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Singapore

SGP

South-Eastern 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?”.

76 metrics for this country

Education

  • 100 = highest adult literacy in the dataset, 0 = lowest

    Ranks 45th of 155 · native score 96.79 · reference year 2021

    71percentile
    How is this calculated?
    Metric
    Adult literacy rate
    Scale
    100 = highest adult literacy in the dataset, 0 = lowest
    Raw value
    97.65 % of adults
    Native score
    96.79 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    71th percentile — ranks 45th of 155. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (97.65 − 26.83) / (100 − 26.83) = 96.79

    Min and max are this dataset's lowest (26.83) and highest (100) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2021
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = highest education spending (% GDP) in the dataset, 0 = lowest

    Ranks 176th of 200 · native score 13.37 · reference year 2024

    12percentile
    How is this calculated?
    Metric
    Government education spending
    Scale
    100 = highest education spending (% GDP) in the dataset, 0 = lowest
    Raw value
    2.191 % of GDP
    Native score
    13.37 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    12th percentile — ranks 176th of 200. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (2.19 − 0) / (16.39 − 0) = 13.37

    Min and max are this dataset's lowest (0) and highest (16.39) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = most years of schooling in the dataset, 0 = fewest

    Ranks 7th of 146 · native score 93.64 · reference year 2020

    96percentile
    How is this calculated?
    Metric
    Mean years of schooling
    Scale
    100 = most years of schooling in the dataset, 0 = fewest
    Raw value
    13.06 years
    Native score
    93.64 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    96th percentile — ranks 7th of 146. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (13.06 − 3.04) / (13.74 − 3.04) = 93.64

    Min 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 60th of 197 · native score 89.85 · reference year 2017

    70percentile
    How is this calculated?
    Metric
    Pupil–teacher ratio (primary)
    Scale
    100 = lowest pupil–teacher ratio (best), 0 = highest
    Raw value
    14.6943 pupils per teacher
    Native score
    89.85 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    70th percentile — ranks 60th of 197. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (14.69 − 6.93) / (83.41 − 6.93) ] = 89.85

    Min and max are this dataset's lowest (6.93) and highest (83.41) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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 = most researchers per capita, 0 = fewest

    Ranks 5th of 144 · native score 92.32 · reference year 2022

    97percentile
    How is this calculated?
    Metric
    Researchers in R&D
    Scale
    100 = most researchers per capita, 0 = fewest
    Raw value
    8,781.74 per million people
    Native score
    92.32 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    97th percentile — ranks 5th of 144. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 8,781.74 − ln 1.45) / (ln 18,129.75 − ln 1.45) = 92.32

    Log 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
    2022
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = highest completion in the dataset, 0 = lowest

    Ranks 18th of 192 · native score 66.59 · reference year 2023

    91percentile
    How is this calculated?
    Metric
    Lower-secondary completion rate
    Scale
    100 = highest completion in the dataset, 0 = lowest
    Raw value
    101.577 % of relevant age group
    Native score
    66.59 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    91th percentile — ranks 18th of 192. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (101.58 − 8.89) / (148.09 − 8.89) = 66.59

    Min and max are this dataset's lowest (8.89) and highest (148.09) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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 12th of 195 · native score 58.46 · reference year 2023

    94percentile
    How is this calculated?
    Metric
    Tertiary enrollment ratio
    Scale
    100 = highest tertiary enrollment in the dataset, 0 = lowest
    Raw value
    97.2887 % gross enrollment
    Native score
    58.46 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    94th percentile — ranks 12th of 195. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (97.29 − 1.84) / (165.11 − 1.84) = 58.46

    Min and max are this dataset's lowest (1.84) and highest (165.11) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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.

Society & culture

  • Adult male heightTier ADescriptive

    100 = tallest mean male height, 0 = shortest — descriptive, not better or worse

    Ranks 84th of 200 · native score 56.17 · reference year 1996

    58percentile
    How is this calculated?
    Metric
    Adult male height
    Scale
    100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
    Raw value
    172.566 cm
    Native score
    56.17 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    58th percentile — ranks 84th of 200. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (172.57 − 159.79) / (182.54 − 159.79) = 56.17

    Min and max are this dataset's lowest (159.79) and highest (182.54) values, so the score is relative to the current country set.

    Source
    NCD Risk Factor Collaboration (via Our World in Data) · NCD Risk Factor Collaboration (NCD-RisC)
    License
    CC BY 4.0
    Reference year
    1996
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Pooled analysis of population-based measured-height studies, retrieved via the Our World in Data mirror. Indexed by year of birth.
  • 100 = highest female participation in the dataset, 0 = lowest

    Ranks 27th of 186 · native score 75.28 · reference year 2025

    86percentile
    How is this calculated?
    Metric
    Female labour force participation
    Scale
    100 = highest female participation in the dataset, 0 = lowest
    Raw value
    63.569 % of women 15+
    Native score
    75.28 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    86th percentile — ranks 27th of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (63.57 − 4.66) / (82.91 − 4.66) = 75.28

