Afghanistan
AFGSouthern Asia · Asia · 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?”.
80 metrics for this country
Education
- Adult literacy rateTier A
100 = highest adult literacy in the dataset, 0 = lowest
Ranks 151st of 155 · native score 14.27 · reference year 2021
3percentileHow is this calculated?
- Metric
- Adult literacy rate
- Scale
- 100 = highest adult literacy in the dataset, 0 = lowest
- Raw value
- 37.27 % of adults
- Native score
- 14.27 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 3th percentile — ranks 151st of 155. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (37.27 − 26.83) / (100 − 26.83) = 14.27Min 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.
100 = highest education spending (% GDP) in the dataset, 0 = lowest
Ranks 90th of 200 · native score 26.5 · reference year 2017
55percentileHow is this calculated?
- Metric
- Government education spending
- Scale
- 100 = highest education spending (% GDP) in the dataset, 0 = lowest
- Raw value
- 4.34319 % of GDP
- Native score
- 26.5 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 55th percentile — ranks 90th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (4.34 − 0) / (16.39 − 0) = 26.5Min 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
- 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.
- Mean years of schoolingTier A
100 = most years of schooling in the dataset, 0 = fewest
Ranks 131st of 146 · native score 24.77 · reference year 2020
11percentileHow is this calculated?
- Metric
- Mean years of schooling
- Scale
- 100 = most years of schooling in the dataset, 0 = fewest
- Raw value
- 5.69 years
- Native score
- 24.77 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 11th percentile — ranks 131st of 146. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (5.69 − 3.04) / (13.74 − 3.04) = 24.77Min and max are this dataset's lowest (3.04) and highest (13.74) values, so the score is relative to the current country set.
- Source
- Our World in Data · Our World in Data
- License
- CC BY 4.0
- Reference year
- 2020
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Mean years of schooling series compiled by Our World in Data from UNDP Human Development Report and UNESCO education statistics.
100 = lowest pupil–teacher ratio (best), 0 = highest
Ranks 188th of 197 · native score 45.27 · reference year 2018
5percentileHow is this calculated?
- Metric
- Pupil–teacher ratio (primary)
- Scale
- 100 = lowest pupil–teacher ratio (best), 0 = highest
- Raw value
- 48.7898 pupils per teacher
- Native score
- 45.27 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 5th percentile — ranks 188th of 197. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (48.79 − 6.93) / (83.41 − 6.93) ] = 45.27Min 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 142nd of 192 · native score 38.19 · reference year 2023
26percentileHow is this calculated?
- Metric
- Lower-secondary completion rate
- Scale
- 100 = highest completion in the dataset, 0 = lowest
- Raw value
- 62.0526 % of relevant age group
- Native score
- 38.19 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 26th percentile — ranks 142nd of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (62.05 − 8.89) / (148.09 − 8.89) = 38.19Min 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
- 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 tertiary enrollment in the dataset, 0 = lowest
Ranks 157th of 195 · native score 5.52 · reference year 2020
19percentileHow is this calculated?
- Metric
- Tertiary enrollment ratio
- Scale
- 100 = highest tertiary enrollment in the dataset, 0 = lowest
- Raw value
- 10.8544 % gross enrollment
- Native score
- 5.52 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 19th percentile — ranks 157th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (10.85 − 1.84) / (165.11 − 1.84) = 5.52Min 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
- 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.
Society & culture
100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
Ranks 175th of 200 · native score 24.03 · reference year 1996
13percentileHow is this calculated?
- Metric
- Adult male height
- Scale
- 100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
- Raw value
- 165.256 cm
- Native score
- 24.03 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 13th percentile — ranks 175th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (165.26 − 159.79) / (182.54 − 159.79) = 24.03Min 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.
- Child labourTier B
100 = lowest child labour (best), 0 = highest
Ranks 39th of 97 · native score 87.13 · reference year 2011
60percentileHow is this calculated?
- Metric
- Child labour
- Scale
- 100 = lowest child labour (best), 0 = highest
- Raw value
- 9.3 % of children 7–14
- Native score
- 87.13 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 60th percentile — ranks 39th of 97. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (9.3 − 1.23) / (63.92 − 1.23) ] = 87.13Min and max are this dataset's lowest (1.23) and highest (63.92) 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
- 2011
- 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 = highest cocoa supply per person in the dataset, 0 = lowest
Ranks 157th of 191 · native score 0.57 · reference year 2023
18percentileLow 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
- 0.08 kg cocoa per person / year
- Native score
- 0.57 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 18th percentile — ranks 157th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.08 − 0) / (14.07 − 0) = 0.57Min 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 185th of 186 · native score 0.54 · reference year 2025
1percentileHow is this calculated?
