Macau
MACEastern Asia · Asia
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?”.
58 metrics for this country
Education
- Adult literacy rateTier A
100 = highest adult literacy in the dataset, 0 = lowest
Ranks 56th of 155 · native score 95.27 · reference year 2016
64percentileHow is this calculated?
- Metric
- Adult literacy rate
- Scale
- 100 = highest adult literacy in the dataset, 0 = lowest
- Raw value
- 96.54 % of adults
- Native score
- 95.27 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 56th of 155. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (96.54 − 26.83) / (100 − 26.83) = 95.27Min 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
- 2016
- 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 129th of 200 · native score 21.36 · reference year 2023
36percentileHow is this calculated?
- Metric
- Government education spending
- Scale
- 100 = highest education spending (% GDP) in the dataset, 0 = lowest
- Raw value
- 3.50183 % of GDP
- Native score
- 21.36 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 36th percentile — ranks 129th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.5 − 0) / (16.39 − 0) = 21.36Min and max are this dataset's lowest (0) and highest (16.39) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Mean years of schoolingTier A
100 = most years of schooling in the dataset, 0 = fewest
Ranks 47th of 146 · native score 74.11 · reference year 2020
68percentileHow is this calculated?
- Metric
- Mean years of schooling
- Scale
- 100 = most years of schooling in the dataset, 0 = fewest
- Raw value
- 10.97 years
- Native score
- 74.11 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 68th percentile — ranks 47th of 146. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (10.97 − 3.04) / (13.74 − 3.04) = 74.11Min 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.
- PISA mathsTier A
100 = highest mathematics score in the dataset, 0 = lowest — participating economies only, not a world ranking
Ranks 2nd of 55 · native score 87.34 · reference year 2018
97percentileHow is this calculated?
- Metric
- PISA maths
- Scale
- 100 = highest mathematics score in the dataset, 0 = lowest — participating economies only, not a world ranking
- Raw value
- 557.67 PISA points
- Native score
- 87.34 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 2nd of 55. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (557.67 − 325.1) / (591.39 − 325.1) = 87.34Min and max are this dataset's lowest (325.1) and highest (591.39) 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.
- PISA readingTier A
100 = highest reading score in the dataset, 0 = lowest — participating economies only, not a world ranking
Ranks 2nd of 55 · native score 87.51 · reference year 2018
97percentileHow is this calculated?
- Metric
- PISA reading
- Scale
- 100 = highest reading score in the dataset, 0 = lowest — participating economies only, not a world ranking
- Raw value
- 525.116 PISA points
- Native score
- 87.51 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 2nd of 55. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (525.12 − 314.02) / (555.24 − 314.02) = 87.51Min and max are this dataset's lowest (314.02) and highest (555.24) 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.
- PISA scienceTier A
100 = highest science score in the dataset, 0 = lowest — participating economies only, not a world ranking
Ranks 2nd of 55 · native score 82.04 · reference year 2018
97percentileHow is this calculated?
- Metric
- PISA science
- Scale
- 100 = highest science score in the dataset, 0 = lowest — participating economies only, not a world ranking
- Raw value
- 543.586 PISA points
- Native score
- 82.04 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 2nd of 55. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (543.59 − 329.55) / (590.45 − 329.55) = 82.04Min and max are this dataset's lowest (329.55) and highest (590.45) 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 = lowest pupil–teacher ratio (best), 0 = highest
Ranks 46th of 197 · native score 91.41 · reference year 2018
77percentileHow is this calculated?
- Metric
- Pupil–teacher ratio (primary)
- Scale
- 100 = lowest pupil–teacher ratio (best), 0 = highest
- Raw value
- 13.4984 pupils per teacher
- Native score
- 91.41 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 77th percentile — ranks 46th of 197. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (13.5 − 6.93) / (83.41 − 6.93) ] = 91.41Min 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.
- Researchers in R&DTier A
100 = most researchers per capita, 0 = fewest
Ranks 26th of 144 · native score 85.54 · reference year 2024
82percentileHow is this calculated?
- Metric
- Researchers in R&D
- Scale
- 100 = most researchers per capita, 0 = fewest
- Raw value
- 4,634.11 per million people
- Native score
- 85.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 82th percentile — ranks 26th of 144. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 4,634.11 − ln 1.45) / (ln 18,129.75 − ln 1.45) = 85.54Log scale (values are heavily skewed). 0 and 100 are the dataset's min (1.45) and max (18,129.75) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest completion in the dataset, 0 = lowest
Ranks 68th of 192 · native score 61.26 · reference year 2024
65percentileHow is this calculated?
