← Map

Papua New Guinea

PNG

Melanesia · Oceania · UN member

The circle shows each metric's percentile rank (position among countries with data), which is comparable across metrics. Each metric's native score uses its own scale and is not comparable between metrics — see it (and the full formula) in “How is this calculated?”.

78 metrics for this country

Education

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

    Ranks 101st of 155 · native score 82.24 · reference year 2022

    35percentile
    How is this calculated?
    Metric
    Adult literacy rate
    Scale
    100 = highest adult literacy in the dataset, 0 = lowest
    Raw value
    87.0047 % of adults
    Native score
    82.24 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    35th percentile — ranks 101st of 155. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (87 − 26.83) / (100 − 26.83) = 82.24

    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
    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 education spending (% GDP) in the dataset, 0 = lowest

    Ranks 197th of 200 · native score 4.77 · reference year 2023

    2percentile
    How is this calculated?
    Metric
    Government education spending
    Scale
    100 = highest education spending (% GDP) in the dataset, 0 = lowest
    Raw value
    0.782123 % of GDP
    Native score
    4.77 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    2th percentile — ranks 197th of 200. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.78 − 0) / (16.39 − 0) = 4.77

    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
    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 years of schooling in the dataset, 0 = fewest

    Ranks 140th of 146 · native score 16.82 · reference year 2020

    4percentile
    How is this calculated?
    Metric
    Mean years of schooling
    Scale
    100 = most years of schooling in the dataset, 0 = fewest
    Raw value
    4.84 years
    Native score
    16.82 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    4th percentile — ranks 140th of 146. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (4.84 − 3.04) / (13.74 − 3.04) = 16.82

    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 164th of 197 · native score 62.62 · reference year 2016

    17percentile
    How is this calculated?
    Metric
    Pupil–teacher ratio (primary)
    Scale
    100 = lowest pupil–teacher ratio (best), 0 = highest
    Raw value
    35.5217 pupils per teacher
    Native score
    62.62 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    17th percentile — ranks 164th of 197. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (35.52 − 6.93) / (83.41 − 6.93) ] = 62.62

    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
    2016
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = most researchers per capita, 0 = fewest

    Ranks 129th of 144 · native score 33.2 · reference year 2016

    11percentile
    How is this calculated?
    Metric
    Researchers in R&D
    Scale
    100 = most researchers per capita, 0 = fewest
    Raw value
    33.1588 per million people
    Native score
    33.2 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    11th percentile — ranks 129th of 144. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 33.16 − ln 1.45) / (ln 18,129.75 − ln 1.45) = 33.2

    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
    2016
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = highest completion in the dataset, 0 = lowest

    Ranks 172nd of 192 · native score 23.7 · reference year 2023

    11percentile
    How is this calculated?
    Metric
    Lower-secondary completion rate
    Scale
    100 = highest completion in the dataset, 0 = lowest
    Raw value
    41.8807 % of relevant age group
    Native score
    23.7 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    11th percentile — ranks 172nd of 192. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (41.88 − 8.89) / (148.09 − 8.89) = 23.7

    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.

Society & culture

  • Adult male heightTier ADescriptive

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

    Ranks 187th of 200 · native score 16.61 · reference year 1996

    7percentile
    How is this calculated?
    Metric
    Adult male height
    Scale
    100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
    Raw value
    163.568 cm
    Native score
    16.61 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    7th percentile — ranks 187th of 200. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (163.57 − 159.79) / (182.54 − 159.79) = 16.61

    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 cocoa supply per person in the dataset, 0 = lowest

    Ranks 160th of 191 · native score 0.5 · reference year 2023

    16percentile

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

    How is this calculated?
    Metric
    Chocolate supply per person (proxy)
    Scale
    100 = highest cocoa supply per person in the dataset, 0 = lowest
    Raw value
    0.07 kg cocoa per person / year
    Native score
    0.5 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    16th percentile — ranks 160th of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.07 − 0) / (14.07 − 0) = 0.5

    Min and max are this dataset's lowest (0) and highest (14.07) values, so the score is relative to the current country set.