- Metric
- Female labour force participation
- Scale
- 100 = highest female participation in the dataset, 0 = lowest
- Raw value
- 5.086 % of women 15+
- Native score
- 0.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 1th percentile — ranks 185th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (5.09 − 4.66) / (82.91 − 4.66) = 0.54Min 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 191st of 191 · native score 0 · reference year 2023
0percentileHow 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
- 0.38 kg per person per year
- Native score
- 0 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 0th percentile — ranks 191st of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.38 − 0.38) / (83.81 − 0.38) = 0Min 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 163rd of 191 · native score 6.79 · reference year 2023
15percentileHow is this calculated?
- Metric
- Fruit supply per capita
- Scale
- 100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 39.92 kg per person per year
- Native score
- 6.79 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 15th percentile — ranks 163rd of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (39.92 − 4.27) / (529.06 − 4.27) = 6.79Min 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 = most gender-equal (GII 0), 0 = most unequal (GII 1)
Ranks 168th of 172 · native score 33.9 · reference year 2023
3percentileHow is this calculated?
- Metric
- Gender equality (inverted GII)
- Scale
- 100 = most gender-equal (GII 0), 0 = most unequal (GII 1)
- Raw value
- 0.661 index (0–1, lower = more equal)
- Native score
- 33.9 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 3th percentile — ranks 168th of 172. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 − [ 100 · (0.66 − 0) / (1 − 0) ] = 33.9The index is kept on its own published scale. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- UNDP Human Development Report (via Our World in Data) · UNDP, Human Development Report Office
- License
- CC BY 3.0 IGO
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Gender Inequality Index from the UNDP Human Development Report, retrieved via the Our World in Data mirror.
- Informal employmentTier A
100 = lowest informal employment (best), 0 = highest
Ranks 112th of 145 · native score 12.69 · reference year 2021
23percentileHow is this calculated?
- Metric
- Informal employment
- Scale
- 100 = lowest informal employment (best), 0 = highest
- Raw value
- 86.135 % of employment
- Native score
- 12.69 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 23th percentile — ranks 112th of 145. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (86.14 − 1.09) / (98.49 − 1.09) ] = 12.69Min 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.
100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
Ranks 187th of 191 · native score 1.89 · reference year 2023
2percentileHow is this calculated?
- Metric
- Meat supply per capita
- Scale
- 100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 6.39 kg per person per year
- Native score
- 1.89 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 2th percentile — ranks 187th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (6.39 − 3.49) / (156.93 − 3.49) = 1.89Min 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 194th of 214 · native score 7.5 · reference year 2019
10percentileHow is this calculated?
- Metric
- Social protection coverage
- Scale
- 100 = universal social protection coverage, 0 = none
- Raw value
- 7.5 % of population
- Native score
- 7.5 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 10th percentile — ranks 194th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (7.5 − 0) / (100 − 0) = 7.5The 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 = highest union density in the dataset, 0 = lowest — descriptive, not better or worse
Ranks 69th of 139 · native score 18.16 · reference year 2019
51percentileHow is this calculated?
- Metric
- Trade union density
- Scale
- 100 = highest union density in the dataset, 0 = lowest — descriptive, not better or worse
- Raw value
- 16.767 % of employees
- Native score
- 18.16 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 51th percentile — ranks 69th of 139. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (16.77 − 0.2) / (91.42 − 0.2) = 18.16Min 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
- 2019
- 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 129th of 191 · native score 14.25 · reference year 2023
33percentileHow is this calculated?
- Metric
- Vegetable supply per capita
- Scale
- 100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 63.41 kg per person per year
- Native score
- 14.25 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 33th percentile — ranks 129th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (63.41 − 5.34) / (412.72 − 5.34) = 14.25Min 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 14th of 215 · native score 73.89 · reference year 2025
94percentileHow is this calculated?
- Metric
- Age dependency ratio
- Scale
- 100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 81.7736 dependents per 100 working-age
- Native score
- 73.89 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 94th percentile — ranks 14th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (81.77 − 20.05) / (103.59 − 20.05) = 73.89Min 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 9th of 215 · native score 76.74 · reference year 2024
96percentileHow is this calculated?