- Metric
- Lower-secondary completion rate
- Scale
- 100 = highest completion in the dataset, 0 = lowest
- Raw value
- 94.1667 % of relevant age group
- Native score
- 61.26 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 65th percentile — ranks 68th of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (94.17 − 8.89) / (148.09 − 8.89) = 61.26Min and max are this dataset's lowest (8.89) and highest (148.09) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest tertiary enrollment in the dataset, 0 = lowest
Ranks 2nd of 195 · native score 85.76 · reference year 2024
99percentileHow is this calculated?
- Metric
- Tertiary enrollment ratio
- Scale
- 100 = highest tertiary enrollment in the dataset, 0 = lowest
- Raw value
- 141.865 % gross enrollment
- Native score
- 85.76 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 99th percentile — ranks 2nd of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (141.86 − 1.84) / (165.11 − 1.84) = 85.76Min 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.
Demographics & migration
100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
Ranks 197th of 215 · native score 24.43 · reference year 2025
9percentileHow is this calculated?
- Metric
- Age dependency ratio
- Scale
- 100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 40.4569 dependents per 100 working-age
- Native score
- 24.43 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 9th percentile — ranks 197th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (40.46 − 20.05) / (103.59 − 20.05) = 24.43Min 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 215th of 215 · native score 0 · reference year 2024
0percentileHow is this calculated?
- Metric
- Fertility rate
- Scale
- 100 = highest fertility, 0 = lowest — descriptive, not better or worse
- Raw value
- 0.582 births per woman
- Native score
- 0 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 0th percentile — ranks 215th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.58 − 0.58) / (6.03 − 0.58) = 0Min 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 77th of 215 · native score 50.61 · reference year 2024
64percentileHow is this calculated?
- Metric
- Life expectancy gap (female − male)
- Scale
- 100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
- Raw value
- 5.6 years (female − male)
- Native score
- 50.61 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 77th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (5.6 − 0.46) / (10.62 − 0.46) = 50.61Min 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 69th of 237 · native score 52.95 · reference year 2023
71percentileHow is this calculated?
- Metric
- Median age
- Scale
- 100 = oldest median age, 0 = youngest — descriptive, not better or worse
- Raw value
- 38.31 years
- Native score
- 52.95 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 71th percentile — ranks 69th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (38.31 − 14.32) / (59.63 − 14.32) = 52.95Min 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 11th of 214 · native score 59.3 · reference year 2024
95percentileHow is this calculated?
- Metric
- Foreign-born population
- Scale
- 100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
- Raw value
- 59.3 % foreign-born
- Native score
- 59.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 11th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (59.3 − 0) / (100 − 0) = 59.3The 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 115th of 215 · native score 51.26 · reference year 2025
46percentileHow 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
- -0.478 per 1,000 people
- Native score
- 51.26 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 46th percentile — ranks 115th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-0.48 − -46.91) / (43.67 − -46.91) = 51.26Min 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 166th of 215 · native score 35.83 · reference year 2025
23percentileHow is this calculated?
- Metric
- Total population
- Scale
- 100 = most populous, 0 = least populous — descriptive, not better or worse
- Raw value
- 685,900 people
- Native score
- 35.83 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 23th percentile — ranks 166th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 685,900 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 35.83Log 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 1st of 215 · native score 100 · reference year 2023
100percentileHow is this calculated?
- Metric
- Population density
- Scale
- 100 = most dense, 0 = least dense — descriptive, not better or worse
- Raw value
- 20,569.7 people per km²
- Native score
- 100 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 100th percentile — ranks 1st of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 20,569.7 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 100Log 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 186th of 237 · native score 19.46 · reference year 2050
22percentileHow is this calculated?
- Metric
- Population change (projection)
- Scale
- 100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
- Raw value
- -7.1 % change 2024→2050
- Native score
- 19.46 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 22th percentile — ranks 186th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-7.1 − -32.9) / (99.7 − -32.9) = 19.46Min 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 175th of 211 · native score 17.3 · reference year 2024
17percentileHow is this calculated?
- Metric
- Refugees (by origin)
- Scale
- 100 = most refugees produced, 0 = fewest — descriptive, not better or worse
- Raw value
- 15 refugees
- Native score
- 17.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 17th percentile — ranks 175th of 211. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 15 among 211 countries = 17.3The 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 160th of 193 · native score 0.56 · reference year 2024
17percentileHow is this calculated?