    Min 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 = most gender-equal (GII 0), 0 = most unequal (GII 1)

    Ranks 8th of 172 · native score 96.9 · reference year 2023

    95percentile
    How is this calculated?
    Metric
    Gender equality (inverted GII)
    Scale
    100 = most gender-equal (GII 0), 0 = most unequal (GII 1)
    Raw value
    0.031 index (0–1, lower = more equal)
    Native score
    96.9 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    95th percentile — ranks 8th of 172. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 − [ 100 · (0.03 − 0) / (1 − 0) ] = 96.9

    The 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.
  • 100 = universal social protection coverage, 0 = none

    Ranks 1st of 214 · native score 100 · reference year 2023

    95percentile
    How is this calculated?
    Metric
    Social protection coverage
    Scale
    100 = universal social protection coverage, 0 = none
    Raw value
    100 % of population
    Native score
    100 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    95th percentile — ranks 1st of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (100 − 0) / (100 − 0) = 100

    The index is kept on its own published scale.

    Source
    ILOSTAT (International Labour Organization) · International Labour Organization
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    ILOSTAT via the ILO rplumber API (rplumber.ilo.org). CC BY 4.0 for databases published since 3 May 2023.
  • 100 = most accepting (fewest object to different-religion neighbours), 0 = least

    Ranks 4th of 94 · native score 97.95 · reference year 2022

    96percentile

    Low reliability (Tier C — Survey / proxy). Survey-based, patchy, or proxy metric. Indicative only — coverage gaps and methodology limits are significant. Not a definitive ranking.

    How is this calculated?
    Metric
    Social tolerance (proxy)
    Scale
    100 = most accepting (fewest object to different-religion neighbours), 0 = least
    Raw value
    2.0476 % who object to different-religion neighbours
    Native score
    97.95 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    96th percentile — ranks 4th of 94. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 − [ 100 · (2.05 − 0) / (100 − 0) ] = 97.95

    The 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 26th of 174 · native score 82.25 · reference year 2019

    85percentile
    How is this calculated?
    Metric
    International tourist arrivals
    Scale
    100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
    Raw value
    15,119,000 arrivals per year
    Native score
    82.25 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    85th percentile — ranks 26th of 174. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 15,119,000 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 82.25

    Log scale (values are heavily skewed). 0 and 100 are the dataset's min (3,700) and max (90,914,000) — relative, not absolute or year-over-year comparable.

    Source
    UN Tourism (via Our World in Data) · UN Tourism (UNWTO)
    License
    CC BY 4.0
    Reference year
    2019
    Retrieved
    2026-07-12
    Confidence
    Tier B — Reputable / modeled
    Source notes
    International tourist arrivals — overnight visitors — from UN Tourism (UNWTO), retrieved via the Our World in Data mirror (OWID's processing layer is CC BY; underlying values are UN Tourism).
  • Trade union densityTier BDescriptive

    100 = highest union density in the dataset, 0 = lowest — descriptive, not better or worse

    Ranks 48th of 139 · native score 24.1 · reference year 2019

    66percentile
    How is this calculated?
    Metric
    Trade union density
    Scale
    100 = highest union density in the dataset, 0 = lowest — descriptive, not better or worse
    Raw value
    22.181 % of employees
    Native score
    24.1 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    66th percentile — ranks 48th of 139. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (22.18 − 0.2) / (91.42 − 0.2) = 24.1

    Min 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.

Demographics & migration

  • Age dependency ratioTier ADescriptive

    100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse

    Ranks 208th of 215 · native score 17.84 · reference year 2025

    3percentile
    How is this calculated?
    Metric
    Age dependency ratio
    Scale
    100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
    Raw value
    34.9531 dependents per 100 working-age
    Native score
    17.84 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    3th percentile — ranks 208th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (34.95 − 20.05) / (103.59 − 20.05) = 17.84

    Min and max are this dataset's lowest (20.05) and highest (103.59) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • Fertility rateTier ADescriptive

    100 = highest fertility, 0 = lowest — descriptive, not better or worse

    Ranks 211th of 215 · native score 7.12 · reference year 2024

    2percentile
    How is this calculated?
    Metric
    Fertility rate
    Scale
    100 = highest fertility, 0 = lowest — descriptive, not better or worse
    Raw value
    0.97 births per woman
    Native score
    7.12 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    2th percentile — ranks 211th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.97 − 0.58) / (6.03 − 0.58) = 7.12

    Min and max are this dataset's lowest (0.58) and highest (6.03) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse

    Ranks 138th of 215 · native score 38.81 · reference year 2024

    36percentile
    How is this calculated?
    Metric
    Life expectancy gap (female − male)
    Scale
    100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
    Raw value
    4.4 years (female − male)
    Native score
    38.81 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    36th percentile — ranks 138th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (4.4 − 0.46) / (10.62 − 0.46) = 38.81

    Min and max are this dataset's lowest (0.46) and highest (10.62) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • Median ageTier ADescriptive

    100 = oldest median age, 0 = youngest — descriptive, not better or worse

    Ranks 98th of 237 · native score 45.87 · reference year 2023

    59percentile
    How is this calculated?
    Metric
    Median age
    Scale
    100 = oldest median age, 0 = youngest — descriptive, not better or worse
    Raw value
    35.102 years
    Native score
    45.87 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    59th percentile — ranks 98th of 237. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (35.1 − 14.32) / (59.63 − 14.32) = 45.87

    Min and max are this dataset's lowest (14.32) and highest (59.63) values, so the score is relative to the current country set.