    Source
    FAO (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier C — Survey / proxy
    Source notes
    Cocoa 'food available for consumption' per capita from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. A supply proxy, not measured consumption — Tier C.
  • 100 = highest female participation in the dataset, 0 = lowest

    Ranks 115th of 186 · native score 58.99 · reference year 2025

    38percentile
    How is this calculated?
    Metric
    Female labour force participation
    Scale
    100 = highest female participation in the dataset, 0 = lowest
    Raw value
    50.822 % of women 15+
    Native score
    58.99 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    38th percentile — ranks 115th of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (50.82 − 4.66) / (82.91 − 4.66) = 58.99

    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 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse

    Ranks 140th of 191 · native score 8.05 · reference year 2023

    27percentile
    How is this calculated?
    Metric
    Fish & seafood supply per capita
    Scale
    100 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse
    Raw value
    7.1 kg per person per year
    Native score
    8.05 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    27th percentile — ranks 140th of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (7.1 − 0.38) / (83.81 − 0.38) = 8.05

    Min and max are this dataset's lowest (0.38) and highest (83.81) values, so the score is relative to the current country set.

    Source
    FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
  • Fruit supply per capitaTier ADescriptive

    100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse

    Ranks 6th of 191 · native score 39.53 · reference year 2023

    97percentile
    How is this calculated?
    Metric
    Fruit supply per capita
    Scale
    100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
    Raw value
    211.7 kg per person per year
    Native score
    39.53 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    97th percentile — ranks 6th of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (211.7 − 4.27) / (529.06 − 4.27) = 39.53

    Min and max are this dataset's lowest (4.27) and highest (529.06) values, so the score is relative to the current country set.

    Source
    FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
  • 100 = most gender-equal (GII 0), 0 = most unequal (GII 1)

    Ranks 156th of 172 · native score 41.6 · reference year 2023

    9percentile
    How is this calculated?
    Metric
    Gender equality (inverted GII)
    Scale
    100 = most gender-equal (GII 0), 0 = most unequal (GII 1)
    Raw value
    0.584 index (0–1, lower = more equal)
    Native score
    41.6 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    9th percentile — ranks 156th of 172. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 − [ 100 · (0.58 − 0) / (1 − 0) ] = 41.6

    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.
  • Meat supply per capitaTier ADescriptive

    100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse

    Ranks 92nd of 191 · native score 35.83 · reference year 2023

    52percentile
    How is this calculated?
    Metric
    Meat supply per capita
    Scale
    100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
    Raw value
    58.47 kg per person per year
    Native score
    35.83 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    52th percentile — ranks 92nd of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (58.47 − 3.49) / (156.93 − 3.49) = 35.83

    Min and max are this dataset's lowest (3.49) and highest (156.93) values, so the score is relative to the current country set.

    Source
    FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
  • 100 = universal social protection coverage, 0 = none

    Ranks 188th of 214 · native score 9.1 · reference year 2022

    12percentile
    How is this calculated?
    Metric
    Social protection coverage
    Scale
    100 = universal social protection coverage, 0 = none
    Raw value
    9.1 % of population
    Native score
    9.1 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    12th percentile — ranks 188th of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (9.1 − 0) / (100 − 0) = 9.1

    The index is kept on its own published scale.

    Source
    ILOSTAT (International Labour Organization) · International Labour Organization
    License
    CC BY 4.0
    Reference year
    2022
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    ILOSTAT via the ILO rplumber API (rplumber.ilo.org). CC BY 4.0 for databases published since 3 May 2023.
  • 100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse

    Ranks 147th of 174 · native score 37.26 · reference year 2019

    16percentile
    How is this calculated?
    Metric
    International tourist arrivals
    Scale
    100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
    Raw value
    160,000 arrivals per year
    Native score
    37.26 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    16th percentile — ranks 147th of 174. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 160,000 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 37.26

    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).
  • 100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse

    Ranks 141st of 191 · native score 11.3 · reference year 2023

    26percentile
    How is this calculated?
    Metric
    Vegetable supply per capita
    Scale
    100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
    Raw value
    51.38 kg per person per year
    Native score
    11.3 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    26th percentile — ranks 141st of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (51.38 − 5.34) / (412.72 − 5.34) = 11.3

    Min and max are this dataset's lowest (5.34) and highest (412.72) values, so the score is relative to the current country set.