- Metric
- Fertility rate
- Scale
- 100 = highest fertility, 0 = lowest — descriptive, not better or worse
- Raw value
- 4.761 births per woman
- Native score
- 76.74 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 96th percentile — ranks 9th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (4.76 − 0.58) / (6.03 − 0.58) = 76.74Min 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 196th of 215 · native score 26.1 · reference year 2024
9percentileHow is this calculated?
- Metric
- Life expectancy gap (female − male)
- Scale
- 100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
- Raw value
- 3.108 years (female − male)
- Native score
- 26.1 — 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 · (3.11 − 0.46) / (10.62 − 0.46) = 26.1Min 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 226th of 237 · native score 5.78 · reference year 2023
5percentileHow is this calculated?
- Metric
- Median age
- Scale
- 100 = oldest median age, 0 = youngest — descriptive, not better or worse
- Raw value
- 16.94 years
- Native score
- 5.78 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 5th percentile — ranks 226th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (16.94 − 14.32) / (59.63 − 14.32) = 5.78Min 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 205th of 214 · native score 0.2 · reference year 2024
4percentileHow is this calculated?
- Metric
- Foreign-born population
- Scale
- 100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
- Raw value
- 0.2 % foreign-born
- Native score
- 0.2 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 4th percentile — ranks 205th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.2 − 0) / (100 − 0) = 0.2The 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 146th of 215 · native score 49.91 · reference year 2025
32percentileHow 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
- -1.697 per 1,000 people
- Native score
- 49.91 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 32th percentile — ranks 146th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-1.7 − -46.91) / (43.67 − -46.91) = 49.91Min 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 36th of 215 · native score 70.63 · reference year 2025
83percentileHow is this calculated?
- Metric
- Total population
- Scale
- 100 = most populous, 0 = least populous — descriptive, not better or worse
- Raw value
- 43,844,111 people
- Native score
- 70.63 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 83th percentile — ranks 36th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 43,844,111 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 70.63Log 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 140th of 215 · native score 51.47 · reference year 2023
35percentileHow is this calculated?
- Metric
- Population density
- Scale
- 100 = most dense, 0 = least dense — descriptive, not better or worse
- Raw value
- 63.5585 people per km²
- Native score
- 51.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 35th percentile — ranks 140th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 63.56 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 51.47Log 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 12th of 237 · native score 85.37 · reference year 2050
95percentileHow is this calculated?
- Metric
- Population change (projection)
- Scale
- 100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
- Raw value
- 80.3 % change 2024→2050
- Native score
- 85.37 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 12th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (80.3 − -32.9) / (99.7 − -32.9) = 85.37Min 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 2nd of 211 · native score 99.29 · reference year 2024
99percentileHow is this calculated?
- Metric
- Refugees (by origin)
- Scale
- 100 = most refugees produced, 0 = fewest — descriptive, not better or worse
- Raw value
- 5,766,559 refugees
- Native score
- 99.29 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 99th percentile — ranks 2nd of 211. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 5,766,559 among 211 countries = 99.29The 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 69th of 193 · native score 8.36 · reference year 2020
65percentileHow is this calculated?
- Metric
- Remittances received
- Scale
- 100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 3.9533 % of GDP
- Native score
- 8.36 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 65th percentile — ranks 69th of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.95 − 0.01) / (47.15 − 0.01) = 8.36Min 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
- 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 = fully rural, 0 = fully urban — descriptive, not better or worse
Ranks 14th of 215 · native score 74.06 · reference year 2025
94percentileHow is this calculated?
- Metric
- Rural population share
- Scale
- 100 = fully rural, 0 = fully urban — descriptive, not better or worse
- Raw value
- 74.0598 % rural
- Native score
- 74.06 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 94th percentile — ranks 14th of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (74.06 − 0) / (100 − 0) = 74.06The 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 104th of 215 · native score 26.32 · reference year 2024
50percentileHow 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
- 1.051 male births per female birth
- Native score
- 26.32 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 50th percentile — ranks 104th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.05 − 1.01) / (1.16 − 1.01) = 26.32Min 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 202nd of 215 · native score 25.94 · reference year 2025
6percentileHow is this calculated?