    Source
    UN World Population Prospects (via Our World in Data) · UN DESA, Population Division
    License
    CC BY 3.0 IGO
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    UN World Population Prospects (median age; medium-variant projections), retrieved via the Our World in Data mirror.
  • Foreign-born populationTier ADescriptive

    100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse

    Ranks 19th of 214 · native score 48.7 · reference year 2024

    91percentile
    How is this calculated?
    Metric
    Foreign-born population
    Scale
    100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
    Raw value
    48.7 % foreign-born
    Native score
    48.7 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    91th percentile — ranks 19th of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (48.7 − 0) / (100 − 0) = 48.7

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • Net migration rateTier BDescriptive

    100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse

    Ranks 38th of 215 · native score 54.84 · reference year 2025

    83percentile
    How is this calculated?
    Metric
    Net migration rate
    Scale
    100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse
    Raw value
    2.764 per 1,000 people
    Native score
    54.84 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    83th percentile — ranks 38th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (2.76 − -46.91) / (43.67 − -46.91) = 54.84

    Min and max are this dataset's lowest (-46.91) and highest (43.67) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier B — Reputable / modeled
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • Total populationTier ADescriptive

    100 = most populous, 0 = least populous — descriptive, not better or worse

    Ranks 113th of 215 · native score 54.14 · reference year 2025

    48percentile
    How is this calculated?
    Metric
    Total population
    Scale
    100 = most populous, 0 = least populous — descriptive, not better or worse
    Raw value
    6,111,175 people
    Native score
    54.14 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    48th percentile — ranks 113th of 215. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 6,111,175 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 54.14

    Log scale (values are heavily skewed). 0 and 100 are the dataset's min (9,492) and max (1,463,865,525) — relative, not absolute or year-over-year comparable.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • Population densityTier ADescriptive

    100 = most dense, 0 = least dense — descriptive, not better or worse

    Ranks 3rd of 215 · native score 92.32 · reference year 2023

    99percentile
    How is this calculated?
    Metric
    Population density
    Scale
    100 = most dense, 0 = least dense — descriptive, not better or worse
    Raw value
    8,241.85 people per km²
    Native score
    92.32 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    99th percentile — ranks 3rd of 215. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 8,241.85 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 92.32

    Log scale (values are heavily skewed). 0 and 100 are the dataset's min (0.14) and max (20,569.7) — relative, not absolute or year-over-year comparable.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse

    Ranks 149th of 237 · native score 28.05 · reference year 2050

    37percentile
    How is this calculated?
    Metric
    Population change (projection)
    Scale
    100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
    Raw value
    4.3 % change 2024→2050
    Native score
    28.05 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    37th percentile — ranks 149th of 237. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (4.3 − -32.9) / (99.7 − -32.9) = 28.05

    Min and max are this dataset's lowest (-32.9) and highest (99.7) values, so the score is relative to the current country set.

    Source
    UN World Population Prospects (via Our World in Data) · UN DESA, Population Division
    License
    CC BY 3.0 IGO
    Reference year
    2050
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    UN World Population Prospects (median age; medium-variant projections), retrieved via the Our World in Data mirror.
  • Refugees (by origin)Tier ADescriptive

    100 = most refugees produced, 0 = fewest — descriptive, not better or worse

    Ranks 163rd of 211 · native score 22.99 · reference year 2024

    23percentile
    How is this calculated?
    Metric
    Refugees (by origin)
    Scale
    100 = most refugees produced, 0 = fewest — descriptive, not better or worse
    Raw value
    45 refugees
    Native score
    22.99 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    23th percentile — ranks 163rd of 211. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = percentile rank of 45 among 211 countries = 22.99

    The score is the country's position in the distribution.

    Source
    UNHCR (via Our World in Data) · UN High Commissioner for Refugees (UNHCR)
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Refugee population by country of origin, retrieved via the Our World in Data mirror.
  • Rural population shareTier ADescriptive

    100 = fully rural, 0 = fully urban — descriptive, not better or worse

    Ranks 204th of 215 · native score 0 · reference year 2025

    3percentile
    How 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) = 0

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • Sex ratio at birthTier ADescriptive

    100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse

    Ranks 55th of 215 · native score 32.24 · reference year 2024

    73percentile
    How is this calculated?
    Metric
    Sex ratio at birth
    Scale
    100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse
    Raw value
    1.06 male births per female birth
    Native score
    32.24 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    73th percentile — ranks 55th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (1.06 − 1.01) / (1.16 − 1.01) = 32.24

    Min and max are this dataset's lowest (1.01) and highest (1.16) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • UrbanizationTier ADescriptive

    100 = fully urban, 0 = fully rural — descriptive, not better or worse

    Ranks 1st of 215 · native score 100 · reference year 2025

    97percentile
    How 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) = 100

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.