    Source
    FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
    License
    CC BY 4.0
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.

Demographics & migration

  • Age dependency ratioTier ADescriptive

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

    Ranks 84th of 215 · native score 45.5 · reference year 2025

    61percentile
    How is this calculated?
    Metric
    Age dependency ratio
    Scale
    100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
    Raw value
    58.062 dependents per 100 working-age
    Native score
    45.5 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    61th percentile — ranks 84th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (58.06 − 20.05) / (103.59 − 20.05) = 45.5

    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 55th of 215 · native score 45.72 · reference year 2024

    75percentile
    How is this calculated?
    Metric
    Fertility rate
    Scale
    100 = highest fertility, 0 = lowest — descriptive, not better or worse
    Raw value
    3.072 births per woman
    Native score
    45.72 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    75th percentile — ranks 55th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (3.07 − 0.58) / (6.03 − 0.58) = 45.72

    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 87th of 215 · native score 48.4 · reference year 2024

    60percentile
    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
    5.375 years (female − male)
    Native score
    48.4 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    60th percentile — ranks 87th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (5.38 − 0.46) / (10.62 − 0.46) = 48.4

    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 179th of 237 · native score 17.71 · reference year 2023

    25percentile
    How is this calculated?
    Metric
    Median age
    Scale
    100 = oldest median age, 0 = youngest — descriptive, not better or worse
    Raw value
    22.344 years
    Native score
    17.71 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    25th percentile — ranks 179th of 237. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (22.34 − 14.32) / (59.63 − 14.32) = 17.71

    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 200th of 214 · native score 0.3 · reference year 2024

    6percentile
    How is this calculated?
    Metric
    Foreign-born population
    Scale
    100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
    Raw value
    0.3 % foreign-born
    Native score
    0.3 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    6th percentile — ranks 200th of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.3 − 0) / (100 − 0) = 0.3

    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 87th of 215 · native score 51.76 · reference year 2025

    59percentile
    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
    -0.026 per 1,000 people
    Native score
    51.76 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    59th percentile — ranks 87th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (-0.03 − -46.91) / (43.67 − -46.91) = 51.76

    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 91st of 215 · native score 58.88 · reference year 2025

    58percentile
    How is this calculated?
    Metric
    Total population
    Scale
    100 = most populous, 0 = least populous — descriptive, not better or worse
    Raw value
    10,762,817 people
    Native score
    58.88 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    58th percentile — ranks 91st of 215. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 10,762,817 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 58.88

    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 181st of 215 · native score 42.91 · reference year 2023

    16percentile
    How is this calculated?
    Metric
    Population density
    Scale
    100 = most dense, 0 = least dense — descriptive, not better or worse
    Raw value
    22.9423 people per km²
    Native score
    42.91 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    16th percentile — ranks 181st of 215. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 22.94 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 42.91

    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 58th of 237 · native score 55.66 · reference year 2050

    76percentile
    How is this calculated?
    Metric
    Population change (projection)
    Scale
    100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
    Raw value
    40.9 % change 2024→2050
    Native score
    55.66 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    76th percentile — ranks 58th of 237. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (40.9 − -32.9) / (99.7 − -32.9) = 55.66

    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 113th of 211 · native score 46.68 · reference year 2024

    47percentile
    How is this calculated?
    Metric
    Refugees (by origin)
    Scale
    100 = most refugees produced, 0 = fewest — descriptive, not better or worse
    Raw value
    504 refugees
    Native score
    46.68 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    47th percentile — ranks 113th of 211. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = percentile rank of 504 among 211 countries = 46.68

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

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

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

    Ranks 192nd of 193 · native score 0 · reference year 2024

    1percentile
    How is this calculated?
    Metric
    Remittances received
    Scale
    100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    0.0125507 % of GDP
    Native score
    0 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    1th percentile — ranks 192nd of 193. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.01 − 0.01) / (47.15 − 0.01) = 0

    Min and max are this dataset's lowest (0.01) and highest (47.15) values, so the score is relative to the current country set.