- Metric
- Urbanization
- Scale
- 100 = fully urban, 0 = fully rural — descriptive, not better or worse
- Raw value
- 25.9402 % urban
- Native score
- 25.94 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 6th percentile — ranks 202nd of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (25.94 − 0) / (100 − 0) = 25.94The 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
100 = most air passengers, 0 = fewest — descriptive, not better or worse
Ranks 101st of 177 · native score 43.22 · reference year 2023
43percentileHow is this calculated?
- Metric
- Air transport passengers
- Scale
- 100 = most air passengers, 0 = fewest — descriptive, not better or worse
- Raw value
- 1,031,379 passengers per year
- Native score
- 43.22 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 43th percentile — ranks 101st of 177. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 1,031,379 among 177 countries = 43.22The 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 181st of 190 · native score 11.11 · reference year 2024
5percentileHow is this calculated?
- Metric
- Climate vulnerability
- Scale
- 100 = least climate-vulnerable (best), 0 = most vulnerable
- Raw value
- 0.611631 index (0–1, higher = more vulnerable)
- Native score
- 11.11 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 5th percentile — ranks 181st of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (0.61 − 0.26) / (0.66 − 0.26) ] = 11.11Min 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 20th of 214 · native score 90.89 · reference year 2024
91percentileHow is this calculated?
- Metric
- CO₂ emissions per capita
- Scale
- 100 = lowest emissions per capita (best), 0 = highest
- Raw value
- 0.253848 tonnes CO₂ per capita
- Native score
- 90.89 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 91th percentile — ranks 20th of 214. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 0.25 among 214 countries ] = 90.89The 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 165th of 214 · native score 85.3 · reference year 2023
23percentileHow is this calculated?
- Metric
- Access to electricity
- Scale
- 100 = universal electricity access, 0 = none
- Raw value
- 85.3 % of population
- Native score
- 85.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 23th percentile — ranks 165th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (85.3 − 0) / (100 − 0) = 85.3The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most fixed-broadband subscriptions per capita, 0 = fewest
Ranks 197th of 208 · native score 0.13 · reference year 2023
5percentileHow is this calculated?
- Metric
- Fixed broadband subscriptions
- Scale
- 100 = most fixed-broadband subscriptions per capita, 0 = fewest
- Raw value
- 0.0800873 per 100 people
- Native score
- 0.13 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 5th percentile — ranks 197th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.08 − 0) / (60.97 − 0) = 0.13Min 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
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most forested, 0 = least — descriptive, not better or worse
Ranks 188th of 213 · native score 1.85 · reference year 2023
12percentileHow is this calculated?
- Metric
- Forest area
- Scale
- 100 = most forested, 0 = least — descriptive, not better or worse
- Raw value
- 1.85278 % of land area
- Native score
- 1.85 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 12th percentile — ranks 188th of 213. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (1.85 − 0) / (100 − 0) = 1.85The 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 201st of 209 · native score 16.09 · reference year 2024
4percentileHow is this calculated?
- Metric
- Internet users
- Scale
- 100 = whole population online, 0 = none
- Raw value
- 16.095 % of population
- Native score
- 16.09 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 4th percentile — ranks 201st of 209. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (16.09 − 0) / (100 − 0) = 16.09The 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 = best logistics performance (index 5), 0 = worst (1)
Ranks 167th of 169 · native score 22.5 · reference year 2022
1percentileHow is this calculated?
- Metric
- Logistics Performance Index
- Scale
- 100 = best logistics performance (index 5), 0 = worst (1)
- Raw value
- 1.9 index (1–5)
- Native score
- 22.5 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 1th percentile — ranks 167th of 169. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (1.9 − 1) / (5 − 1) = 22.5The 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.
- PM2.5 air pollutionTier A
100 = cleanest air (lowest PM2.5), 0 = most polluted
Ranks 175th of 200 · native score 12.75 · reference year 2023
13percentileHow is this calculated?
- Metric
- PM2.5 air pollution
- Scale
- 100 = cleanest air (lowest PM2.5), 0 = most polluted
- Raw value
- 37.9483 µg/m³
- Native score
- 12.75 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 13th percentile — ranks 175th of 200. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 37.95 among 200 countries ] = 12.75The 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 194th of 212 · native score 3.6 · reference year 2025
9percentileHow is this calculated?
- Metric
- Protected land area
- Scale
- 100 = most land protected, 0 = least
- Raw value
- 3.6 % of land area
- Native score
- 3.6 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 9th percentile — ranks 194th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (3.6 − 0) / (100 − 0) = 3.6The 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 107th of 212 · native score 20 · reference year 2022
50percentileHow is this calculated?
