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Getting electricity: Financial deterrents aimed at limiting … 0-1 in Papua New Guinea

Papua New Guinea: Getting electricity: Financial deterrents aimed at limiting … 0-1 was 1 DB16-20 methodology in 2019. ▬ Flat

Latest (2019)
1 DB16-20 methodology
Change on year
unchanged
World rank
1st
of 187 countries
All-time high
1 DB16-20 methodology
in 2014
All-time low
1 DB16-20 methodology
in 2014
Years of data
6
2014–2019

Getting electricity: Financial deterrents aimed at limiting outages in Papua New Guinea, 2014–2019

00.20.40.60.812014201620192014: 1 DB16-20 methodology2015: 1 DB16-20 methodology2016: 1 DB16-20 methodology2017: 1 DB16-20 methodology2018: 1 DB16-20 methodology2019: 1 DB16-20 methodology

Source: World Bank. Measured in DB16-20 methodology.

Analysis

Papua New Guinea recorded 1 DB16-20 methodology for getting electricity: financial deterrents aimed at limiting outages in 2019. That is the highest value across all 6 years on record.

Compared with earlier readings it is unchanged over ten years.

That places Papua New Guinea 1st out of 187 countries with data for 2019, putting it in the top 10%.

Getting electricity: Financial deterrents aimed at limiting … 0-1 in Papua New Guinea, year by year

Year DB16-20 methodology Change
2014 1 DB16-20 methodology —
2015 1 DB16-20 methodology +0.0%
2016 1 DB16-20 methodology +0.0%
2017 1 DB16-20 methodology +0.0%
2018 1 DB16-20 methodology +0.0%
2019 1 DB16-20 methodology +0.0%

Papua New Guinea compared with similar countries

  • Papua New Guinea's 1 DB16-20 methodology is above the median for East Asia & Pacific, which is 1 DB16-20 methodology, 1.0× the median. (28 countries reporting)

Countries ranked near Papua New Guinea

  1. 1 India 1 DB16-20 methodology compare
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  7. 1 Brazil 1 DB16-20 methodology compare
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  11. 1 Armenia 1 DB16-20 methodology compare
  12. 1 Australia 1 DB16-20 methodology compare
  13. 1 Barbados 1 DB16-20 methodology compare
  14. 1 Belarus 1 DB16-20 methodology compare
  15. 1 Belgium 1 DB16-20 methodology compare
  16. 1 Bhutan 1 DB16-20 methodology compare
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  23. 1 Costa Rica 1 DB16-20 methodology compare
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  28. 1 Ecuador 1 DB16-20 methodology compare
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  31. 1 Finland 1 DB16-20 methodology compare
  32. 1 France 1 DB16-20 methodology compare
  33. 1 Georgia 1 DB16-20 methodology compare
  34. 1 Germany 1 DB16-20 methodology compare
  35. 1 Greece 1 DB16-20 methodology compare
  36. 1 Guatemala 1 DB16-20 methodology compare
  37. 1 Guyana 1 DB16-20 methodology compare
  38. 1 Hong Kong 1 DB16-20 methodology compare
  39. 1 Hungary 1 DB16-20 methodology compare
  40. 1 Ireland 1 DB16-20 methodology compare
  41. 1 Israel 1 DB16-20 methodology compare
  42. 1 Italy 1 DB16-20 methodology compare
  43. 1 Jamaica 1 DB16-20 methodology compare
  44. 1 Kazakhstan 1 DB16-20 methodology compare
  45. 1 Kiribati 1 DB16-20 methodology compare
  46. 1 South Korea 1 DB16-20 methodology compare
  47. 1 Kosovo 1 DB16-20 methodology compare
  48. 1 Kyrgyzstan 1 DB16-20 methodology compare
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  53. 1 Montenegro 1 DB16-20 methodology compare
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  56. 1 Netherlands 1 DB16-20 methodology compare
  57. 1 New Zealand 1 DB16-20 methodology compare
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  64. 1 Poland 1 DB16-20 methodology compare
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  67. 1 Rwanda 1 DB16-20 methodology compare
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  69. 1 Saudi Arabia 1 DB16-20 methodology compare
  70. 1 Senegal 1 DB16-20 methodology compare
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  72. 1 Slovakia 1 DB16-20 methodology compare
  73. 1 Slovenia 1 DB16-20 methodology compare
  74. 1 Spain 1 DB16-20 methodology compare
  75. 1 Sweden 1 DB16-20 methodology compare
  76. 1 Taiwan 1 DB16-20 methodology compare
  77. 1 Tanzania 1 DB16-20 methodology compare
  78. 1 Thailand 1 DB16-20 methodology compare
  79. 1 Togo 1 DB16-20 methodology compare
  80. 1 Trinidad and Tobago 1 DB16-20 methodology compare
  81. 1 Turkey 1 DB16-20 methodology compare
  82. 1 Ukraine 1 DB16-20 methodology compare
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  84. 1 United Kingdom 1 DB16-20 methodology compare
  85. 1 Uruguay 1 DB16-20 methodology compare
  86. 1 Uzbekistan 1 DB16-20 methodology compare
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  89. 1 Kosovo (UNSCR 1244) 1 DB16-20 methodology compare

See the full ranking of 187 places →

More private sector data for Papua New Guinea

All data for Papua New Guinea →

Frequently asked questions

What is getting electricity: financial deterrents aimed at limiting outages in Papua New Guinea?
Getting electricity: financial deterrents aimed at limiting outages in Papua New Guinea was 1 DB16-20 methodology in 2019, according to the World Bank.
What is the highest getting electricity: financial deterrents aimed at limiting outages recorded in Papua New Guinea?
The highest recorded value was 1 DB16-20 methodology in 2014.
What is the lowest getting electricity: financial deterrents aimed at limiting outages recorded in Papua New Guinea?
The lowest recorded value was 1 DB16-20 methodology in 2014.
How does Papua New Guinea rank for getting electricity: financial deterrents aimed at limiting outages?
Papua New Guinea ranks 1st out of 187 countries with data for 2019.
Is getting electricity: financial deterrents aimed at limiting outages rising or falling in Papua New Guinea?
Over the last ten years it is unchanged. The long-run trend across the full record is flat.
Where does this Papua New Guinea data come from?
The figures come from the World Bank, published as part of Getting electricity: Financial deterrents aimed at limiting outages (0-1) (DB16-20 methodology). Statizoid updates them automatically from the source API.

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Getting electricity: Financial deterrents aimed at limiting outages in Papua New Guinea. Statizoid. Retrieved 08 November 2026, from https://private-sector.statizoid.com/stat/getting-electricity-financial-deterrents-aimed-at-limiting-outages-0-1-db16-20-methodology/papua-new-guinea/

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About this data

Indicator
Getting electricity: Financial deterrents aimed at limiting outages (0-1) (DB16-20 methodology)
Unit
DB16-20 methodology
Source
World Bank
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
187 places, 1,122 data points, 2014–2019
Last refreshed

Th financial deterrents index evaluates whether financial deterrents exist to limit outages. A score of 1 is assigned if the utility compensates customers when outages exceed a certain cap, if the utility is fined by the regulator when outages exceed a certain cap or if both these conditions are met. The index is computed based on the methodology in the DB16-20 studies.