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

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

    Ranks 2nd of 215 · native score 84.22 · reference year 2025

    99percentile
    How is this calculated?
    Metric
    Rural population share
    Scale
    100 = fully rural, 0 = fully urban — descriptive, not better or worse
    Raw value
    84.2203 % rural
    Native score
    84.22 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    99th percentile — ranks 2nd of 215. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (84.22 − 0) / (100 − 0) = 84.22

    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 13th of 215 · native score 42.76 · reference year 2024

    93percentile
    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
    1.076 male births per female birth
    Native score
    42.76 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    93th percentile — ranks 13th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (1.08 − 1.01) / (1.16 − 1.01) = 42.76

    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 214th of 215 · native score 15.78 · reference year 2025

    1percentile
    How is this calculated?
    Metric
    Urbanization
    Scale
    100 = fully urban, 0 = fully rural — descriptive, not better or worse
    Raw value
    15.7797 % urban
    Native score
    15.78 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    1th percentile — ranks 214th of 215. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (15.78 − 0) / (100 − 0) = 15.78

    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 88th of 177 · native score 50.56 · reference year 2023

    51percentile
    How is this calculated?
    Metric
    Air transport passengers
    Scale
    100 = most air passengers, 0 = fewest — descriptive, not better or worse
    Raw value
    1,547,502 passengers per year
    Native score
    50.56 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    51th percentile — ranks 88th of 177. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = percentile rank of 1,547,502 among 177 countries = 50.56

    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 165th of 190 · native score 27.02 · reference year 2024

    13percentile
    How is this calculated?
    Metric
    Climate vulnerability
    Scale
    100 = least climate-vulnerable (best), 0 = most vulnerable
    Raw value
    0.549284 index (0–1, higher = more vulnerable)
    Native score
    27.02 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    13th percentile — ranks 165th of 190. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (0.55 − 0.26) / (0.66 − 0.26) ] = 27.02

    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 48th of 214 · native score 77.8 · reference year 2024

    78percentile
    How is this calculated?
    Metric
    CO₂ emissions per capita
    Scale
    100 = lowest emissions per capita (best), 0 = highest
    Raw value
    0.789055 tonnes CO₂ per capita
    Native score
    77.8 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    78th percentile — ranks 48th of 214. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 0.79 among 214 countries ] = 77.8

    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 208th of 214 · native score 20.5 · reference year 2023

    3percentile
    How is this calculated?
    Metric
    Access to electricity
    Scale
    100 = universal electricity access, 0 = none
    Raw value
    20.5 % of population
    Native score
    20.5 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    3th percentile — ranks 208th of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (20.5 − 0) / (100 − 0) = 20.5

    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 = most fixed-broadband subscriptions per capita, 0 = fewest

    Ranks 188th of 208 · native score 0.38 · reference year 2024

    10percentile
    How is this calculated?
    Metric
    Fixed broadband subscriptions
    Scale
    100 = most fixed-broadband subscriptions per capita, 0 = fewest
    Raw value
    0.232591 per 100 people
    Native score
    0.38 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    10th percentile — ranks 188th of 208. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.23 − 0) / (60.97 − 0) = 0.38

    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 9th of 213 · native score 78.95 · reference year 2023

    96percentile
    How is this calculated?
    Metric
    Forest area
    Scale
    100 = most forested, 0 = least — descriptive, not better or worse
    Raw value
    78.9541 % of land area
    Native score
    78.95 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    96th percentile — ranks 9th of 213. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (78.95 − 0) / (100 − 0) = 78.95

    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 195th of 209 · native score 18.81 · reference year 2024

    7percentile
    How is this calculated?
    Metric
    Internet users
    Scale
    100 = whole population online, 0 = none
    Raw value
    18.8116 % of population
    Native score
    18.81 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    7th percentile — ranks 195th of 209. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (18.81 − 0) / (100 − 0) = 18.81

    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 84th of 169 · native score 42.5 · reference year 2022