Environment & infrastructure

  • Air transport passengersTier ADescriptive

    100 = most air passengers, 0 = fewest — descriptive, not better or worse

    Ranks 23rd of 177 · native score 87.29 · reference year 2023

    87percentile
    How is this calculated?
    Metric
    Air transport passengers
    Scale
    100 = most air passengers, 0 = fewest — descriptive, not better or worse
    Raw value
    47,502,800 passengers per year
    Native score
    87.29 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    87th percentile — ranks 23rd of 177. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = percentile rank of 47,502,833.59 among 177 countries = 87.29

    The score is the country's position in the distribution.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = least climate-vulnerable (best), 0 = most vulnerable

    Ranks 45th of 190 · native score 70.38 · reference year 2024

    77percentile
    How is this calculated?
    Metric
    Climate vulnerability
    Scale
    100 = least climate-vulnerable (best), 0 = most vulnerable
    Raw value
    0.379491 index (0–1, higher = more vulnerable)
    Native score
    70.38 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    77th percentile — ranks 45th of 190. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (0.38 − 0.26) / (0.66 − 0.26) ] = 70.38

    Min and max are this dataset's lowest (0.26) and highest (0.66) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    ND-GAIN Country Index (University of Notre Dame) · University of Notre Dame Global Adaptation Initiative
    License
    CC BY 3.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier B — Reputable / modeled
    Source notes
    ND-GAIN vulnerability score. The source ZIP is version-stamped (no stable 'latest' URL), so the snapshot is pinned to a specific release; refreshes are a manual, documented step.
  • 100 = lowest emissions per capita (best), 0 = highest

    Ranks 187th of 214 · native score 12.85 · reference year 2024

    13percentile
    How is this calculated?
    Metric
    CO₂ emissions per capita
    Scale
    100 = lowest emissions per capita (best), 0 = highest
    Raw value
    9.24484 tonnes CO₂ per capita
    Native score
    12.85 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    13th percentile — ranks 187th of 214. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 9.24 among 214 countries ] = 12.85

    The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    Global Carbon Project (via Our World in Data) · Global Carbon Project
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Per-capita CO₂ emissions from the Global Carbon Project's Global Carbon Budget, retrieved via the Our World in Data mirror.
  • 100 = universal electricity access, 0 = none

    Ranks 1st of 214 · native score 100 · reference year 2023

    70percentile
    How is this calculated?
    Metric
    Access to electricity
    Scale
    100 = universal electricity access, 0 = none
    Raw value
    100 % of population
    Native score
    100 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    70th percentile — ranks 1st of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (100 − 0) / (100 − 0) = 100

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = highest electricity use per capita, 0 = lowest — descriptive, not better or worse

    Ranks 16th of 149 · native score 80.27 · reference year 2023

    90percentile
    How is this calculated?
    Metric
    Electricity use per capita
    Scale
    100 = highest electricity use per capita, 0 = lowest — descriptive, not better or worse
    Raw value
    9,750.5 kWh per capita
    Native score
    80.27 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    90th percentile — ranks 16th of 149. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 9,750.5 − ln 13.72) / (ln 48,997.95 − ln 13.72) = 80.27

    Log scale (values are heavily skewed). 0 and 100 are the dataset's min (13.72) and max (48,997.95) — 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.
  • Energy use per capitaTier ADescriptive

    100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse

    Ranks 15th of 177 · native score 84.79 · reference year 2023

    92percentile
    How is this calculated?
    Metric
    Energy use per capita
    Scale
    100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
    Raw value
    5,282.76 kg oil-equivalent per capita
    Native score
    84.79 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    92th percentile — ranks 15th of 177. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 5,282.76 − ln 9.73) / (ln 16,343.04 − ln 9.73) = 84.79

    Log scale (values are heavily skewed). 0 and 100 are the dataset's min (9.73) and max (16,343.04) — relative, not absolute or year-over-year comparable.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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 69th of 208 · native score 45.62 · reference year 2024

    67percentile
    How is this calculated?
    Metric
    Fixed broadband subscriptions
    Scale
    100 = most fixed-broadband subscriptions per capita, 0 = fewest
    Raw value
    27.8137 per 100 people
    Native score
    45.62 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    67th percentile — ranks 69th of 208. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (27.81 − 0) / (60.97 − 0) = 45.62

    Min and max are this dataset's lowest (0) and highest (60.97) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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.
  • Forest areaTier ADescriptive

    100 = most forested, 0 = least — descriptive, not better or worse

    Ranks 132nd of 213 · native score 20.93 · reference year 2023

    38percentile
    How is this calculated?
    Metric
    Forest area
    Scale
    100 = most forested, 0 = least — descriptive, not better or worse
    Raw value
    20.9331 % of land area
    Native score
    20.93 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    38th percentile — ranks 132nd of 213. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (20.93 − 0) / (100 − 0) = 20.93

