Data for 1985

Poverty Headcount at $3.00 a Day, Line-up Estimates, 1985

Name: Poverty Headcount at $3.00 a Day, Line-up Estimates, 1985
Creator: World Bank Group
License: https://datacatalog.worldbank.org/public-licenses

1985, as World Bank Group’s 2026 release gives it · stored as published, never rewritten

These are the World Bank’s line-up estimates of the share of people living on less than $3.00 a day: one figure for every country in every year, the numbers the Bank adds up into its regional and world poverty counts. Where a country ran no household survey in a year, the Bank estimates the figure from the surveys it did run.

Poverty Headcount at $3.00 a Day, Line-up Estimates, 1985 covers 169 countries. Equatorial Guinea is highest, at 99.44; 16 countries share the lowest reading, 0.00. The middle country reads 16.08. Against 1984, 141 values changed (60 up, 81 down), 1 country joined.

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Poverty Headcount at $3.00 a Day, Line-up Estimates · Data for 1985

HighestEquatorial Guinea

99.44

Lowest16 countries share it

0.00

Shaded by value in five groups of equal size, darkest at the lowest end.

169countries
1measure
1985the year it describes
149distinct values2 decimals, as published
Sep 29, 2026read from the publisher
CC BY 4.0licence

01Values only

The table

Every country and every column of Poverty Headcount at $3.00 a Day, Line-up Estimates, 1985, as published. The file carries values only, so no position is shown. “=” marks a shared position.

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Showing 25 of 169 countries · select a heading to sort

Poverty Headcount at $3.00 a Day, Line-up Estimates, 1985: every country, as published by World Bank Group.

