of 237 · native score 14.08 · reference year 2023
20percentile
How is this calculated?
Metric
Median age
Scale
100 = oldest median age, 0 = youngest — descriptive, not better or worse
Raw value
20.699 years
Native score
14.08 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
20th percentile — ranks 189th of 237. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (20.7 − 14.32) / (59.63 − 14.32) = 14.08
Min 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.
Foreign-born populationTier ADescriptive
100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
Ranks 88th of 214 · native score 8.8 · reference year 2024
59percentile
How is this calculated?
Metric
Foreign-born population
Scale
100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
Raw value
8.8 % foreign-born
Native score
8.8 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
59th percentile — ranks 88th of 214. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (8.8 − 0) / (100 − 0) = 8.8
The 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.
Net migration rateTier BDescriptive
100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse
Ranks 214th of 215 · native score 0.12 · reference year 2025
1percentile
How 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
-46.8 per 1,000 people
Native score
0.12 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
1th percentile — ranks 214th of 215. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (-46.8 − -46.91) / (43.67 − -46.91) = 0.12
Min 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.
Total populationTier ADescriptive
100 = most populous, 0 = least populous — descriptive, not better or worse
Ranks 210th of 215 · native score 11.22 · reference year 2025
3percentile
How is this calculated?
Metric
Total population
Scale
100 = most populous, 0 = least populous — descriptive, not better or worse
Raw value
36,282 people
Native score
11.22 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
3th percentile — ranks 210th of 215. Comparable across metrics.
Normalization
Log + min–max (log scale, for skewed data)
score = 100 · (ln 36,282 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 11.22
Log 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.
Population densityTier ADescriptive
100 = most dense, 0 = least dense — descriptive, not better or worse
Ranks 63rd of 215 · native score 61.73 · reference year 2023
71percentile
How is this calculated?
Metric
Population density
Scale
100 = most dense, 0 = least dense — descriptive, not better or worse
Raw value
215.706 people per km²
Native score
61.73 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
71th percentile — ranks 63rd of 215. Comparable across metrics.
Normalization
Log + min–max (log scale, for skewed data)
score = 100 · (ln 215.71 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 61.73
Log 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.
Population change (projection)Tier ADescriptive
100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
Ranks 237th of 237 · native score 0 · reference year 2050
0percentile
How is this calculated?
Metric
Population change (projection)
Scale
100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
Raw value
-32.9 % change 2024→2050
Native score
0 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
0th percentile — ranks 237th of 237. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (-32.9 − -32.9) / (99.7 − -32.9) = 0
Min 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.
Refugees (by origin)Tier ADescriptive
100 = most refugees produced, 0 = fewest — descriptive, not better or worse
Ranks 198th of 211 · native score 3.32 · reference year 2024
3percentile
How is this calculated?
Metric
Refugees (by origin)
Scale
100 = most refugees produced, 0 = fewest — descriptive, not better or worse
Raw value
0 refugees
Native score
3.32 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
3th percentile — ranks 198th of 211. Comparable across metrics.
Normalization
Percentile rank across countries
score = percentile rank of 0 among 211 countries = 3.32
The 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.
Remittances receivedTier ADescriptive
100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 10th of 193 · native score 49.77 · reference year 2024
95percentile
How is this calculated?
Metric
Remittances received
Scale
100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
Raw value
23.4766 % of GDP
Native score
49.77 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
95th percentile — ranks 10th of 193. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (23.48 − 0.01) / (47.15 − 0.01) = 49.77
Min 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.
Rural population shareTier ADescriptive
100 = fully rural, 0 = fully urban — descriptive, not better or worse
Ranks 152nd of 215 · native score 20.89 · reference year 2025
30percentile
How is this calculated?
Metric
Rural population share
Scale
100 = fully rural, 0 = fully urban — descriptive, not better or worse
Raw value
20.8945 % rural
Native score
20.89 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
30th percentile — ranks 152nd of 215. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (20.89 − 0) / (100 − 0) = 20.89
The 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.
Sex ratio at birthTier ADescriptive
100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse
Ranks 22nd of 215 · native score 38.82 · reference year 2024
89percentile
How 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
1.07 male births per female birth
Native score
38.82 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
89th percentile — ranks 22nd of 215. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (1.07 − 1.01) / (1.16 − 1.01) = 38.82
Min 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.
UrbanizationTier ADescriptive
100 = fully urban, 0 = fully rural — descriptive, not better or worse
Ranks 64th of 215 · native score 79.11 · reference year 2025
70percentile
How is this calculated?
Metric
Urbanization
Scale
100 = fully urban, 0 = fully rural — descriptive, not better or worse
Raw value
79.1055 % urban
Native score
79.11 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
70th percentile — ranks 64th of 215. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (79.11 − 0) / (100 − 0) = 79.11
The index is kept on its own published scale.
Source
World Bank · World Bank
License
CC BY 4.0
Reference year
2025
Retrieved
2026-07-12
Confidence
Tier A — Official / robust
Source notes
World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.