- Metric
- Remittances received
- Scale
- 100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 0.2742 % of GDP
- Native score
- 0.56 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 17th percentile — ranks 160th of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.27 − 0.01) / (47.15 − 0.01) = 0.56Min and max are this dataset's lowest (0.01) and highest (47.15) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fully rural, 0 = fully urban — descriptive, not better or worse
Ranks 204th of 215 · native score 0 · reference year 2025
3percentileHow is this calculated?
- Metric
- Rural population share
- Scale
- 100 = fully rural, 0 = fully urban — descriptive, not better or worse
- Raw value
- 0 % rural
- Native score
- 0 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 3th percentile — ranks 204th of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0 − 0) / (100 − 0) = 0The 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 8th of 215 · native score 44.74 · reference year 2024
97percentileHow 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
- 1.079 male births per female birth
- Native score
- 44.74 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 8th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.08 − 1.01) / (1.16 − 1.01) = 44.74Min 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 1st of 215 · native score 100 · reference year 2025
97percentileHow is this calculated?
- Metric
- Urbanization
- Scale
- 100 = fully urban, 0 = fully rural — descriptive, not better or worse
- Raw value
- 100 % urban
- Native score
- 100 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 1st of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (100 − 0) / (100 − 0) = 100The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 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 82nd of 177 · native score 53.95 · reference year 2023
54percentileHow is this calculated?
- Metric
- Air transport passengers
- Scale
- 100 = most air passengers, 0 = fewest — descriptive, not better or worse
- Raw value
- 2,053,176 passengers per year
- Native score
- 53.95 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 54th percentile — ranks 82nd of 177. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 2,053,176 among 177 countries = 53.95The 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.
- CO₂ emissions per capitaTier A
100 = lowest emissions per capita (best), 0 = highest
Ranks 70th of 214 · native score 67.52 · reference year 2024
68percentileHow is this calculated?
- Metric
- CO₂ emissions per capita
- Scale
- 100 = lowest emissions per capita (best), 0 = highest
- Raw value
- 1.46657 tonnes CO₂ per capita
- Native score
- 67.52 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 68th percentile — ranks 70th of 214. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 1.47 among 214 countries ] = 67.52The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- Global Carbon Project (via Our World in Data) · Global Carbon Project
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita CO₂ emissions from the Global Carbon Project's Global Carbon Budget, retrieved via the Our World in Data mirror.
- Access to electricityTier A
100 = universal electricity access, 0 = none
Ranks 1st of 214 · native score 100 · reference year 2023
70percentileHow is this calculated?
- Metric
- Access to electricity
- Scale
- 100 = universal electricity access, 0 = none
- Raw value
- 100 % of population
- Native score
- 100 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 1st of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (100 − 0) / (100 − 0) = 100The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most fixed-broadband subscriptions per capita, 0 = fewest
Ranks 59th of 208 · native score 48.96 · reference year 2024
72percentileHow is this calculated?
- Metric
- Fixed broadband subscriptions
- Scale
- 100 = most fixed-broadband subscriptions per capita, 0 = fewest
- Raw value
- 29.8554 per 100 people
- Native score
- 48.96 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 72th percentile — ranks 59th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (29.86 − 0) / (60.97 − 0) = 48.96Min and max are this dataset's lowest (0) and highest (60.97) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Internet usersTier A
100 = whole population online, 0 = none
Ranks 60th of 209 · native score 89.83 · reference year 2024
71percentileHow is this calculated?
- Metric
- Internet users
- Scale
- 100 = whole population online, 0 = none
- Raw value
- 89.8264 % of population
- Native score
- 89.83 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 71th percentile — ranks 60th of 209. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (89.83 − 0) / (100 − 0) = 89.83The 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.
- Renewable energy shareTier A
100 = all energy renewable, 0 = none
Ranks 141st of 212 · native score 11 · reference year 2022
34percentileHow is this calculated?
- Metric
- Renewable energy share
- Scale
- 100 = all energy renewable, 0 = none
- Raw value
- 11 % of final energy
- Native score
- 11 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 34th percentile — ranks 141st of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (11 − 0) / (100 − 0) = 11The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Society & culture
100 = highest cocoa supply per person in the dataset, 0 = lowest
Ranks 52nd of 191 · native score 12.15 · reference year 2023
73percentileLow reliability (Tier C — Survey / proxy). Survey-based, patchy, or proxy metric. Indicative only — coverage gaps and methodology limits are significant. Not a definitive ranking.