- Metric
- Renewable energy share
- Scale
- 100 = all energy renewable, 0 = none
- Raw value
- 20 % of final energy
- Native score
- 20 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 50th percentile — ranks 107th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (20 − 0) / (100 − 0) = 20The 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 163rd of 182 · native score 0.1 · reference year 2018
11percentileHow is this calculated?
- Metric
- New business density
- Scale
- 100 = highest new-business density in the dataset, 0 = lowest
- Raw value
- 0.220836 new firms per 1,000 aged 15–64
- Native score
- 0.1 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 11th percentile — ranks 163rd of 182. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.22 − 0.02) / (201.01 − 0.02) = 0.1Min 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
- 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 employment ratio in the dataset, 0 = lowest
Ranks 181st of 186 · native score 17.12 · reference year 2025
3percentileHow is this calculated?
- Metric
- Employment-to-population ratio
- Scale
- 100 = highest employment ratio in the dataset, 0 = lowest
- Raw value
- 32.457 % of population 15+
- Native score
- 17.12 — 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 · (32.46 − 21.21) / (86.9 − 21.21) = 17.12Min and max are this dataset's lowest (21.21) and highest (86.9) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 167th of 192 · native score 7.35 · reference year 2024
13percentileHow is this calculated?
- Metric
- Exports of goods & services
- Scale
- 100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 15.7028 % of GDP
- Native score
- 7.35 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 13th percentile — ranks 167th of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (15.7 − 1.1) / (199.76 − 1.1) = 7.35Min 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
- 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 net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 171st of 201 · native score 88.47 · reference year 2021
14percentileHow is this calculated?
- Metric
- Foreign direct investment
- Scale
- 100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 0.144467 % of GDP (net inflows)
- Native score
- 88.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 14th percentile — ranks 171st of 201. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.14 − -1,303.11) / (170.05 − -1,303.11) = 88.47Min 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
- 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.
- GDP per capita (PPP)Tier A
100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
Ranks 190th of 202 · native score 13.15 · reference year 2023
6percentileHow is this calculated?
- Metric
- GDP per capita (PPP)
- Scale
- 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
- Raw value
- 2,201.72 international $ (PPP, current)
- Native score
- 13.15 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 6th percentile — ranks 190th of 202. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 2,201.72 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 13.15Log 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
- 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 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 141st of 155 · native score 8.89 · reference year 2017
9percentileHow is this calculated?
- Metric
- Government revenue
- Scale
- 100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 13.0393 % of GDP
- Native score
- 8.89 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 9th percentile — ranks 141st of 155. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (13.04 − 3.03) / (115.55 − 3.03) = 8.89Min 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 gross savings (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 173rd of 177 · native score 23.41 · reference year 2020
3percentileHow is this calculated?
- Metric
- Gross savings
- Scale
- 100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- -2.73777 % of GDP
- Native score
- 23.41 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 3th percentile — ranks 173rd of 177. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-2.74 − -21.13) / (57.42 − -21.13) = 23.41Min 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
- 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 inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
Ranks 192nd of 192 · native score 0.26 · reference year 2024
0percentileHow is this calculated?
- Metric
- Inflation rate
- Scale
- 100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
- Raw value
- -6.60119 % annual change (CPI)
- Native score
- 0.26 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 0th percentile — ranks 192nd of 192. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of -6.6 among 192 countries = 0.26The score is the country's position in the distribution.
- 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.
- Labour productivityTier A
100 = highest output per worker, 0 = lowest
Ranks 151st of 177 · native score 31.76 · reference year 2023
15percentileHow is this calculated?
- Metric
- Labour productivity
- Scale
- 100 = highest output per worker, 0 = lowest
- Raw value
- 10,810.4 constant PPP$ per worker
- Native score
- 31.76 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 15th percentile — ranks 151st of 177. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 10,810.38 − ln 2,444.23) / (ln 263,863.91 − ln 2,444.23) = 31.76Log 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
- 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 debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
Ranks 187th of 193 · native score 2.59 · reference year 2025
3percentileHow is this calculated?
- Metric
- Government debt
- Scale
- 100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
- Raw value
- 8 % of GDP
- Native score
- 2.59 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 3th percentile — ranks 187th of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (8 − 0) / (308.7 − 0) = 2.59Min 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 166th of 186 · native score 61.2 · reference year 2025
11percentileHow is this calculated?