    48percentile
    How is this calculated?
    Metric
    Logistics Performance Index
    Scale
    100 = best logistics performance (index 5), 0 = worst (1)
    Raw value
    2.7 index (1–5)
    Native score
    42.5 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    48th percentile — ranks 84th of 169. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (2.7 − 1) / (5 − 1) = 42.5

    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 75th of 200 · native score 62.75 · reference year 2023

    63percentile
    How is this calculated?
    Metric
    PM2.5 air pollution
    Scale
    100 = cleanest air (lowest PM2.5), 0 = most polluted
    Raw value
    14.1118 µg/m³
    Native score
    62.75 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    63th percentile — ranks 75th of 200. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 14.11 among 200 countries ] = 62.75

    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 193rd of 212 · native score 3.7 · reference year 2025

    9percentile
    How is this calculated?
    Metric
    Protected land area
    Scale
    100 = most land protected, 0 = least
    Raw value
    3.7 % of land area
    Native score
    3.7 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    9th percentile — ranks 193rd of 212. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (3.7 − 0) / (100 − 0) = 3.7

    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 43rd of 212 · native score 54.6 · reference year 2022

    80percentile
    How is this calculated?
    Metric
    Renewable energy share
    Scale
    100 = all energy renewable, 0 = none
    Raw value
    54.6 % of final energy
    Native score
    54.6 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    80th percentile — ranks 43rd of 212. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (54.6 − 0) / (100 − 0) = 54.6

    The index is kept on its own published scale.

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

Economy

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

    Ranks 144th of 182 · native score 0.32 · reference year 2020

    21percentile
    How is this calculated?
    Metric
    New business density
    Scale
    100 = highest new-business density in the dataset, 0 = lowest
    Raw value
    0.673116 new firms per 1,000 aged 15–64
    Native score
    0.32 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    21th percentile — ranks 144th of 182. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.67 − 0.02) / (201.01 − 0.02) = 0.32

    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
    2020
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
  • 100 = highest employment ratio in the dataset, 0 = lowest

    Ranks 136th of 186 · native score 44.94 · reference year 2025

    27percentile
    How is this calculated?
    Metric
    Employment-to-population ratio
    Scale
    100 = highest employment ratio in the dataset, 0 = lowest
    Raw value
    50.731 % of population 15+
    Native score
    44.94 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    27th percentile — ranks 136th of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (50.73 − 21.21) / (86.9 − 21.21) = 44.94

    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 26th of 192 · native score 35.77 · reference year 2004

    87percentile
    How is this calculated?
    Metric
    Exports of goods & services
    Scale
    100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    72.164 % of GDP
    Native score
    35.77 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    87th percentile — ranks 26th of 192. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (72.16 − 1.1) / (199.76 − 1.1) = 35.77

    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
    2004
    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 184th of 201 · native score 88.41 · reference year 2024

    9percentile
    How is this calculated?
    Metric
    Foreign direct investment
    Scale
    100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    -0.643805 % of GDP (net inflows)
    Native score
    88.41 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    9th percentile — ranks 184th of 201. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (-0.64 − -1,303.11) / (170.05 − -1,303.11) = 88.41

    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 81st of 189 · native score 19.84 · reference year 2031

    57percentile
    How is this calculated?
    Metric
    GDP growth (projection)
    Scale
    100 = highest projected growth, 0 = lowest
    Raw value
    3.35 % per year (avg 2026–2031)
    Native score
    19.84 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    57th percentile — ranks 81st of 189. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (3.35 − 0.62) / (14.38 − 0.62) = 19.84

    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 164th of 202 · native score 29.36 · reference year 2024

    19percentile
    How is this calculated?
    Metric
    GDP per capita (PPP)
    Scale
    100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
    Raw value
    4,874.69 international $ (PPP, current)
    Native score
    29.36 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    19th percentile — ranks 164th of 202. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 4,874.69 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 29.36

    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 121st of 155 · native score 12.02 · reference year 2024

    22percentile
    How is this calculated?
    Metric
    Government revenue
    Scale
    100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    16.5534 % of GDP
    Native score
    12.02 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    22th percentile — ranks 121st of 155. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (16.55 − 3.03) / (115.55 − 3.03) = 12.02