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = whole population online, 0 = none

    Ranks 34th of 209 · native score 94.38 · reference year 2024

    84percentile
    How is this calculated?
    Metric
    Internet users
    Scale
    100 = whole population online, 0 = none
    Raw value
    94.3776 % of population
    Native score
    94.38 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    84th percentile — ranks 34th of 209. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (94.38 − 0) / (100 − 0) = 94.38

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = best logistics performance (index 5), 0 = worst (1)

    Ranks 1st of 169 · native score 82.5 · reference year 2022

    100percentile
    How is this calculated?
    Metric
    Logistics Performance Index
    Scale
    100 = best logistics performance (index 5), 0 = worst (1)
    Raw value
    4.3 index (1–5)
    Native score
    82.5 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    100th percentile — ranks 1st of 169. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (4.3 − 1) / (5 − 1) = 82.5

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2022
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = cleanest air (lowest PM2.5), 0 = most polluted

    Ranks 85th of 200 · native score 57.75 · reference year 2023

    58percentile
    How is this calculated?
    Metric
    PM2.5 air pollution
    Scale
    100 = cleanest air (lowest PM2.5), 0 = most polluted
    Raw value
    15.1427 µg/m³
    Native score
    57.75 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    58th percentile — ranks 85th of 200. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 15.14 among 200 countries ] = 57.75

    The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = most land protected, 0 = least

    Ranks 184th of 212 · native score 4.6 · reference year 2025

    13percentile
    How is this calculated?
    Metric
    Protected land area
    Scale
    100 = most land protected, 0 = least
    Raw value
    4.6 % of land area
    Native score
    4.6 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    13th percentile — ranks 184th of 212. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (4.6 − 0) / (100 − 0) = 4.6

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = all energy renewable, 0 = none

    Ranks 187th of 212 · native score 1.1 · reference year 2021

    11percentile
    How is this calculated?
    Metric
    Renewable energy share
    Scale
    100 = all energy renewable, 0 = none
    Raw value
    1.1 % of final energy
    Native score
    1.1 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    11th percentile — ranks 187th of 212. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (1.1 − 0) / (100 − 0) = 1.1

    The 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.

Economy

  • 100 = highest new-business density in the dataset, 0 = lowest

    Ranks 22nd of 182 · native score 5.76 · reference year 2024

    88percentile
    How is this calculated?
    Metric
    New business density
    Scale
    100 = highest new-business density in the dataset, 0 = lowest
    Raw value
    11.5927 new firms per 1,000 aged 15–64
    Native score
    5.76 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    88th percentile — ranks 22nd of 182. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (11.59 − 0.02) / (201.01 − 0.02) = 5.76

    Min and max are this dataset's lowest (0.02) and highest (201.01) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = highest employment ratio in the dataset, 0 = lowest

    Ranks 24th of 186 · native score 70.79 · reference year 2025

    87percentile
    How is this calculated?
    Metric
    Employment-to-population ratio
    Scale
    100 = highest employment ratio in the dataset, 0 = lowest
    Raw value
    67.709 % of population 15+
    Native score
    70.79 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    87th percentile — ranks 24th of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (67.71 − 21.21) / (86.9 − 21.21) = 70.79

    Min 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 4th of 192 · native score 88.97 · reference year 2025

    98percentile
    How is this calculated?
    Metric
    Exports of goods & services
    Scale
    100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    177.851 % of GDP
    Native score
    88.97 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    98th percentile — ranks 4th of 192. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (177.85 − 1.1) / (199.76 − 1.1) = 88.97

    Min and max are this dataset's lowest (1.1) and highest (199.76) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • Foreign direct investmentTier ADescriptive

    100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse

    Ranks 6th of 201 · native score 90.06 · reference year 2024

    97percentile
    How is this calculated?
    Metric
    Foreign direct investment
    Scale
    100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    23.5787 % of GDP (net inflows)
    Native score
    90.06 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    97th percentile — ranks 6th of 201. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (23.58 − -1,303.11) / (170.05 − -1,303.11) = 90.06

    Min and max are this dataset's lowest (-1,303.11) and highest (170.05) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = highest projected growth, 0 = lowest

    Ranks 109th of 189 · native score 15.12 · reference year 2031

    42percentile
    How is this calculated?
    Metric
    GDP growth (projection)
    Scale
    100 = highest projected growth, 0 = lowest
    Raw value
    2.7 % per year (avg 2026–2031)
    Native score
    15.12 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    42th percentile — ranks 109th of 189. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (2.7 − 0.62) / (14.38 − 0.62) = 15.12

    Min and max are this dataset's lowest (0.62) and highest (14.38) values, so the score is relative to the current country set.