Environment & infrastructure

Air transport passengersTier ADescriptive
100 = most air passengers, 0 = fewest — descriptive, not better or worse
Ranks 163rd of 177 · native score 8.19 · reference year 2023
8percentile
How is this calculated?
Metric
Air transport passengers
Scale
100 = most air passengers, 0 = fewest — descriptive, not better or worse
Raw value
29,502.2 passengers per year
Native score
8.19 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
8th percentile — ranks 163rd of 177. Comparable across metrics.
Normalization
Percentile rank across countries
score = percentile rank of 29,502.16 among 177 countries = 8.19
The score is the country's position in the distribution.
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.
Climate vulnerabilityTier B
100 = least climate-vulnerable (best), 0 = most vulnerable
Ranks 136th of 190 · native score 39.9 · reference year 2024
29percentile
How is this calculated?
Metric
Climate vulnerability
Scale
100 = least climate-vulnerable (best), 0 = most vulnerable
Raw value
0.498858 index (0–1, higher = more vulnerable)
Native score
39.9 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
29th percentile — ranks 136th of 190. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 − [ 100 · (0.5 − 0.26) / (0.66 − 0.26) ] = 39.9
Min 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 130th of 214 · native score 39.49 · reference year 2024
39percentile
How is this calculated?
Metric
CO₂ emissions per capita
Scale
100 = lowest emissions per capita (best), 0 = highest
Raw value
4.11157 tonnes CO₂ per capita
Native score
39.49 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
39th percentile — ranks 130th of 214. Comparable across metrics.
Normalization
Percentile rank across countries
score = 100 − [ percentile rank of 4.11 among 214 countries ] = 39.49
The 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
70percentile
How 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) = 100
The 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.
Energy use per capitaTier ADescriptive
100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
Ranks 123rd of 177 · native score 55.83 · reference year 2007
31percentile
How is this calculated?
Metric
Energy use per capita
Scale
100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
Raw value
614.971 kg oil-equivalent per capita
Native score
55.83 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
31th percentile — ranks 123rd of 177. Comparable across metrics.
Normalization
Log + min–max (log scale, for skewed data)
score = 100 · (ln 614.97 − ln 9.73) / (ln 16,343.04 − ln 9.73) = 55.83
Log 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.
Fixed broadband subscriptionsTier A
100 = most fixed-broadband subscriptions per capita, 0 = fewest
Ranks 156th of 208 · native score 3.85 · reference year 2022
25percentile
How is this calculated?
Metric
Fixed broadband subscriptions
Scale
100 = most fixed-broadband subscriptions per capita, 0 = fewest
Raw value
2.35048 per 100 people
Native score
3.85 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
25th percentile — ranks 156th of 208. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (2.35 − 0) / (60.97 − 0) = 3.85
Min 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.
Forest areaTier ADescriptive
100 = most forested, 0 = least — descriptive, not better or worse
Ranks 46th of 213 · native score 52.22 · reference year 2023
79percentile
How is this calculated?
Metric
Forest area
Scale
100 = most forested, 0 = least — descriptive, not better or worse
Raw value
52.2222 % of land area
Native score
52.22 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
79th percentile — ranks 46th of 213. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (52.22 − 0) / (100 − 0) = 52.22
The 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 142nd of 209 · native score 65.92 · reference year 2024
32percentile
How is this calculated?
Metric
Internet users
Scale
100 = whole population online, 0 = none
Raw value
65.9158 % of population
Native score
65.92 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
32th percentile — ranks 142nd of 209. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (65.92 − 0) / (100 − 0) = 65.92
The 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 6th of 200 · native score 97.25 · reference year 2023
97percentile
How is this calculated?
Metric
PM2.5 air pollution
Scale
100 = cleanest air (lowest PM2.5), 0 = most polluted
Raw value
4.1016 µg/m³
Native score
97.25 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
97th percentile — ranks 6th of 200. Comparable across metrics.
Normalization
Percentile rank across countries
score = 100 − [ percentile rank of 4.1 among 200 countries ] = 97.25
The 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 115th of 212 · native score 16.1 · reference year 2025
46percentile
How is this calculated?
Metric
Protected land area
Scale
100 = most land protected, 0 = least
Raw value
16.1 % of land area
Native score
16.1 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
46th percentile — ranks 115th of 212. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (16.1 − 0) / (100 − 0) = 16.1
The 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 131st of 212 · native score 12.2 · reference year 2022
38percentile
How is this calculated?
Metric
Renewable energy share
Scale
100 = all energy renewable, 0 = none
Raw value
12.2 % of final energy
Native score
12.2 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
38th percentile — ranks 131st of 212. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (12.2 − 0) / (100 − 0) = 12.2
The 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.