    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 38th of 177 · native score 65.63 · reference year 2004

    79percentile
    How is this calculated?
    Metric
    Gross savings
    Scale
    100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    30.4211 % of GDP
    Native score
    65.63 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    79th percentile — ranks 38th of 177. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (30.42 − -21.13) / (57.42 − -21.13) = 65.63

    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
    2004
    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 equal (lowest Gini in the dataset), 0 = most unequal

    Ranks 134th of 167 · native score 48.73 · reference year 2009

    20percentile
    How is this calculated?
    Metric
    Income inequality (Gini)
    Scale
    100 = most equal (lowest Gini in the dataset), 0 = most unequal
    Raw value
    41.9 Gini index (0–100)
    Native score
    48.73 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    20th percentile — ranks 134th of 167. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (41.9 − 23.8) / (59.1 − 23.8) ] = 48.73

    Min and max are this dataset's lowest (23.8) and highest (59.1) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    World Bank · World Bank
    License
    CC BY 4.0
    Reference year
    2009
    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 53rd of 192 · native score 72.66 · reference year 2025

    73percentile
    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
    4.42141 % annual change (CPI)
    Native score
    72.66 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    73th percentile — ranks 53rd of 192. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = percentile rank of 4.42 among 192 countries = 72.66

    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 147th of 177 · native score 35.27 · reference year 2024

    17percentile
    How is this calculated?
    Metric
    Labour productivity
    Scale
    100 = highest output per worker, 0 = lowest
    Raw value
    12,742 constant PPP$ per worker
    Native score
    35.27 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    17th percentile — ranks 147th of 177. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 12,741.97 − ln 2,444.23) / (ln 263,863.91 − ln 2,444.23) = 35.27

    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 100th of 193 · native score 16.88 · reference year 2025

    48percentile
    How is this calculated?
    Metric
    Government debt
    Scale
    100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
    Raw value
    52.1 % of GDP
    Native score
    16.88 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    48th percentile — ranks 100th of 193. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (52.1 − 0) / (308.7 − 0) = 16.88

    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 25th of 186 · native score 92.84 · reference year 2025

    87percentile
    How is this calculated?
    Metric
    Unemployment rate
    Scale
    100 = lowest unemployment in the dataset, 0 = highest
    Raw value
    2.571 % of labour force
    Native score
    92.84 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    87th percentile — ranks 25th of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (2.57 − 0.13) / (34.2 − 0.13) ] = 92.84

    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 16th of 186 · native score 95.64 · reference year 2025

    92percentile
    How is this calculated?
    Metric
    Youth unemployment rate
    Scale
    100 = lowest youth unemployment (best), 0 = highest
    Raw value
    3.785 % of labour force 15–24
    Native score
    95.64 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    92th percentile — ranks 16th of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (3.79 − 0.46) / (76.77 − 0.46) ] = 95.64

    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 153rd of 197 · native score 22.59 · reference year 2025

    23percentile
    How is this calculated?
    Metric
    Deaths in armed conflicts
    Scale
    100 = fewest conflict deaths (most at peace), 0 = most
    Raw value
    31 deaths per year
    Native score
    22.59 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    23th percentile — ranks 153rd of 197. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 31 among 197 countries ] = 22.59

    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 151st of 193 · native score 22.02 · reference year 2010

    22percentile
    How is this calculated?
    Metric
    Homicide rate
    Scale
    100 = safest (fewest homicides), 0 = most homicides
    Raw value
    9.34038 per 100,000 population
    Native score
    22.02 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    22th percentile — ranks 151st of 193. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 9.34 among 193 countries ] = 22.02

    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
    2010
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Intentional homicide victims per 100,000, indicator VC.IHR.PSRC.P5, retrieved via the World Bank API. Primary source is UNODC; the World Bank redistributes the series under CC BY 4.0.
  • 100 = fewest internally displaced (most stable), 0 = most

    Ranks 43rd of 82 · native score 48.17 · reference year 2025

    48percentile
    How is this calculated?
    Metric
    Internally displaced persons
    Scale
    100 = fewest internally displaced (most stable), 0 = most
    Raw value
    70,000 people
    Native score
    48.17 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    48th percentile — ranks 43rd of 82. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 70,000 among 82 countries ] = 48.17