Equatorial Guinea`GNQ`Middle Africa	99.44	extrapolation	consumption
Eswatini`SWZ`Southern Africa	93.68	extrapolation	consumption
Mozambique`MOZ`Eastern Africa	90.74	extrapolation	consumption
Myanmar`MMR`South-eastern Asia	90.50	extrapolation	consumption
Mali`MLI`Western Africa	90.04	extrapolation	consumption
Burkina Faso`BFA`Western Africa	88.43	extrapolation	consumption
China`CHN`Eastern Asia	87.90	interpolation	income
Guinea`GIN`Western Africa	87.36	extrapolation	consumption
Burundi`BDI`Eastern Africa	87.10	extrapolation	consumption
Indonesia`IDN`South-eastern Asia	86.56	interpolation	consumption
Niger`NER`Western Africa	85.92	extrapolation	consumption
Nepal`NPL`Southern Asia	82.31	extrapolation	income
Pakistan`PAK`Southern Asia	82.29	extrapolation	consumption
Central African Republic`CAF`Middle Africa	81.25	extrapolation	consumption
Rwanda`RWA`Eastern Africa	80.94	extrapolation	consumption
Ghana`GHA`Western Africa	80.42	extrapolation	consumption
DR Congo`COD`Middle Africa	78.83	extrapolation	consumption
Tanzania`TZA`Eastern Africa	76.94	extrapolation	consumption
Gambia`GMB`Western Africa	76.68	extrapolation	consumption
Senegal`SEN`Western Africa	76.55	extrapolation	consumption
Uganda`UGA`Eastern Africa	75.32	extrapolation	consumption
Benin`BEN`Western Africa	75.00	extrapolation	consumption
Madagascar`MDG`Eastern Africa	74.75	interpolation	consumption
Ethiopia`ETH`Eastern Africa	72.33	extrapolation	consumption
Uzbekistan`UZB`Central Asia	71.35	extrapolation	consumption
Cabo Verde`CPV`Western Africa	70.58	extrapolation	consumption
Papua New Guinea`PNG`Melanesia	69.21	extrapolation	consumption
Vietnam`VNM`South-eastern Asia	68.98	extrapolation	consumption
Chad`TCD`Middle Africa	67.56	extrapolation	consumption
Malawi`MWI`Eastern Africa	67.08	extrapolation	consumption
Saint Lucia`LCA`Caribbean	66.50	extrapolation	income
Bhutan`BTN`Southern Asia	63.66	extrapolation	consumption
Lesotho`LSO`Southern Africa	63.54	extrapolation	consumption
Togo`TGO`Western Africa	63.28	extrapolation	consumption
Haiti`HTI`Caribbean	63.05	extrapolation	income
Sierra Leone`SLE`Western Africa	62.12	extrapolation	consumption
Solomon Islands`SLB`Melanesia	61.86	extrapolation	consumption
Zambia`ZMB`Eastern Africa	61.30	extrapolation	consumption
Maldives`MDV`Southern Asia	58.44	extrapolation	consumption
Namibia`NAM`Southern Africa	58.42	extrapolation	income
Guinea-Bissau`GNB`Western Africa	54.40	extrapolation	consumption
Honduras`HND`Central America	53.30	extrapolation	income
Mauritania`MRT`Western Africa	51.38	extrapolation	consumption
India`IND`Southern Asia	51.30	interpolation	consumption
Botswana`BWA`Southern Africa	50.88	extrapolation	consumption
Nigeria`NGA`Western Africa	50.81	extrapolation	consumption
Laos`LAO`South-eastern Asia	47.21	extrapolation	consumption
Guatemala`GTM`Central America	46.50	extrapolation	income
Republic of the Congo`COG`Middle Africa	45.80	extrapolation	consumption
Philippines`PHL`South-eastern Asia	43.34	survey	consumption
Bangladesh`BGD`Southern Asia	43.08	interpolation	consumption
South Africa`ZAF`Southern Africa	42.56	extrapolation	consumption
Belize`BLZ`Central America	41.05	extrapolation	income
Guyana`GUY`South America	37.03	extrapolation	income
Sudan`SDN`Northern Africa	34.96	extrapolation	consumption
Cameroon`CMR`Middle Africa	33.68	extrapolation	consumption
Kenya`KEN`Eastern Africa	33.24	extrapolation	consumption
Brazil`BRA`South America	32.42	survey	income
Tuvalu`TUV`Polynesia	29.34	extrapolation	consumption
Thailand`THA`South-eastern Asia	29.08	interpolation	consumption
Sri Lanka`LKA`Southern Asia	28.24	survey	consumption
Zimbabwe`ZWE`Eastern Africa	27.64	extrapolation	consumption
Vanuatu`VUT`Melanesia	26.66	extrapolation	consumption
Kyrgyzstan`KGZ`Central Asia	25.39	extrapolation	income
Chile`CHL`South America	24.92	extrapolation	income
Comoros`COM`Eastern Africa	24.32	extrapolation	consumption
El Salvador`SLV`Central America	24.17	extrapolation	income
Ecuador`ECU`South America	23.98	extrapolation	income
Turkmenistan`TKM`Central Asia	23.64	extrapolation	consumption
Costa Rica`CRI`Central America	23.20	interpolation	income
Nicaragua`NIC`Central America	22.90	extrapolation	consumption
Bolivia`BOL`South America	22.04	extrapolation	income
Angola`AGO`Middle Africa	22.02	extrapolation	consumption
Tunisia`TUN`Northern Africa	21.60	survey	consumption
Morocco`MAR`Northern Africa	21.48	interpolation	consumption
Micronesia`FSM`Micronesia	21.12	extrapolation	consumption
Kiribati`KIR`Micronesia	20.62	extrapolation	consumption
Panama`PAN`Central America	20.30	interpolation	income
Colombia`COL`South America	20.23	extrapolation	income
Tajikistan`TJK`Central Asia	19.74	extrapolation	consumption
Iran`IRN`Southern Asia	19.18	extrapolation	consumption
Mongolia`MNG`Eastern Asia	19.18	extrapolation	consumption