Economy

New business densityTier A
100 = highest new-business density in the dataset, 0 = lowest
Ranks 164th of 182 · native score 0.09 · reference year 2022
10percentile
How is this calculated?
Metric
New business density
Scale
100 = highest new-business density in the dataset, 0 = lowest
Raw value
0.203625 new firms per 1,000 aged 15–64
Native score
0.09 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
10th percentile — ranks 164th of 182. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (0.2 − 0.02) / (201.01 − 0.02) = 0.09
Min 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
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.
Exports of goods & servicesTier ADescriptive
100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 98th of 192 · native score 17.59 · reference year 2025
49percentile
How is this calculated?
Metric
Exports of goods & services
Scale
100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
Raw value
36.039 % of GDP
Native score
17.59 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
49th percentile — ranks 98th of 192. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (36.04 − 1.1) / (199.76 − 1.1) = 17.59
Min 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
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.
Foreign direct investmentTier ADescriptive
100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 50th of 201 · native score 88.77 · reference year 2024
75percentile
How is this calculated?
Metric
Foreign direct investment
Scale
100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
Raw value
4.68731 % of GDP (net inflows)
Native score
88.77 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
75th percentile — ranks 50th of 201. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (4.69 − -1,303.11) / (170.05 − -1,303.11) = 88.77
Min 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 140th of 189 · native score 10.76 · reference year 2031
26percentile
How is this calculated?
Metric
GDP growth (projection)
Scale
100 = highest projected growth, 0 = lowest
Raw value
2.1 % per year (avg 2026–2031)
Native score
10.76 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
26th percentile — ranks 140th of 189. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (2.1 − 0.62) / (14.38 − 0.62) = 10.76
Min 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 144th of 202 · native score 39.94 · reference year 2024
29percentile
How is this calculated?
Metric
GDP per capita (PPP)
Scale
100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
Raw value
8,194.64 international $ (PPP, current)
Native score
39.94 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
29th percentile — ranks 144th of 202. Comparable across metrics.
Normalization
Log + min–max (log scale, for skewed data)
score = 100 · (ln 8,194.64 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 39.94
Log 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.
Government revenueTier ADescriptive
100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 43rd of 155 · native score 25.1 · reference year 2020
73percentile
How is this calculated?
Metric
Government revenue
Scale
100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
Raw value
31.2771 % of GDP
Native score
25.1 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
73th percentile — ranks 43rd of 155. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (31.28 − 3.03) / (115.55 − 3.03) = 25.1
Min 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
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.
Gross savingsTier ADescriptive
100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 15th of 177 · native score 75.39 · reference year 2024
92percentile
How is this calculated?
Metric
Gross savings
Scale
100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
Raw value
38.0881 % of GDP
Native score
75.39 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
92th percentile — ranks 15th of 177. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (38.09 − -21.13) / (57.42 − -21.13) = 75.39
Min and max are this dataset's lowest (-21.13) and highest (57.42) 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.
Income inequality (Gini)Tier A
100 = most equal (lowest Gini in the dataset), 0 = most unequal
Ranks 87th of 167 · native score 66.86 · reference year 2019
48percentile
How is this calculated?
Metric
Income inequality (Gini)
Scale
100 = most equal (lowest Gini in the dataset), 0 = most unequal
Raw value
35.5 Gini index (0–100)
Native score
66.86 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
48th percentile — ranks 87th of 167. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 − [ 100 · (35.5 − 23.8) / (59.1 − 23.8) ] = 66.86
Min and max are this dataset's lowest (23.8) and highest (59.1) 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 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.
Government debtTier BDescriptive
100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
Ranks 185th of 193 · native score 3.82 · reference year 2025
4percentile
How is this calculated?
Metric
Government debt
Scale
100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
Raw value
11.8 % of GDP
Native score
3.82 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
4th percentile — ranks 185th of 193. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (11.8 − 0) / (308.7 − 0) = 3.82
Min 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).