    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
    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 road-death rate (best), 0 = highest

    Ranks 79th of 190 · native score 80.5 · reference year 2019

    59percentile
    How is this calculated?
    Metric
    Road-traffic deaths
    Scale
    100 = lowest road-death rate (best), 0 = highest
    Raw value
    12.6 deaths per 100,000
    Native score
    80.5 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    59th percentile — ranks 79th of 190. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (12.6 − 0) / (64.6 − 0) ] = 80.5

    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 127th of 180 · native score 31 · reference year 2024

    29percentile
    How is this calculated?
    Metric
    Corruption Perceptions Index
    Scale
    100 = cleanest (least corrupt), 0 = most corrupt
    Raw value
    31 CPI score (0–100)
    Native score
    31 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    29th percentile — ranks 127th of 180. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (31 − 0) / (100 − 0) = 31

    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 94th of 175 · native score 46.7 · reference year 2025

    47percentile
    How is this calculated?
    Metric
    Electoral democracy index
    Scale
    100 = most democratic (index 1.0), 0 = least democratic
    Raw value
    0.467 index (0–1)
    Native score
    46.7 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    47th percentile — ranks 94th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.47 − 0) / (1 − 0) = 46.7

    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 47th of 175 · native score 83.9 · reference year 2025

    73percentile
    How is this calculated?
    Metric
    Freedom of expression index
    Scale
    100 = most free expression (index 1.0), 0 = least
    Raw value
    0.839 index (0–1)
    Native score
    83.9 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    73th percentile — ranks 47th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.84 − 0) / (1 − 0) = 83.9

    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 173rd of 204 · native score 31.99 · reference year 2024

    15percentile
    How is this calculated?
    Metric
    Government effectiveness
    Scale
    100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
    Raw value
    -0.900447 index (−2.5 to +2.5)
    Native score
    31.99 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    15th percentile — ranks 173rd of 204. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (-0.9 − -2.5) / (2.5 − -2.5) = 31.99

    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 97th of 175 · native score 51.1 · reference year 2025

    45percentile
    How is this calculated?
    Metric
    Rule of law index
    Scale
    100 = strongest rule of law (index 1.0), 0 = weakest
    Raw value
    0.511 index (0–1)
    Native score
    51.1 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    45th percentile — ranks 97th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.51 − 0) / (1 − 0) = 51.1

    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 188th of 193 · native score 2.7 · reference year 2025

    3percentile
    How is this calculated?
    Metric
    Women in parliament
    Scale
    100 = all seats held by women, 0 = none (≈50 = parity)
    Raw value
    2.7027 % of seats
    Native score
    2.7 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    3th percentile — ranks 188th of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (2.7 − 0) / (100 − 0) = 2.7

    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 173rd of 208 · native score 57.86 · reference year 2024

    17percentile
    How is this calculated?
    Metric
    Diabetes prevalence
    Scale
    100 = lowest diabetes prevalence (best), 0 = highest
    Raw value
    14.1 % of adults 20–79
    Native score
    57.86 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    17th percentile — ranks 173rd of 208. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (14.1 − 1.5) / (31.4 − 1.5) ] = 57.86

    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 148th of 193 · native score 23.85 · reference year 2023

    24percentile
    How is this calculated?
    Metric
    Health expenditure per capita
    Scale
    100 = highest health spending per capita, 0 = lowest
    Raw value
    85.1502 current US$ per capita
    Native score
    23.85 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    24th percentile — ranks 148th of 193. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 85.15 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 23.85

    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 171st of 191 · native score 2.15 · reference year 2023

    11percentile
    How is this calculated?
    Metric
    Hospital beds per 1,000
    Scale
    100 = most hospital beds per capita in the dataset, 0 = fewest
    Raw value
    0.62 per 1,000 people
    Native score
    2.15 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    11th percentile — ranks 171st of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.62 − 0.15) / (21.99 − 0.15) = 2.15

    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 190th of 193 · native score 42 · reference year 2024