- Metric
- Unemployment rate
- Scale
- 100 = lowest unemployment in the dataset, 0 = highest
- Raw value
- 13.351 % of labour force
- Native score
- 61.2 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 11th percentile — ranks 166th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (13.35 − 0.13) / (34.2 − 0.13) ] = 61.2Min 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 119th of 186 · native score 78.6 · reference year 2025
36percentileHow is this calculated?
- Metric
- Youth unemployment rate
- Scale
- 100 = lowest youth unemployment (best), 0 = highest
- Raw value
- 16.785 % of labour force 15–24
- Native score
- 78.6 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 36th percentile — ranks 119th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (16.79 − 0.46) / (76.77 − 0.46) ] = 78.6Min 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.
Safety & crime
100 = fewest conflict deaths (most at peace), 0 = most
Ranks 169th of 197 · native score 14.47 · reference year 2025
14percentileHow is this calculated?
- Metric
- Deaths in armed conflicts
- Scale
- 100 = fewest conflict deaths (most at peace), 0 = most
- Raw value
- 330 deaths per year
- Native score
- 14.47 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 14th percentile — ranks 169th of 197. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 330 among 197 countries ] = 14.47The 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 112th of 193 · native score 42.23 · reference year 2021
42percentileHow is this calculated?
- Metric
- Homicide rate
- Scale
- 100 = safest (fewest homicides), 0 = most homicides
- Raw value
- 4.03246 per 100,000 population
- Native score
- 42.23 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 42th percentile — ranks 112th of 193. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 4.03 among 193 countries ] = 42.23The 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
- 2021
- 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.
100 = fewest internally displaced (most stable), 0 = most
Ranks 78th of 82 · native score 5.49 · reference year 2025
5percentileHow is this calculated?
- Metric
- Internally displaced persons
- Scale
- 100 = fewest internally displaced (most stable), 0 = most
- Raw value
- 4,355,000 people
- Native score
- 5.49 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 5th percentile — ranks 78th of 82. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 4,355,000 among 82 countries ] = 5.49The 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
- 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.
- Road-traffic deathsTier B
100 = lowest road-death rate (best), 0 = highest
Ranks 104th of 190 · native score 75.39 · reference year 2019
46percentileHow is this calculated?
- Metric
- Road-traffic deaths
- Scale
- 100 = lowest road-death rate (best), 0 = highest
- Raw value
- 15.9 deaths per 100,000
- Native score
- 75.39 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 46th percentile — ranks 104th of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (15.9 − 0) / (64.6 − 0) ] = 75.39Min 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 165th of 180 · native score 17 · reference year 2024
8percentileHow is this calculated?
- Metric
- Corruption Perceptions Index
- Scale
- 100 = cleanest (least corrupt), 0 = most corrupt
- Raw value
- 17 CPI score (0–100)
- Native score
- 17 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 8th percentile — ranks 165th of 180. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (17 − 0) / (100 − 0) = 17The 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.
100 = most democratic (index 1.0), 0 = least democratic
Ranks 172nd of 175 · native score 6.9 · reference year 2025
2percentileHow is this calculated?
- Metric
- Electoral democracy index
- Scale
- 100 = most democratic (index 1.0), 0 = least democratic
- Raw value
- 0.069 index (0–1)
- Native score
- 6.9 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 2th percentile — ranks 172nd of 175. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.07 − 0) / (1 − 0) = 6.9The index is kept on its own published scale.
- Source
- V-Dem Institute (via Our World in Data) · V-Dem Institute, University of Gothenburg
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Varieties of Democracy (V-Dem) expert-coded indices (electoral democracy, rule of law, freedom of expression), retrieved via the Our World in Data mirror. Expert-coded estimates; see V-Dem for uncertainty intervals.
100 = most free expression (index 1.0), 0 = least
Ranks 173rd of 175 · native score 2.2 · reference year 2025
1percentileHow is this calculated?
- Metric
- Freedom of expression index
- Scale
- 100 = most free expression (index 1.0), 0 = least
- Raw value
- 0.022 index (0–1)
- Native score
- 2.2 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 1th percentile — ranks 173rd of 175. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.02 − 0) / (1 − 0) = 2.2The index is kept on its own published scale.
