Coverage of social insurance programs (% 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 Hungary 57.12 2007
2 Russia 56.38 2017
3 Lebanon 53.66 2004
4 Croatia 52.56 2014
5 Armenia 52.33 2018
6 Serbia 52.10 2015
7 Azerbaijan 50.61 2015
8 Ukraine 49.76 2018
9 Slovak Republic 49.72 2009
10 Montenegro 47.93 2014
11 Moldova 47.83 2018
12 Bulgaria 47.72 2007
13 Ghana 47.66 2016
14 Belarus 47.48 2019
15 Latvia 45.72 2009
16 Chile 45.67 2017
17 Lithuania 45.04 2008
18 Mongolia 44.52 2016
19 Poland 43.92 2015
20 Romania 43.44 2016
21 Bosnia and Herzegovina 40.16 2015
22 Kyrgyz Republic 39.35 2013
23 Turkey 37.17 2019
24 Palau 36.42 2006
25 Albania 36.26 2012
26 China 35.58 2013
27 Uruguay 34.94 2019
28 Argentina 34.30 2019
29 Tajikistan 34.15 2011
30 Samoa 33.64 2008
31 Kazakhstan 31.52 2017
32 Brazil 30.51 2019
33 Jordan 28.23 2010
34 Belize 28.19 2009
35 Iraq 26.36 2012
36 Panama 21.41 2019
37 Egypt 21.30 2008
38 Uzbekistan 20.12 2018
39 Mauritius 19.08 2017
40 Costa Rica 18.35 2019
41 India 17.66 2011
42 Vietnam 15.25 2014
43 Mexico 13.86 2018
44 Nicaragua 13.71 2014
45 Gabon 13.42 2005
46 Dominica 13.37 2002
47 Ecuador 13.15 2019
48 Indonesia 10.86 2019
49 Colombia 10.82 2019
50 Rwanda 10.78 2013
51 Yemen 10.27 2005
52 Venezuela 10.24 2006
53 Peru 10.04 2019
54 Mauritania 9.23 2008
55 Philippines 8.92 2015
56 Fiji 8.92 2013
57 Congo 8.91 2005
58 Bolivia 8.54 2019
59 Djibouti 8.50 2012
60 Malaysia 8.38 2016
61 Senegal 8.32 2011
62 Syrian Arab Republic 8.19 2003
63 Côte d'Ivoire 7.92 2015
64 Sri Lanka 7.84 2016
65 Jamaica 7.00 2017
66 El Salvador 6.71 2019
67 Benin 6.63 2003
68 Pakistan 6.45 2018
69 Dominican Republic 6.31 2019
70 Cabo Verde 6.00 2007
71 Eswatini 5.71 2016
72 Paraguay 5.65 2019
73 Myanmar 5.35 2017
74 Nepal 5.26 2010
75 Zimbabwe 4.81 2019
76 Guatemala 3.99 2014
77 Namibia 3.85 2015
78 Mozambique 3.81 2014
79 Botswana 3.77 2015
80 Angola 3.63 2018
81 Thailand 3.50 2017
82 Cameroon 3.41 2014
83 Honduras 3.37 2017
84 South Africa 3.35 2014
85 Nigeria 3.31 2018
86 Togo 3.01 2011
87 Burkina Faso 2.70 2018
88 Chad 2.48 2011
89 Guinea 2.28 2012
90 Lao PDR 2.16 2018
91 Comoros 1.88 2004
92 Cambodia 1.87 2013
93 Dem. Rep. Congo 1.60 2012
94 The Gambia 1.47 2015
95 Niger 1.37 2014
96 Mali 1.31 2009
97 Tanzania 1.29 2014
98 Tonga 1.29 2009
99 Ethiopia 1.25 2018
100 Timor-Leste 1.24 2011
101 Solomon Islands 1.21 2005
102 Kenya 1.19 2015
103 Lesotho 1.16 2017
104 Papua New Guinea 1.01 2009
105 Bangladesh 0.95 2016
106 Zambia 0.92 2015
107 Sierra Leone 0.91 2018
108 Bhutan 0.89 2017
109 Uganda 0.57 2016
110 Malawi 0.57 2016
111 Afghanistan 0.54 2007
112 Liberia 0.50 2016
113 Haiti 0.37 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