How is this calculated?
- Metric
- Chocolate supply per person (proxy)
- Scale
- 100 = highest cocoa supply per person in the dataset, 0 = lowest
- Raw value
- 1.70999 kg cocoa per person / year
- Native score
- 12.15 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 73th percentile — ranks 52nd of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.71 − 0) / (14.07 − 0) = 12.15Min 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 28th of 186 · native score 74.68 · reference year 2025
85percentileHow is this calculated?
- Metric
- Female labour force participation
- Scale
- 100 = highest female participation in the dataset, 0 = lowest
- Raw value
- 63.098 % of women 15+
- Native score
- 74.68 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 85th percentile — ranks 28th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (63.1 − 4.66) / (82.91 − 4.66) = 74.68Min 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 5th of 191 · native score 72.8 · reference year 2023
98percentileHow 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
- 61.1195 kg per person per year
- Native score
- 72.8 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 98th percentile — ranks 5th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (61.12 − 0.38) / (83.81 − 0.38) = 72.8Min 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 125th of 191 · native score 11.79 · reference year 2023
35percentileHow is this calculated?
- Metric
- Fruit supply per capita
- Scale
- 100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 66.1595 kg per person per year
- Native score
- 11.79 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 35th percentile — ranks 125th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (66.16 − 4.27) / (529.06 − 4.27) = 11.79Min 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 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
Ranks 5th of 191 · native score 76.73 · reference year 2023
98percentileHow is this calculated?
- Metric
- Meat supply per capita
- Scale
- 100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 121.229 kg per person per year
- Native score
- 76.73 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 98th percentile — ranks 5th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (121.23 − 3.49) / (156.93 − 3.49) = 76.73Min 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 70th of 214 · native score 75.3 · reference year 2022
67percentileHow is this calculated?
- Metric
- Social protection coverage
- Scale
- 100 = universal social protection coverage, 0 = none
- Raw value
- 75.3 % of population
- Native score
- 75.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 67th percentile — ranks 70th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (75.3 − 0) / (100 − 0) = 75.3The index is kept on its own published scale.
- Source
- ILOSTAT (International Labour Organization) · International Labour Organization
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- ILOSTAT via the ILO rplumber API (rplumber.ilo.org). CC BY 4.0 for databases published since 3 May 2023.
- Social tolerance (proxy)Tier C
100 = most accepting (fewest object to different-religion neighbours), 0 = least
Ranks 88th of 94 · native score 56.99 · reference year 2022
7percentileLow reliability (Tier C — Survey / proxy). Survey-based, patchy, or proxy metric. Indicative only — coverage gaps and methodology limits are significant. Not a definitive ranking.
How is this calculated?
- Metric
- Social tolerance (proxy)
- Scale
- 100 = most accepting (fewest object to different-religion neighbours), 0 = least
- Raw value
- 43.0108 % who object to different-religion neighbours
- Native score
- 56.99 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 7th percentile — ranks 88th of 94. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 − [ 100 · (43.01 − 0) / (100 − 0) ] = 56.99The index is kept on its own published scale. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Values Survey (via Our World in Data) · World Values Survey Association / Integrated Values Surveys
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier C — Survey / proxy
- Source notes
- Share of survey respondents who mention 'people of a different religion' when asked which groups they would not want as neighbours (World Values Survey / Integrated Values Surveys), via the Our World in Data mirror. A single attitudinal proxy — Tier C.
100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
Ranks 19th of 174 · native score 84.32 · reference year 2019
89percentileHow is this calculated?
- Metric
- International tourist arrivals
- Scale
- 100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
- Raw value
- 18,633,000 arrivals per year
- Native score
- 84.32 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 89th percentile — ranks 19th of 174. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 18,633,000 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 84.32Log scale (values are heavily skewed). 0 and 100 are the dataset's min (3,700) and max (90,914,000) — relative, not absolute or year-over-year comparable.
- Source
- UN Tourism (via Our World in Data) · UN Tourism (UNWTO)
- License
- CC BY 4.0
- Reference year
- 2019
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- International tourist arrivals — overnight visitors — from UN Tourism (UNWTO), retrieved via the Our World in Data mirror (OWID's processing layer is CC BY; underlying values are UN Tourism).