- Source
- V-Dem Institute (via Our World in Data) · V-Dem Institute, University of Gothenburg
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Varieties of Democracy (V-Dem) expert-coded indices (electoral democracy, rule of law, freedom of expression), retrieved via the Our World in Data mirror. Expert-coded estimates; see V-Dem for uncertainty intervals.
- Government effectivenessTier A
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Ranks 201st of 204 · native score 11.32 · reference year 2024
2percentileHow is this calculated?
- Metric
- Government effectiveness
- Scale
- 100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
- Raw value
- -1.934 index (−2.5 to +2.5)
- Native score
- 11.32 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 2th percentile — ranks 201st of 204. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (-1.93 − -2.5) / (2.5 − -2.5) = 11.32The 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.
- Rule of law indexTier A
100 = strongest rule of law (index 1.0), 0 = weakest
Ranks 160th of 175 · native score 8.4 · reference year 2025
9percentileHow is this calculated?
- Metric
- Rule of law index
- Scale
- 100 = strongest rule of law (index 1.0), 0 = weakest
- Raw value
- 0.084 index (0–1)
- Native score
- 8.4 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 9th percentile — ranks 160th of 175. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.08 − 0) / (1 − 0) = 8.4The index is kept on its own published scale.
- Source
- V-Dem Institute (via Our World in Data) · V-Dem Institute, University of Gothenburg
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Varieties of Democracy (V-Dem) expert-coded indices (electoral democracy, rule of law, freedom of expression), retrieved via the Our World in Data mirror. Expert-coded estimates; see V-Dem for uncertainty intervals.
- Women in parliamentTier A
100 = all seats held by women, 0 = none (≈50 = parity)
Ranks 90th of 193 · native score 27.02 · reference year 2021
54percentileHow is this calculated?
- Metric
- Women in parliament
- Scale
- 100 = all seats held by women, 0 = none (≈50 = parity)
- Raw value
- 27.0161 % of seats
- Native score
- 27.02 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 54th percentile — ranks 90th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (27.02 − 0) / (100 − 0) = 27.02The index is kept on its own published scale.
- 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.
Health
- Diabetes prevalenceTier A
100 = lowest diabetes prevalence (best), 0 = highest
Ranks 150th of 208 · native score 65.89 · reference year 2024
28percentileHow is this calculated?
- Metric
- Diabetes prevalence
- Scale
- 100 = lowest diabetes prevalence (best), 0 = highest
- Raw value
- 11.7 % of adults 20–79
- Native score
- 65.89 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 28th percentile — ranks 150th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (11.7 − 1.5) / (31.4 − 1.5) ] = 65.89Min 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 167th of 193 · native score 18.35 · reference year 2023
14percentileHow is this calculated?
- Metric
- Health expenditure per capita
- Scale
- 100 = highest health spending per capita, 0 = lowest
- Raw value
- 59.0677 current US$ per capita
- Native score
- 18.35 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 14th percentile — ranks 167th of 193. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 59.07 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 18.35Log 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 183rd of 191 · native score 0.92 · reference year 2023
4percentileHow is this calculated?
- Metric
- Hospital beds per 1,000
- Scale
- 100 = most hospital beds per capita in the dataset, 0 = fewest
- Raw value
- 0.35 per 1,000 people
- Native score
- 0.92 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 4th percentile — ranks 183rd of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.35 − 0.15) / (21.99 − 0.15) = 0.92Min 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
- 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 = full DTP3 coverage, 0 = none
Ranks 186th of 193 · native score 59 · reference year 2024
4percentileHow is this calculated?
- Metric
- Immunization coverage (DTP3)
- Scale
- 100 = full DTP3 coverage, 0 = none
- Raw value
- 59 % of children aged 12–23 months
- Native score
- 59 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 4th percentile — ranks 186th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (59 − 0) / (100 − 0) = 59The 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 183rd of 195 · native score 33.38 · reference year 2024
6percentileHow is this calculated?
- Metric
- Infant mortality rate
- Scale
- 100 = lowest infant mortality in the dataset, 0 = highest
- Raw value
- 48.3 per 1,000 live births
- Native score
- 33.38 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 6th percentile — ranks 183rd of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (48.3 − 1.2) / (71.9 − 1.2) ] = 33.38Min 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 182nd of 215 · native score 36.58 · reference year 2024
16percentileHow is this calculated?