Yemen`YEM`Western Asia	18.23	extrapolation	consumption
Liberia`LBR`Western Africa	16.71	extrapolation	consumption
Jamaica`JAM`Caribbean	16.08	extrapolation	consumption
Djibouti`DJI`Eastern Africa	14.89	extrapolation	consumption
Mexico`MEX`Central America	14.58	interpolation	income
Venezuela`VEN`South America	13.82	interpolation	income
Côte d’Ivoire`CIV`Western Africa	13.62	extrapolation	consumption
Mauritius`MUS`Eastern Africa	13.22	extrapolation	consumption
São Tomé and Príncipe`STP`Middle Africa	11.51	extrapolation	consumption
Türkiye`TUR`Western Asia	11.46	extrapolation	consumption
Samoa`WSM`Polynesia	10.53	extrapolation	consumption
Marshall Islands`MHL`Micronesia	9.72	extrapolation	consumption
Grenada`GRD`Caribbean	9.60	extrapolation	consumption
Egypt`EGY`Northern Africa	9.53	extrapolation	consumption
Fiji`FJI`Melanesia	9.25	extrapolation	consumption
Dominican Republic`DOM`Caribbean	8.92	extrapolation	income
Bosnia and Herzegovina`BIH`Southern Europe	8.63	extrapolation	consumption
Kazakhstan`KAZ`Central Asia	7.42	extrapolation	income
Algeria`DZA`Northern Africa	7.30	extrapolation	consumption
Malaysia`MYS`South-eastern Asia	6.94	interpolation	income
Tonga`TON`Polynesia	6.92	extrapolation	consumption
Gabon`GAB`Middle Africa	6.72	extrapolation	consumption
Iraq`IRQ`Western Asia	6.61	extrapolation	consumption
Peru`PER`South America	6.54	extrapolation	consumption
Uruguay`URY`South America	6.16	extrapolation	income
Ukraine`UKR`Eastern Europe	5.62	extrapolation	consumption
Moldova`MDA`Eastern Europe	4.39	extrapolation	consumption
Palestine`PSE`Western Asia	4.06	extrapolation	consumption
South Korea`KOR`Eastern Asia	3.60	extrapolation	income
Paraguay`PRY`South America	3.53	extrapolation	income
Armenia`ARM`Western Asia	3.48	extrapolation	income
Azerbaijan`AZE`Western Asia	3.23	extrapolation	consumption
Russia`RUS`Eastern Europe	3.14	extrapolation	consumption
Albania`ALB`Southern Europe	2.49	extrapolation	consumption
Suriname`SUR`South America	2.19	extrapolation	consumption
Syria`SYR`Western Asia	2.14	extrapolation	consumption
Portugal`PRT`Southern Europe	2.10	extrapolation	income
Lithuania`LTU`Northern Europe	1.73	extrapolation	income
Barbados`BRB`Caribbean	1.68	extrapolation	consumption
Japan`JPN`Eastern Asia	1.68	extrapolation	income
Seychelles`SYC`Eastern Africa	1.66	extrapolation	consumption
North Macedonia`MKD`Southern Europe	1.37	extrapolation	consumption
Greece`GRC`Southern Europe	1.30	extrapolation	income
Ireland`IRL`Northern Europe	1.30	extrapolation	income
Argentina`ARG`South America	1.12	interpolation	income
Australia`AUS`Australia and New Zealand	1.00	survey	income
Malta`MLT`Southern Europe	0.82	extrapolation	income
Canada`CAN`Northern America	0.66	survey	income
Switzerland`CHE`Western Europe	0.64	interpolation	income
Denmark`DNK`Northern Europe	0.60	extrapolation	income
United States`USA`Northern America	0.58	survey	income
Netherlands`NLD`Western Europe	0.54	interpolation	income
Israel`ISR`Western Asia	0.42	interpolation	income
Spain`ESP`Southern Europe	0.40	survey	income
France`FRA`Western Europe	0.36	interpolation	income
Belarus`BLR`Eastern Europe	0.32	extrapolation	income
Lebanon`LBN`Western Asia	0.31	extrapolation	consumption
Belgium`BEL`Western Europe	0.26	survey	income
Sweden`SWE`Northern Europe	0.26	interpolation	income
Italy`ITA`Southern Europe	0.24	interpolation	income
Montenegro`MNE`Southern Europe	0.22	extrapolation	consumption
Cyprus`CYP`Western Asia	0.20	extrapolation	income
Austria`AUT`Western Europe	0.16	extrapolation	income
Norway`NOR`Northern Europe	0.14	interpolation	income
Serbia`SRB`Southern Europe	0.12	extrapolation	consumption
Taiwan`TWN`Eastern Asia	0.09	interpolation	income
United Kingdom`GBR`Northern Europe	0.09	survey	income
Iceland`ISL`Northern Europe	0.08	extrapolation	income
Germany`DEU`Western Europe	0.04	extrapolation	income
Luxembourg`LUX`Western Europe	0.02	survey	income
Finland`FIN`Northern Europe	0.01	extrapolation	income
Bulgaria`BGR`Eastern Europe	0.00	extrapolation	consumption
Croatia`HRV`Southern Europe	0.00	extrapolation	income
Czechia`CZE`Eastern Europe	0.00	extrapolation	income
Estonia`EST`Northern Europe	0.00	extrapolation	income
Georgia`GEO`Western Asia	0.00	extrapolation	consumption
Hungary`HUN`Eastern Europe	0.00	extrapolation	income
Jordan`JOR`Western Asia	0.00	extrapolation	consumption
Latvia`LVA`Northern Europe	0.00	extrapolation	income
Nauru`NRU`Micronesia	0.00	extrapolation	consumption
Poland`POL`Eastern Europe	0.00	survey	income
Qatar`QAT`Western Asia	0.00	extrapolation	income
Romania`ROU`Eastern Europe	0.00	extrapolation	income
Slovakia`SVK`Eastern Europe	0.00	extrapolation	income
Slovenia`SVN`Southern Europe	0.00	extrapolation	income
Trinidad and Tobago`TTO`Caribbean	0.00	extrapolation	income
United Arab Emirates`ARE`Western Asia	0.00	extrapolation	income