Safety & crime

Deaths in armed conflictsTier A
100 = fewest conflict deaths (most at peace), 0 = most
Ranks 1st of 197 · native score 63.71 · reference year 2025
64percentile
How 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 ] = 63.71
The 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.
Road-traffic deathsTier B
100 = lowest road-death rate (best), 0 = highest
Ranks 34th of 190 · native score 91.18 · reference year 2013
82percentile
How is this calculated?
Metric
Road-traffic deaths
Scale
100 = lowest road-death rate (best), 0 = highest
Raw value
5.7 deaths per 100,000
Native score
91.18 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
82th percentile — ranks 34th of 190. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 − [ 100 · (5.7 − 0) / (64.6 − 0) ] = 91.18
Min and max are this dataset's lowest (0) and highest (64.6) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
Source
World Bank · World Bank
License
CC BY 4.0
Reference year
2013
Retrieved
2026-07-12
Confidence
Tier B — Reputable / modeled
Source notes
World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.

Health

Diabetes prevalenceTier A
100 = lowest diabetes prevalence (best), 0 = highest
Ranks 207th of 208 · native score 19.06 · reference year 2024
1percentile
How is this calculated?
Metric
Diabetes prevalence
Scale
100 = lowest diabetes prevalence (best), 0 = highest
Raw value
25.7 % of adults 20–79
Native score
19.06 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
1th percentile — ranks 207th of 208. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 − [ 100 · (25.7 − 1.5) / (31.4 − 1.5) ] = 19.06
Min 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.
Health expenditure per capitaTier A
100 = highest health spending per capita, 0 = lowest
Ranks 67th of 193 · native score 59.21 · reference year 2023
66percentile
How is this calculated?
Metric
Health expenditure per capita
Scale
100 = highest health spending per capita, 0 = lowest
Raw value
894.215 current US$ per capita
Native score
59.21 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
66th percentile — ranks 67th of 193. Comparable across metrics.
Normalization
Log + min–max (log scale, for skewed data)
score = 100 · (ln 894.22 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 59.21
Log 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 74th of 191 · native score 12.13 · reference year 2010
62percentile
How is this calculated?
Metric
Hospital beds per 1,000
Scale
100 = most hospital beds per capita in the dataset, 0 = fewest
Raw value
2.8 per 1,000 people
Native score
12.13 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
62th percentile — ranks 74th of 191. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (2.8 − 0.15) / (21.99 − 0.15) = 12.13
Min 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
2010
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.
Immunization coverage (DTP3)Tier A
100 = full DTP3 coverage, 0 = none
Ranks 132nd of 193 · native score 85 · reference year 2024
31percentile
How is this calculated?
Metric
Immunization coverage (DTP3)
Scale
100 = full DTP3 coverage, 0 = none
Raw value
85 % of children aged 12–23 months
Native score
85 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
31th percentile — ranks 132nd of 193. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (85 − 0) / (100 − 0) = 85
The 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 133rd of 195 · native score 69.59 · reference year 2024
32percentile
How is this calculated?
Metric
Infant mortality rate
Scale
100 = lowest infant mortality in the dataset, 0 = highest
Raw value
22.7 per 1,000 live births
Native score
69.59 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
32th percentile — ranks 133rd of 195. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 − [ 100 · (22.7 − 1.2) / (71.9 − 1.2) ] = 69.59
Min 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 176th of 215 · native score 39.04 · reference year 2024
18percentile
How is this calculated?
Metric
Life expectancy at birth
Scale
100 = longest life expectancy in the dataset, 0 = shortest
Raw value
67.075 years
Native score
39.04 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
18th percentile — ranks 176th of 215. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (67.08 − 54.64) / (86.5 − 54.64) = 39.04