    Source
    IMF (World Economic Outlook) · International Monetary Fund
    License
    IMF terms (reuse with attribution)
    Reference year
    2031
    Retrieved
    2026-07-12
    Confidence
    Tier B — Reputable / modeled
    Source notes
    IMF World Economic Outlook via the IMF DataMapper API (imf.org/external/datamapper).
  • 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)

    Ranks 2nd of 202 · native score 99.3 · reference year 2024

    99percentile
    How is this calculated?
    Metric
    GDP per capita (PPP)
    Scale
    100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
    Raw value
    150,689 international $ (PPP, current)
    Native score
    99.3 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    99th percentile — ranks 2nd of 202. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 150,689.3 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 99.3

    Log scale (values are heavily skewed). 0 and 100 are the dataset's min (1,154.89) and max (155,941.29) — relative, not absolute or year-over-year comparable.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • Government revenueTier ADescriptive

    100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse

    Ranks 115th of 155 · native score 13.06 · reference year 2024

    26percentile
    How is this calculated?
    Metric
    Government revenue
    Scale
    100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    17.727 % of GDP
    Native score
    13.06 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    26th percentile — ranks 115th of 155. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (17.73 − 3.03) / (115.55 − 3.03) = 13.06

    Min and max are this dataset's lowest (3.03) and highest (115.55) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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.
  • Gross savingsTier ADescriptive

    100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse

    Ranks 9th of 177 · native score 77.79 · reference year 2025

    95percentile
    How is this calculated?
    Metric
    Gross savings
    Scale
    100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    39.9756 % of GDP
    Native score
    77.79 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    95th percentile — ranks 9th of 177. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (39.98 − -21.13) / (57.42 − -21.13) = 77.79

    Min and max are this dataset's lowest (-21.13) and highest (57.42) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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.
  • Inflation rateTier ADescriptive

    100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse

    Ranks 155th of 192 · native score 19.53 · reference year 2025

    20percentile
    How is this calculated?
    Metric
    Inflation rate
    Scale
    100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
    Raw value
    0.902998 % annual change (CPI)
    Native score
    19.53 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    20th percentile — ranks 155th of 192. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = percentile rank of 0.9 among 192 countries = 19.53

    The 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.
  • 100 = highest output per worker, 0 = lowest

    Ranks 3rd of 177 · native score 96.41 · reference year 2024

    99percentile
    How is this calculated?
    Metric
    Labour productivity
    Scale
    100 = highest output per worker, 0 = lowest
    Raw value
    223,022 constant PPP$ per worker
    Native score
    96.41 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    99th percentile — ranks 3rd of 177. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 223,022.29 − ln 2,444.23) / (ln 263,863.91 − ln 2,444.23) = 96.41

    Log 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.
  • Government debtTier BDescriptive

    100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse

    Ranks 5th of 193 · native score 55.49 · reference year 2025

    98percentile
    How is this calculated?
    Metric
    Government debt
    Scale
    100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
    Raw value
    171.3 % of GDP
    Native score
    55.49 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    98th percentile — ranks 5th of 193. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (171.3 − 0) / (308.7 − 0) = 55.49

    Min and max are this dataset's lowest (0) and highest (308.7) values, so the score is relative to the current country set.

    Source
    IMF (World Economic Outlook) · International Monetary Fund
    License
    IMF terms (reuse with attribution)
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier B — Reputable / modeled
    Source notes
    IMF World Economic Outlook via the IMF DataMapper API (imf.org/external/datamapper).
  • 100 = lowest unemployment in the dataset, 0 = highest

    Ranks 33rd of 186 · native score 92.11 · reference year 2025

    83percentile
    How is this calculated?
    Metric
    Unemployment rate
    Scale
    100 = lowest unemployment in the dataset, 0 = highest
    Raw value
    2.818 % of labour force
    Native score
    92.11 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    83th percentile — ranks 33rd of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (2.82 − 0.13) / (34.2 − 0.13) ] = 92.11

    Min 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.
  • 100 = lowest youth unemployment (best), 0 = highest

    Ranks 41st of 186 · native score 91.71 · reference year 2025

    78percentile
    How is this calculated?
    Metric
    Youth unemployment rate
    Scale
    100 = lowest youth unemployment (best), 0 = highest
    Raw value
    6.781 % of labour force 15–24
    Native score
    91.71 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    78th percentile — ranks 41st of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (6.78 − 0.46) / (76.77 − 0.46) ] = 91.71

    Min 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 1st of 197 · native score 63.71 · reference year 2025

    64percentile
    How is this calculated?
    Metric
    Deaths in armed conflicts
    Scale
    100 = fewest conflict deaths (most at peace), 0 = most
    Raw value
    0 deaths per year
    Native score
    63.71 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    64th percentile — ranks 1st of 197. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 0 among 197 countries ] = 63.71

    The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    Uppsala Conflict Data Program (via Our World in Data) · Uppsala Conflict Data Program (UCDP)
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Deaths in armed conflicts, best estimate, retrieved via the Our World in Data mirror.
  • 100 = safest (fewest homicides), 0 = most homicides

    Ranks 1st of 193 · native score 99.74 · reference year 2023

    100percentile
    How is this calculated?
    Metric
    Homicide rate
    Scale
    100 = safest (fewest homicides), 0 = most homicides
    Raw value
    0.0690955 per 100,000 population
    Native score
    99.74 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    100th percentile — ranks 1st of 193. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 0.07 among 193 countries ] = 99.74