- Metric
- Life expectancy at birth
- Scale
- 100 = longest life expectancy in the dataset, 0 = shortest
- Raw value
- 66.289 years
- Native score
- 36.58 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 16th percentile — ranks 182nd of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (66.29 − 54.64) / (86.5 − 54.64) = 36.58Min 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 188th of 194 · native score 3.35 · reference year 2023
3percentileHow is this calculated?
- Metric
- Maternal mortality ratio
- Scale
- 100 = lowest maternal mortality (best), 0 = highest
- Raw value
- 521 deaths per 100,000 live births
- Native score
- 3.35 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 3th percentile — ranks 188th of 194. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 521 among 194 countries ] = 3.35The 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 151st of 195 · native score 2.94 · reference year 2023
23percentileHow is this calculated?
- Metric
- Physicians per 1,000
- Scale
- 100 = most physicians per capita in the dataset, 0 = fewest
- Raw value
- 0.317 per 1,000 people
- Native score
- 2.94 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 23th percentile — ranks 151st of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.32 − 0.04) / (9.54 − 0.04) = 2.94Min and max are this dataset's lowest (0.04) and highest (9.54) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Safe sanitationTier A
100 = universal safe sanitation, 0 = none
Ranks 121st of 145 · native score 24.78 · reference year 2024
17percentileHow is this calculated?
- Metric
- Safe sanitation
- Scale
- 100 = universal safe sanitation, 0 = none
- Raw value
- 24.7774 % of population
- Native score
- 24.78 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 17th percentile — ranks 121st of 145. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (24.78 − 0) / (100 − 0) = 24.78The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Safe drinking waterTier A
100 = universal safe drinking water, 0 = none
Ranks 128th of 151 · native score 30.55 · reference year 2024
16percentileHow is this calculated?
- Metric
- Safe drinking water
- Scale
- 100 = universal safe drinking water, 0 = none
- Raw value
- 30.5547 % of population
- Native score
- 30.55 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 16th percentile — ranks 128th of 151. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (30.55 − 0) / (100 − 0) = 30.55The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Tobacco useTier A
100 = lowest tobacco use (best), 0 = highest
Ranks 100th of 166 · native score 58.42 · reference year 2024
40percentileHow is this calculated?
- Metric
- Tobacco use
- Scale
- 100 = lowest tobacco use (best), 0 = highest
- Raw value
- 22.1 % of adults
- Native score
- 58.42 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 40th percentile — ranks 100th of 166. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (22.1 − 3.1) / (48.8 − 3.1) ] = 58.42Min 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 170th of 195 · native score 13.08 · reference year 2024
13percentileHow is this calculated?
- Metric
- Under-5 mortality rate
- Scale
- 100 = lowest under-5 mortality (best), 0 = highest
- Raw value
- 53 deaths per 1,000 live births
- Native score
- 13.08 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 13th percentile — ranks 170th of 195. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 53 among 195 countries ] = 13.08The 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 157th of 169 · native score 50.48 · reference year 2023
7percentileHow is this calculated?
- Metric
- Undernourishment
- Scale
- 100 = lowest undernourishment (best), 0 = highest
- Raw value
- 28.1 % of population
- Native score
- 50.48 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 7th percentile — ranks 157th of 169. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (28.1 − 2.5) / (54.2 − 2.5) ] = 50.48Min 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.
Quality of life & wellbeing
- Human Development IndexTier A
100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
Ranks 181st of 193 · native score 49.6 · reference year 2023
6percentileHow is this calculated?
- Metric
- Human Development Index
- Scale
- 100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
- Raw value
- 0.496 HDI (0–1)
- Native score
- 49.6 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 6th percentile — ranks 181st of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.5 − 0) / (1 − 0) = 49.6The 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.
100 = highest average life evaluation (ladder 10), 0 = lowest (ladder 0)
Ranks 165th of 165 · native score 14.46 · reference year 2025
0percentileHow is this calculated?
- Metric
- Life satisfaction (happiness)
- Scale
- 100 = highest average life evaluation (ladder 10), 0 = lowest (ladder 0)
- Raw value
- 1.446 Cantril ladder (0–10)
- Native score
- 14.46 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 0th percentile — ranks 165th of 165. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (1.45 − 0) / (10 − 0) = 14.46The index is kept on its own published scale.
- Source
- World Happiness Report (via Our World in Data) · World Happiness Report / Gallup
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- Self-reported life evaluation (Cantril ladder, 0–10) from the Gallup World Poll, published in the World Happiness Report, retrieved via the Our World in Data mirror. Survey-based (Tier B).