Benefit incidence of social insurance programs to poorest quintile (% of total social insurance benefits) - Country Ranking

Definition: Benefit incidence of social insurance programs to poorest quintile shows the percentage of total social insurance benefits received by the poorest 20% of the population. Social insurance programs include old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.

Source: ASPIRE: The Atlas of Social Protection - Indicators of Resilience and Equity, The World Bank. Data are based on national representative household surveys. (datatopics.worldbank.org/aspire/)

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 India 21.24 2011
2 Lithuania 19.33 2008
3 Belize 18.95 2009
4 Tajikistan 17.76 2011
5 Liberia 17.28 2016
6 Azerbaijan 15.92 2015
7 Bulgaria 15.46 2007
8 Armenia 15.08 2018
9 Kyrgyz Republic 14.86 2013
10 Latvia 14.38 2009
11 Moldova 13.73 2018
12 Ukraine 13.03 2018
13 Albania 12.23 2012
14 Uzbekistan 12.08 2018
15 Serbia 11.68 2015
16 Belarus 11.23 2019
17 Bosnia and Herzegovina 11.08 2015
18 Samoa 11.02 2008
19 Hungary 10.76 2007
20 Rwanda 10.52 2013
21 Jordan 9.96 2010
22 Mongolia 9.95 2016
23 The Gambia 9.93 2015
24 Mauritania 9.93 2008
25 Croatia 9.40 2014
26 Montenegro 9.10 2014
27 Gabon 8.64 2005
28 Russia 8.42 2017
29 Poland 8.42 2015
30 Kazakhstan 8.21 2017
31 Yemen 8.08 2005
32 Iraq 8.02 2012
33 Palau 7.13 2006
34 Côte d'Ivoire 6.78 2015
35 Romania 6.62 2016
36 Slovak Republic 6.24 2009
37 Zimbabwe 5.70 2019
38 Egypt 5.69 2008
39 Myanmar 5.15 2017
40 Timor-Leste 4.87 2011
41 Djibouti 4.48 2012
42 Turkey 4.46 2019
43 Papua New Guinea 4.21 2009
44 Botswana 4.19 2015
45 Guinea 4.10 2012
46 Solomon Islands 4.09 2005
47 Chile 3.83 2017
48 Namibia 3.71 2015
49 Malaysia 3.67 2016
50 Afghanistan 3.66 2007
51 Congo 3.64 2005
52 Fiji 3.48 2013
53 Cabo Verde 3.32 2007
54 Dem. Rep. Congo 3.06 2012
55 Uruguay 2.98 2019
56 Argentina 2.95 2019
57 Mauritius 2.92 2017
58 Mozambique 2.58 2014
59 Eswatini 2.47 2016
60 Nicaragua 2.47 2014
61 Benin 2.47 2003
62 Sri Lanka 2.32 2016
63 China 2.16 2013
64 Kenya 2.15 2015
65 Bangladesh 2.10 2016
66 Lao PDR 2.05 2018
67 Pakistan 2.04 2018
68 Tanzania 1.88 2014
69 Jamaica 1.84 2017
70 Nigeria 1.74 2018
71 Costa Rica 1.73 2019
72 Vietnam 1.62 2014
73 Chad 1.60 2011
74 Brazil 1.56 2019
75 Dominica 1.56 2002
76 Syrian Arab Republic 1.51 2003
77 Mexico 1.47 2018
78 Bhutan 1.31 2012
79 El Salvador 1.16 2019
80 Panama 1.14 2019
81 Philippines 1.06 2015
82 Guatemala 0.99 2014
83 Dominican Republic 0.95 2019
84 Cameroon 0.90 2014
85 Ecuador 0.85 2019
86 Ethiopia 0.83 2018
87 Angola 0.82 2018
88 South Africa 0.73 2014
89 Lesotho 0.73 2017
90 Ghana 0.68 2012
91 Malawi 0.67 2016
92 Peru 0.57 2019
93 Comoros 0.54 2004
94 Paraguay 0.53 2019
95 Thailand 0.53 2017
96 Nepal 0.46 2010
97 Mali 0.40 2009
98 Burkina Faso 0.25 2018
99 Bolivia 0.23 2019
100 Senegal 0.23 2011
101 Colombia 0.19 2019
102 Uganda 0.15 2016
103 Cambodia 0.10 2013
104 Honduras 0.08 2017
105 Zambia 0.04 2015
106 Niger 0.01 2014
107 Tonga 0.00 2009
107 Togo 0.00 2011
107 Sierra Leone 0.00 2018
107 Haiti 0.00 2012

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Limitations and Exceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs. As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance. In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.

Aggregation method: Simple average

Periodicity: Annual