    The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    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.
  • 100 = lowest road-death rate (best), 0 = highest

    Ranks 8th of 190 · native score 96.75 · reference year 2019

    96percentile
    How is this calculated?
    Metric
    Road-traffic deaths
    Scale
    100 = lowest road-death rate (best), 0 = highest
    Raw value
    2.1 deaths per 100,000
    Native score
    96.75 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    96th percentile — ranks 8th of 190. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (2.1 − 0) / (64.6 − 0) ] = 96.75

    Min and max are this dataset's lowest (0) and highest (64.6) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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 3rd of 180 · native score 84 · reference year 2024

    99percentile
    How is this calculated?
    Metric
    Corruption Perceptions Index
    Scale
    100 = cleanest (least corrupt), 0 = most corrupt
    Raw value
    84 CPI score (0–100)
    Native score
    84 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    99th percentile — ranks 3rd of 180. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (84 − 0) / (100 − 0) = 84

    The 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 96th of 175 · native score 43.4 · reference year 2025

    45percentile
    How is this calculated?
    Metric
    Electoral democracy index
    Scale
    100 = most democratic (index 1.0), 0 = least democratic
    Raw value
    0.434 index (0–1)
    Native score
    43.4 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    45th percentile — ranks 96th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.43 − 0) / (1 − 0) = 43.4

    The 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 134th of 175 · native score 40 · reference year 2025

    24percentile
    How is this calculated?
    Metric
    Freedom of expression index
    Scale
    100 = most free expression (index 1.0), 0 = least
    Raw value
    0.4 index (0–1)
    Native score
    40 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    24th percentile — ranks 134th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.4 − 0) / (1 − 0) = 40

    The 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 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)

    Ranks 1st of 204 · native score 95.59 · reference year 2024

    100percentile
    How is this calculated?
    Metric
    Government effectiveness
    Scale
    100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
    Raw value
    2.27963 index (−2.5 to +2.5)
    Native score
    95.59 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    100th percentile — ranks 1st of 204. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (2.28 − -2.5) / (2.5 − -2.5) = 95.59

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = strongest rule of law (index 1.0), 0 = weakest

    Ranks 14th of 175 · native score 97.4 · reference year 2025

    92percentile
    How is this calculated?
    Metric
    Rule of law index
    Scale
    100 = strongest rule of law (index 1.0), 0 = weakest
    Raw value
    0.974 index (0–1)
    Native score
    97.4 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    92th percentile — ranks 14th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.97 − 0) / (1 − 0) = 97.4

    The 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 = all seats held by women, 0 = none (≈50 = parity)

    Ranks 62nd of 193 · native score 32.32 · reference year 2025

    68percentile
    How is this calculated?
    Metric
    Women in parliament
    Scale
    100 = all seats held by women, 0 = none (≈50 = parity)
    Raw value
    32.3232 % of seats
    Native score
    32.32 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    68th percentile — ranks 62nd of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (32.32 − 0) / (100 − 0) = 32.32

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.

Health

  • 100 = lowest diabetes prevalence (best), 0 = highest

    Ranks 147th of 208 · native score 66.89 · reference year 2024

    29percentile
    How is this calculated?
    Metric
    Diabetes prevalence
    Scale
    100 = lowest diabetes prevalence (best), 0 = highest
    Raw value
    11.4 % of adults 20–79
    Native score
    66.89 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    29th percentile — ranks 147th of 208. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (11.4 − 1.5) / (31.4 − 1.5) ] = 66.89

    Min and max are this dataset's lowest (1.5) and highest (31.4) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = highest health spending per capita, 0 = lowest

    Ranks 23rd of 193 · native score 81.44 · reference year 2023

    88percentile
    How is this calculated?
    Metric
    Health expenditure per capita
    Scale
    100 = highest health spending per capita, 0 = lowest
    Raw value
    3,921.6 current US$ per capita
    Native score
    81.44 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    88th percentile — ranks 23rd of 193. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 3,921.6 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 81.44

    Log scale (values are heavily skewed). 0 and 100 are the dataset's min (17.44) and max (13,473.19) — relative, not absolute or year-over-year comparable.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = most hospital beds per capita in the dataset, 0 = fewest

    Ranks 73rd of 191 · native score 12.18 · reference year 2023

    62percentile
    How is this calculated?
    Metric
    Hospital beds per 1,000
    Scale
    100 = most hospital beds per capita in the dataset, 0 = fewest
    Raw value
    2.81 per 1,000 people
    Native score
    12.18 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    62th percentile — ranks 73rd of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (2.81 − 0.15) / (21.99 − 0.15) = 12.18

    Min and max are this dataset's lowest (0.15) and highest (21.99) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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 29th of 193 · native score 97 · reference year 2024

    81percentile
    How is this calculated?
    Metric
    Immunization coverage (DTP3)
    Scale
    100 = full DTP3 coverage, 0 = none
    Raw value
    97 % of children aged 12–23 months
    Native score
    97 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    81th percentile — ranks 29th of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (97 − 0) / (100 − 0) = 97

