Coverage of social insurance programs in poorest quintile (% of population) - Country Ranking

Definition: Coverage of social insurance programs shows the percentage of population participating in programs that provide 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 Azerbaijan 56.98 2015
2 Armenia 55.91 2018
3 Russia 55.70 2017
4 Serbia 54.34 2015
5 Croatia 52.85 2014
6 Lithuania 52.56 2008
7 Ukraine 52.29 2018
8 Montenegro 51.86 2014
9 Hungary 49.86 2007
10 Moldova 49.53 2018
11 Ghana 49.30 2016
12 Bulgaria 48.20 2007
13 Mongolia 47.39 2016
14 Latvia 46.84 2009
15 Kyrgyz Republic 42.88 2013
16 Poland 41.54 2015
17 Belarus 41.43 2019
18 Chile 40.64 2017
19 Tajikistan 39.02 2011
20 Palau 38.90 2006
21 Albania 38.23 2012
22 Bosnia and Herzegovina 37.24 2015
23 Slovak Republic 37.03 2009
24 China 33.87 2013
25 Romania 32.63 2016
26 Samoa 31.81 2008
27 Kazakhstan 29.63 2017
28 Belize 29.37 2009
29 Turkey 26.33 2019
30 Jordan 24.92 2010
31 India 23.88 2011
32 Lebanon 23.83 2004
33 Argentina 22.53 2019
34 Uruguay 21.23 2019
35 Iraq 20.07 2012
36 Uzbekistan 18.28 2018
37 Egypt 17.73 2008
38 Rwanda 17.27 2013
39 Dominica 15.44 2002
40 Mauritius 12.54 2017
41 Gabon 11.45 2005
42 Brazil 10.54 2019
43 Mauritania 10.45 2008
44 Yemen 9.13 2005
45 Costa Rica 6.96 2019
46 Panama 5.76 2019
47 Côte d'Ivoire 5.43 2015
48 Djibouti 5.33 2012
49 Congo 4.89 2005
50 Mexico 4.62 2018
51 Fiji 4.57 2013
52 Venezuela 4.46 2006
53 Malaysia 4.29 2016
54 Ecuador 4.13 2019
55 Benin 3.60 2003
56 Syrian Arab Republic 3.57 2003
57 Philippines 3.27 2015
58 Cabo Verde 3.25 2007
59 Nicaragua 3.12 2014
60 Vietnam 3.11 2014
61 Indonesia 3.03 2019
62 Jamaica 2.71 2017
63 Namibia 2.65 2015
64 Sri Lanka 2.03 2016
65 Botswana 2.02 2015
66 El Salvador 2.01 2019
67 Pakistan 1.88 2018
68 Zimbabwe 1.80 2019
69 Dominican Republic 1.75 2019
70 Timor-Leste 1.65 2011
71 Myanmar 1.60 2017
72 Guatemala 1.49 2014
73 Bolivia 1.42 2019
74 Eswatini 1.37 2016
75 Mozambique 1.14 2014
76 The Gambia 1.13 2015
77 Paraguay 1.03 2019
78 Nigeria 0.99 2018
79 Solomon Islands 0.95 2005
80 Senegal 0.94 2011
81 Cameroon 0.91 2014
82 South Africa 0.91 2014
83 Peru 0.89 2019
84 Comoros 0.77 2004
85 Lao PDR 0.76 2018
86 Guinea 0.74 2012
87 Angola 0.72 2018
88 Dem. Rep. Congo 0.65 2012
89 Chad 0.64 2011
90 Liberia 0.59 2016
91 Bhutan 0.58 2017
92 Colombia 0.57 2019
93 Nepal 0.57 2010
94 Mali 0.56 2009
95 Thailand 0.48 2017
96 Bangladesh 0.48 2016
97 Cambodia 0.36 2013
98 Burkina Faso 0.30 2018
99 Lesotho 0.26 2017
100 Tanzania 0.26 2014
101 Kenya 0.22 2015
102 Zambia 0.20 2015
103 Malawi 0.18 2016
104 Papua New Guinea 0.18 2009
105 Afghanistan 0.16 2007
106 Ethiopia 0.09 2018
107 Honduras 0.09 2017
108 Uganda 0.03 2016
109 Niger 0.00 2014
110 Tonga 0.00 2009
110 Togo 0.00 2011
110 Sierra Leone 0.00 2018
110 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