100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
Ranks 58th of 191 · native score 31.94 · reference year 2023
70percentileHow is this calculated?
- Metric
- Vegetable supply per capita
- Scale
- 100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 135.459 kg per person per year
- Native score
- 31.94 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 58th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (135.46 − 5.34) / (412.72 − 5.34) = 31.94Min 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.
Health
- Diabetes prevalenceTier A
100 = lowest diabetes prevalence (best), 0 = highest
Ranks 96th of 208 · native score 77.93 · reference year 2024
53percentileHow is this calculated?
- Metric
- Diabetes prevalence
- Scale
- 100 = lowest diabetes prevalence (best), 0 = highest
- Raw value
- 8.1 % of adults 20–79
- Native score
- 77.93 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 53th percentile — ranks 96th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (8.1 − 1.5) / (31.4 − 1.5) ] = 77.93Min and max are this dataset's lowest (1.5) and highest (31.4) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Life expectancy at birthTier A
100 = longest life expectancy in the dataset, 0 = shortest
Ranks 16th of 215 · native score 90.07 · reference year 2024
93percentileHow is this calculated?
- Metric
- Life expectancy at birth
- Scale
- 100 = longest life expectancy in the dataset, 0 = shortest
- Raw value
- 83.3317 years
- Native score
- 90.07 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 93th percentile — ranks 16th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (83.33 − 54.64) / (86.5 − 54.64) = 90.07Min and max are this dataset's lowest (54.64) and highest (86.5) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Safe sanitationTier A
100 = universal safe sanitation, 0 = none
Ranks 50th of 145 · native score 79.96 · reference year 2024
66percentileHow is this calculated?
- Metric
- Safe sanitation
- Scale
- 100 = universal safe sanitation, 0 = none
- Raw value
- 79.9557 % of population
- Native score
- 79.96 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 66th percentile — ranks 50th of 145. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (79.96 − 0) / (100 − 0) = 79.96The 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 1st of 151 · native score 100 · reference year 2024
96percentileHow is this calculated?
- Metric
- Safe drinking water
- Scale
- 100 = universal safe drinking water, 0 = none
- Raw value
- 100 % of population
- Native score
- 100 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 96th percentile — ranks 1st of 151. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (100 − 0) / (100 − 0) = 100The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- UndernourishmentTier A
100 = lowest undernourishment (best), 0 = highest
Ranks 116th of 169 · native score 83.17 · reference year 2023
31percentileHow is this calculated?
- Metric
- Undernourishment
- Scale
- 100 = lowest undernourishment (best), 0 = highest
- Raw value
- 11.2 % of population
- Native score
- 83.17 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 31th percentile — ranks 116th of 169. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (11.2 − 2.5) / (54.2 − 2.5) ] = 83.17Min 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.
Economy
100 = highest employment ratio in the dataset, 0 = lowest
Ranks 30th of 186 · native score 68.57 · reference year 2025
84percentileHow is this calculated?
- Metric
- Employment-to-population ratio
- Scale
- 100 = highest employment ratio in the dataset, 0 = lowest
- Raw value
- 66.255 % of population 15+
- Native score
- 68.57 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 84th percentile — ranks 30th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (66.26 − 21.21) / (86.9 − 21.21) = 68.57Min 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 12th of 192 · native score 45.9 · reference year 2025
94percentileHow is this calculated?
- Metric
- Exports of goods & services
- Scale
- 100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 92.2861 % of GDP
- Native score
- 45.9 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 94th percentile — ranks 12th of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (92.29 − 1.1) / (199.76 − 1.1) = 45.9Min 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.
100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 61st of 201 · native score 88.72 · reference year 2024
69percentileHow is this calculated?
- Metric
- Foreign direct investment
- Scale
- 100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 3.82364 % of GDP (net inflows)
- Native score
- 88.72 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 69th percentile — ranks 61st of 201. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.82 − -1,303.11) / (170.05 − -1,303.11) = 88.72Min 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 90th of 189 · native score 17.51 · reference year 2031
52percentileHow is this calculated?
- Metric
- GDP growth (projection)
- Scale
- 100 = highest projected growth, 0 = lowest
- Raw value
- 3.03 % per year (avg 2026–2031)
- Native score
- 17.51 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 52th percentile — ranks 90th of 189. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.03 − 0.62) / (14.38 − 0.62) = 17.51Min 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 4th of 202 · native score 95.81 · reference year 2024
98percentileHow is this calculated?