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = lowest infant mortality in the dataset, 0 = highest

    Ranks 13th of 195 · native score 98.59 · reference year 2024

    93percentile
    How is this calculated?
    Metric
    Infant mortality rate
    Scale
    100 = lowest infant mortality in the dataset, 0 = highest
    Raw value
    2.2 per 1,000 live births
    Native score
    98.59 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    93th percentile — ranks 13th of 195. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (2.2 − 1.2) / (71.9 − 1.2) ] = 98.59

    Min and max are this dataset's lowest (1.2) and highest (71.9) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = longest life expectancy in the dataset, 0 = shortest

    Ranks 15th of 215 · native score 90.11 · reference year 2024

    93percentile
    How is this calculated?
    Metric
    Life expectancy at birth
    Scale
    100 = longest life expectancy in the dataset, 0 = shortest
    Raw value
    83.3463 years
    Native score
    90.11 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    93th percentile — ranks 15th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (83.35 − 54.64) / (86.5 − 54.64) = 90.11

    Min and max are this dataset's lowest (54.64) and highest (86.5) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = lowest maternal mortality (best), 0 = highest

    Ranks 28th of 194 · native score 84.54 · reference year 2023

    85percentile
    How is this calculated?
    Metric
    Maternal mortality ratio
    Scale
    100 = lowest maternal mortality (best), 0 = highest
    Raw value
    6 deaths per 100,000 live births
    Native score
    84.54 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    85th percentile — ranks 28th of 194. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 6 among 194 countries ] = 84.54

    The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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 physicians per capita in the dataset, 0 = fewest

    Ranks 67th of 195 · native score 29.42 · reference year 2022

    66percentile
    How is this calculated?
    Metric
    Physicians per 1,000
    Scale
    100 = most physicians per capita in the dataset, 0 = fewest
    Raw value
    2.834 per 1,000 people
    Native score
    29.42 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    66th percentile — ranks 67th of 195. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (2.83 − 0.04) / (9.54 − 0.04) = 29.42

    Min and max are this dataset's lowest (0.04) and highest (9.54) values, so the score is relative to the current country set.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2022
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = universal safe sanitation, 0 = none

    Ranks 1st of 145 · native score 100 · reference year 2024

    98percentile
    How is this calculated?
    Metric
    Safe sanitation
    Scale
    100 = universal safe sanitation, 0 = none
    Raw value
    100 % of population
    Native score
    100 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    98th percentile — ranks 1st of 145. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (100 − 0) / (100 − 0) = 100

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    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 = universal safe drinking water, 0 = none

    Ranks 1st of 151 · native score 100 · reference year 2024

    96percentile
    How 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) = 100

    The index is kept on its own published scale.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = lowest tobacco use (best), 0 = highest

    Ranks 59th of 166 · native score 76.59 · reference year 2024

    65percentile
    How is this calculated?
    Metric
    Tobacco use
    Scale
    100 = lowest tobacco use (best), 0 = highest
    Raw value
    13.8 % of adults
    Native score
    76.59 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    65th percentile — ranks 59th of 166. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (13.8 − 3.1) / (48.8 − 3.1) ] = 76.59

    Min and max are this dataset's lowest (3.1) and highest (48.8) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = lowest under-5 mortality (best), 0 = highest

    Ranks 14th of 195 · native score 92.56 · reference year 2024

    93percentile
    How is this calculated?
    Metric
    Under-5 mortality rate
    Scale
    100 = lowest under-5 mortality (best), 0 = highest
    Raw value
    2.7 deaths per 1,000 live births
    Native score
    92.56 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    93th percentile — ranks 14th of 195. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 2.7 among 195 countries ] = 92.56

    The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.

Quality of life & wellbeing

  • 100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)

    Ranks 13th of 193 · native score 94.6 · reference year 2023

    93percentile
    How is this calculated?
    Metric
    Human Development Index
    Scale
    100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
    Raw value
    0.946 HDI (0–1)
    Native score
    94.6 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    93th percentile — ranks 13th of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.95 − 0) / (1 − 0) = 94.6

    The index is kept on its own published scale.

    Source
    UNDP — Human Development Report · United Nations Development Programme
    License
    CC BY 3.0 IGO
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Human Development Index, retrieved via the Our World in Data mirror (ourworldindata.org/grapher/human-development-index), which republishes the UNDP HDR series. Primary source and methodology owner is UNDP.
  • 100 = highest average life evaluation (ladder 10), 0 = lowest (ladder 0)

    Ranks 37th of 165 · native score 65.85 · reference year 2025

    78percentile
    How is this calculated?
    Metric
    Life satisfaction (happiness)
    Scale
    100 = highest average life evaluation (ladder 10), 0 = lowest (ladder 0)
    Raw value
    6.585 Cantril ladder (0–10)
    Native score
    65.85 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    78th percentile — ranks 37th of 165. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (6.59 − 0) / (10 − 0) = 65.85

    The 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).
Singapore — country scores · WorldScore