    1percentile
    How is this calculated?
    Metric
    Immunization coverage (DTP3)
    Scale
    100 = full DTP3 coverage, 0 = none
    Raw value
    42 % of children aged 12–23 months
    Native score
    42 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    1th percentile — ranks 190th of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (42 − 0) / (100 − 0) = 42

    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 152nd of 195 · native score 57.43 · reference year 2024

    22percentile
    How is this calculated?
    Metric
    Infant mortality rate
    Scale
    100 = lowest infant mortality in the dataset, 0 = highest
    Raw value
    31.3 per 1,000 live births
    Native score
    57.43 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    22th percentile — ranks 152nd of 195. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (31.3 − 1.2) / (71.9 − 1.2) ] = 57.43

    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 183rd of 215 · native score 36.47 · reference year 2024

    15percentile
    How is this calculated?
    Metric
    Life expectancy at birth
    Scale
    100 = longest life expectancy in the dataset, 0 = shortest
    Raw value
    66.256 years
    Native score
    36.47 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    15th percentile — ranks 183rd of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (66.26 − 54.64) / (86.5 − 54.64) = 36.47

    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 156th of 194 · native score 19.85 · reference year 2023

    20percentile
    How is this calculated?
    Metric
    Maternal mortality ratio
    Scale
    100 = lowest maternal mortality (best), 0 = highest
    Raw value
    189 deaths per 100,000 live births
    Native score
    19.85 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    20th percentile — ranks 156th of 194. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 189 among 194 countries ] = 19.85

    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
    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 191st of 195 · native score 0.24 · reference year 2023

    2percentile
    How is this calculated?
    Metric
    Physicians per 1,000
    Scale
    100 = most physicians per capita in the dataset, 0 = fewest
    Raw value
    0.061 per 1,000 people
    Native score
    0.24 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    2th percentile — ranks 191st of 195. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.06 − 0.04) / (9.54 − 0.04) = 0.24

    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
    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 = universal safe sanitation, 0 = none

    Ranks 133rd of 145 · native score 16.66 · reference year 2024

    9percentile
    How is this calculated?
    Metric
    Safe sanitation
    Scale
    100 = universal safe sanitation, 0 = none
    Raw value
    16.6644 % of population
    Native score
    16.66 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    9th percentile — ranks 133rd of 145. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (16.66 − 0) / (100 − 0) = 16.66

    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 161st of 166 · native score 20.79 · reference year 2024

    3percentile
    How is this calculated?
    Metric
    Tobacco use
    Scale
    100 = lowest tobacco use (best), 0 = highest
    Raw value
    39.3 % of adults
    Native score
    20.79 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    3th percentile — ranks 161st of 166. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (39.3 − 3.1) / (48.8 − 3.1) ] = 20.79

    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 157th of 195 · native score 19.74 · reference year 2024

    20percentile
    How is this calculated?
    Metric
    Under-5 mortality rate
    Scale
    100 = lowest under-5 mortality (best), 0 = highest
    Raw value
    39.4 deaths per 1,000 live births
    Native score
    19.74 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    20th percentile — ranks 157th of 195. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 39.4 among 195 countries ] = 19.74

    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
    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 undernourishment (best), 0 = highest

    Ranks 158th of 169 · native score 49.32 · reference year 2023

    7percentile
    How is this calculated?
    Metric
    Undernourishment
    Scale
    100 = lowest undernourishment (best), 0 = highest
    Raw value
    28.7 % of population
    Native score
    49.32 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    7th percentile — ranks 158th of 169. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (28.7 − 2.5) / (54.2 − 2.5) ] = 49.32

    Min and max are this dataset's lowest (2.5) and highest (54.2) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

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

Quality of life & wellbeing

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

    Ranks 160th of 193 · native score 57.6 · reference year 2023

    17percentile
    How is this calculated?
    Metric
    Human Development Index
    Scale
    100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
    Raw value
    0.576 HDI (0–1)
    Native score
    57.6 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    17th percentile — ranks 160th of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.58 − 0) / (1 − 0) = 57.6

    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.
Papua New Guinea — country scores · WorldScore