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Papua New Guinea

Updated: July 2026

Key Insights
The resources applied by the Papua New Guinean government to collect, compile, and publish national accounts data are severely inadequate.

The national statistical agency, the National Statistical Office (NSO), operates under severe structural, operational, and financial constraints:
  • Geographical and Infrastructure Barriers: Papua New Guinea's rugged topography-comprising mountainous highlands, dense rainforests, and isolated island provinces-makes physical field data collection logistically difficult and expensive. Transport links across many provinces remain poor, resulting in persistent gaps in local survey coverage.
  • Large Rural and Informal Economy: The vast majority of the population relies on subsistence agriculture, informal trade, and small-scale cash cropping. Accurately measuring non-monetised rural production and informal economic activity requires frequent, resource-intensive household and agricultural surveys that state budgets cannot sustain.
  • Severe Budgetary and Capacity Shortfalls: The NSO faces chronic underfunding, which directly limits its ability to recruit and retain specialized technical staff, update administrative business registries, and modernise digital data processing systems.
  • Significant Release Lags: Delays in conducting baseline surveys-such as the national population census, household income and expenditure surveys, and economic censuses-mean national accounts frequently rely on outdated baselines, causing substantial time lags in official macroeconomic publications.
  • Heavy Reliance on External Technical Support: Major statistical operations and capacity-strengthening projects rely heavily on financial and technical assistance from foreign development partners, such as the Australian Government (DFAT), the World Bank, and UN agencies.
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Demographics:   
DATA QUALITY    /    POPULATION PROFILE

E.S.G.:   
ENVIRONMENTAL    /    SOCIAL    /    GOVERNANCE

 
ECONOMICS
DEMOGRAPHICS
E.S.G.
Demographics sections:    DATA QUALITY    /    POPULATION PROFILE

 
POPULATION DATA QUALITY

The Population Data Quality Rating is derived from three factors: a country's latest Census Year; its Capacity for producing statistical data; and its Registration of Births data. Read more...

The three components are weighted to form the Population Data Quality Index.


Population Data Quality Ratings
Index: 0 = Extremely poor quality, 100 = Good as it gets
Ranked by Data Quality Index
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Country
 Rank
Order		 Population
Data Quality
(Index, 0-100)		 Population
Data Quality
(Rating, A-E)		 Census
Years
(Out-of-date)		 Statistical Resources
(Index, 0-100)		 Registration of Births
(% of total)




Guinea 137 33.1 E 11 39.6 62.0
Gabon 138 32.3 E 12 38.4 89.6
Eswatini 139 32.0 E 8 38.3 53.5
Cameroon 140 31.8 E 20 53.3 61.9
Mauritania 141 31.4 E 12 34.6 44.8
Honduras 142 30.0 E 19 43.4 97.0
Chad 143 27.3 E 16 35.8 25.7
Congo, Rep. 144 26.8 E 18 24.2 95.9
Papua New Guinea 145 26.3 E 14 31.1 13.4
Turkmenistan 146 25.9 E 5 7.2 99.9
Guinea-Bissau 147 25.6 E 16 35.1 46.0
Comoros 148 24.9 E 8 67.0 87.3
Haiti 149 24.8 E 11 28.3 84.8
Burundi 150 23.6 E 17 41.4 83.5
Central African Republic 151 21.9 E 22 27.3 44.8
Yemen, Rep. 152 21.6 E 21 23.0 30.7
Libya 153 19.4 E 19 20.6 99.0

Access full Population Data Quality Ratings table


Data Notes
Population Data Quality Index numbers shown on a scale of 0-100.
         0 = Poor, 100 = Excellent.

Rating definitions:
         A: As good as it gets
         B: Good
         C: Use with caution
         D: Poor
         E: Extremely poor quality

The index calculations and displayed data are derived from the most current and up-to-date source data available.
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Related Insights for Population Data Quality
 
 

 
POPULATION PROFILE

World Economics has collated key demographic data for Papua New Guinea in the table below. The data covers Population size, average age and dependency ratios.


Population Profile
Ranked by Population Size: 2025
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Country
 Population
Size
(Millions, 2025)		 Median
Age
(Years)		 Fertility
Rate
(2025)		 Age
Dependency
(Young)		 Age
Dependency
(Old)		 Age
Dependency
(Total)




Belgium 11.7 41.9 1.1% 24.4% 33.8% 58.2%
Jordan 11.5 24.7 2.3% 45.3% 7.6% 52.9%
Dominican Republic 11.6 28.3 2.0% 39.3% 12.9% 52.2%
United Arab Emirates 11.5 31.6 1.0% 19.3% 2.2% 21.6%
Honduras 11.1 24.2 2.2% 45.7% 7.1% 52.9%
Czechia 10.5 43.8 1.2% 23.3% 33.7% 56.9%
Sweden 10.7 40.3 1.2% 26.3% 33.7% 60.0%
Tajikistan 10.9 22.2 2.7% 58.8% 7.1% 65.9%
Papua New Guinea 10.9 22.8 2.8% 51.7% 5.9% 57.5%
Portugal 10.4 46.9 1.3% 20.4% 40.9% 61.3%
Azerbaijan 10.4 33.6 1.4% 29.6% 14.0% 43.6%
Greece 9.9 46.8 1.1% 20.0% 39.4% 59.5%
Hungary 9.6 43.9 1.3% 22.3% 33.1% 55.4%
Togo 9.9 19.1 3.8% 67.0% 5.7% 72.7%
Israel 9.6 29.2 2.5% 44.6% 21.3% 65.9%
Austria 9.1 43.6 1.1% 21.9% 33.6% 55.5%
Belarus 8.9 41.3 1.0% 23.5% 28.8% 52.3%


Access full Population table


Data Notes
Data sources:
Fertility rate data is from the United Nations Population Prospect Database, Actual data to 2024, Medium estimate used for 2024-2050.

The displayed data are derived from the most current and up-to-date source data available.
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