02In 1985

At either end

The 5 countries at each end of the headline.

Highest

Lowest

Trinidad and Tobagoshared0.00
Sloveniashared0.00
Slovakiashared0.00
Romaniashared0.00
Qatarshared0.00

A higher value is the worse result. The middle country reads 16.08. “Shared” marks a value another country also holds.

031984 → 1985

Since 1984

+1 / −0countries joined / left
141values changed, of 168 in both
60 · 81rose · fell
27unchanged

Rose most

Philippines39.43 → 43.34+3.91
Kiribati16.74 → 20.62+3.88
Sudan31.67 → 34.96+3.29
Sierra Leone59.35 → 62.12+2.77
Kyrgyzstan22.93 → 25.39+2.46

Fell most

Chad74.18 → 67.56−6.62
Maldives63.20 → 58.44−4.76
Brazil36.94 → 32.42−4.52
China91.25 → 87.90−3.35
Saint Lucia69.66 → 66.50−3.16

+ Slovakia

04Caveats

Read before you use

How values are stored

One year of the 2026 release
Every year in this series comes from World Bank Group’s 2026 release, recalculated on one method, so a change from one year to the next is not a revision. It can differ from what was first published for 1985.
149 distinct values among 169
Values are stored exactly as published, to 2 decimals. 16 countries share 0.00. Countries sharing a value share a position too.
Nothing missing
Every one of the 169 countries has every column.

05The files

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Licence: CC BY 4.0 · what it allows, in plain words

Cite this edition

World Bank Group (1985). Poverty Headcount at $3.00 a Day, Line-up Estimates, 1985 [data set], describing 1985. As held by Nations Inquiry, https://nationsinquiry.com/datasets/poverty-headcount-lineup/1985

0644 held

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Poverty Headcount at $3.00 a Day, Line-up Estimates, 1984
168 countries
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Poverty Headcount at $3.00 a Day, Line-up Estimates, 1986
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