Min 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 146th of 194 · native score 24.48 · reference year 2023
24percentile
How is this calculated?
Metric
Maternal mortality ratio
Scale
100 = lowest maternal mortality (best), 0 = highest
Raw value
155 deaths per 100,000 live births
Native score
24.48 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
24th percentile — ranks 146th of 194. Comparable across metrics.
Normalization
Percentile rank across countries
score = 100 − [ percentile rank of 155 among 194 countries ] = 24.48
The 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 143rd of 195 · native score 4.51 · reference year 2012
27percentile
How is this calculated?
Metric
Physicians per 1,000
Scale
100 = most physicians per capita in the dataset, 0 = fewest
Raw value
0.467 per 1,000 people
Native score
4.51 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
27th percentile — ranks 143rd of 195. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 · (0.47 − 0.04) / (9.54 − 0.04) = 4.51
Min 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.
Tobacco useTier A
100 = lowest tobacco use (best), 0 = highest
Ranks 138th of 166 · native score 41.36 · reference year 2024
17percentile
How is this calculated?
Metric
Tobacco use
Scale
100 = lowest tobacco use (best), 0 = highest
Raw value
29.9 % of adults
Native score
41.36 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
17th percentile — ranks 138th of 166. Comparable across metrics.
Normalization
Min–max (rescaled against the dataset)
score = 100 − [ 100 · (29.9 − 3.1) / (48.8 − 3.1) ] = 41.36
Min and max are this dataset's lowest (3.1) and highest (48.8) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
Source
World Bank · World Bank
License
CC BY 4.0
Reference year
2024
Retrieved
2026-07-12
Confidence
Tier A — Official / robust
Source notes
World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Under-5 mortality rateTier A
100 = lowest under-5 mortality (best), 0 = highest
Ranks 134th of 195 · native score 31.54 · reference year 2024
32percentile
How is this calculated?
Metric
Under-5 mortality rate
Scale
100 = lowest under-5 mortality (best), 0 = highest
Raw value
26.7 deaths per 1,000 live births
Native score
31.54 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
32th percentile — ranks 134th of 195. Comparable across metrics.
Normalization
Percentile rank across countries
score = 100 − [ percentile rank of 26.7 among 195 countries ] = 31.54
The 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.

Governance & institutions

Government effectivenessTier A
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Ranks 127th of 204 · native score 44.18 · reference year 2024
38percentile
How is this calculated?
Metric
Government effectiveness
Scale
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Raw value
-0.290944 index (−2.5 to +2.5)
Native score
44.18 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
38th percentile — ranks 127th of 204. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (-0.29 − -2.5) / (2.5 − -2.5) = 44.18
The 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 163rd of 193 · native score 12.12 · reference year 2025
16percentile
How is this calculated?
Metric
Women in parliament
Scale
100 = all seats held by women, 0 = none (≈50 = parity)
Raw value
12.1212 % of seats
Native score
12.12 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
16th percentile — ranks 163rd of 193. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (12.12 − 0) / (100 − 0) = 12.12
The index is kept on its own published scale.
Source
World Bank · World Bank
License
CC BY 4.0
Reference year
2025
Retrieved
2026-07-12
Confidence
Tier A — Official / robust
Source notes
World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.

Quality of life & wellbeing

Human Development IndexTier A
100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
Ranks 108th of 193 · native score 73.3 · reference year 2023
44percentile
How is this calculated?
Metric
Human Development Index
Scale
100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
Raw value
0.733 HDI (0–1)
Native score
73.3 — this metric's own 0–100 scale; not comparable to other metrics.
Percentile rank
44th percentile — ranks 108th of 193. Comparable across metrics.
Normalization
Native rescale (index kept on its own scale)
score = 100 · (0.73 − 0) / (1 − 0) = 73.3
The 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.