- Metric
- GDP per capita (PPP)
- Scale
- 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
- Raw value
- 126,960 international $ (PPP, current)
- Native score
- 95.81 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 98th percentile — ranks 4th of 202. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 126,959.92 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 95.81Log scale (values are heavily skewed). 0 and 100 are the dataset's min (1,154.89) and max (155,941.29) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 38th of 155 · native score 25.56 · reference year 2024
76percentileHow is this calculated?
- Metric
- Government revenue
- Scale
- 100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 31.7892 % of GDP
- Native score
- 25.56 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 38th of 155. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (31.79 − 3.03) / (115.55 − 3.03) = 25.56Min and max are this dataset's lowest (3.03) and highest (115.55) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 3rd of 177 · native score 87.78 · reference year 2024
99percentileHow is this calculated?
- Metric
- Gross savings
- Scale
- 100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 47.8185 % of GDP
- Native score
- 87.78 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 99th percentile — ranks 3rd of 177. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (47.82 − -21.13) / (57.42 − -21.13) = 87.78Min 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.
100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
Ranks 170th of 192 · native score 11.72 · reference year 2025
12percentileHow is this calculated?
- Metric
- Inflation rate
- Scale
- 100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
- Raw value
- 0.333312 % annual change (CPI)
- Native score
- 11.72 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 12th percentile — ranks 170th of 192. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 0.33 among 192 countries = 11.72The score is the country's position in the distribution.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Labour productivityTier A
100 = highest output per worker, 0 = lowest
Ranks 5th of 177 · native score 93.48 · reference year 2024
97percentileHow is this calculated?
- Metric
- Labour productivity
- Scale
- 100 = highest output per worker, 0 = lowest
- Raw value
- 194,417 constant PPP$ per worker
- Native score
- 93.48 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 97th percentile — ranks 5th of 177. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 194,417.4 − ln 2,444.23) / (ln 263,863.91 − ln 2,444.23) = 93.48Log scale (values are heavily skewed). 0 and 100 are the dataset's min (2,444.23) and max (263,863.91) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
Ranks 193rd of 193 · native score 0 · reference year 2025
0percentileHow is this calculated?
- Metric
- Government debt
- Scale
- 100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
- Raw value
- 0 % of GDP
- Native score
- 0 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 0th percentile — ranks 193rd of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0 − 0) / (308.7 − 0) = 0Min 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 23rd of 186 · native score 93.49 · reference year 2025
88percentileHow is this calculated?
- Metric
- Unemployment rate
- Scale
- 100 = lowest unemployment in the dataset, 0 = highest
- Raw value
- 2.347 % of labour force
- Native score
- 93.49 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 88th percentile — ranks 23rd of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (2.35 − 0.13) / (34.2 − 0.13) ] = 93.49Min 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 40th of 186 · native score 91.72 · reference year 2025
79percentileHow is this calculated?
- Metric
- Youth unemployment rate
- Scale
- 100 = lowest youth unemployment (best), 0 = highest
- Raw value
- 6.779 % of labour force 15–24
- Native score
- 91.72 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 79th percentile — ranks 40th of 186. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (6.78 − 0.46) / (76.77 − 0.46) ] = 91.72Min 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.
Governance & institutions
- Government effectivenessTier A
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Ranks 36th of 204 · native score 72.32 · reference year 2024
83percentileHow is this calculated?
- Metric
- Government effectiveness
- Scale
- 100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
- Raw value
- 1.11593 index (−2.5 to +2.5)
- Native score
- 72.32 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 83th percentile — ranks 36th of 204. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (1.12 − -2.5) / (2.5 − -2.5) = 72.32The 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.
Safety & crime
- Homicide rateTier A
100 = safest (fewest homicides), 0 = most homicides
Ranks 15th of 193 · native score 92.49 · reference year 2023
92percentileHow is this calculated?
- Metric
- Homicide rate
- Scale
- 100 = safest (fewest homicides), 0 = most homicides
- Raw value
- 0.560294 per 100,000 population
- Native score
- 92.49 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 92th percentile — ranks 15th of 193. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 0.56 among 193 countries ] = 92.49The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- UNODC (via World Bank) · UN Office on Drugs and Crime / World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Intentional homicide victims per 100,000, indicator VC.IHR.PSRC.P5, retrieved via the World Bank API. Primary source is UNODC; the World Bank redistributes the series under CC BY 4.0.