Coverage of social insurance programs in 2nd 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 Russia 61.82 2017
2 Hungary 58.58 2007
3 Serbia 57.59 2015
4 Azerbaijan 53.57 2015
5 Moldova 53.50 2018
6 Armenia 53.49 2018
7 Bulgaria 53.42 2007
8 Ukraine 52.36 2018
9 Latvia 51.71 2009
10 Croatia 50.52 2014
11 Slovak Republic 50.46 2009
12 Ghana 49.11 2016
13 Chile 48.66 2017
14 Lithuania 47.83 2008
15 Mongolia 47.47 2016
16 Montenegro 46.36 2014
17 Romania 46.14 2016
18 Belarus 45.81 2019
19 Lebanon 43.30 2004
20 Poland 43.05 2015
21 Bosnia and Herzegovina 42.86 2015
22 Palau 40.28 2006
23 Kyrgyz Republic 38.39 2013
24 Albania 37.61 2012
25 Tajikistan 34.49 2011
26 Samoa 33.36 2008
27 Uruguay 33.07 2019
28 Turkey 32.36 2019
29 China 31.54 2013
30 Argentina 30.63 2019
31 Belize 30.27 2009
32 Kazakhstan 29.47 2017
33 Jordan 25.95 2010
34 Iraq 25.63 2012
35 Brazil 25.42 2019
36 India 21.56 2011
37 Uzbekistan 19.05 2018
38 Panama 15.65 2019
39 Mauritius 14.90 2017
40 Gabon 14.53 2005
41 Egypt 14.18 2008
42 Costa Rica 13.48 2019
43 Rwanda 11.73 2013
44 Dominica 11.56 2002
45 Yemen 10.39 2005
46 Mauritania 10.10 2008
47 Nicaragua 9.51 2014
48 Mexico 9.35 2018
49 Congo 8.76 2005
50 Djibouti 8.65 2012
51 Ecuador 8.05 2019
52 Malaysia 7.59 2016
53 Vietnam 7.02 2014
54 Syrian Arab Republic 6.88 2003
55 Fiji 6.55 2013
56 Côte d'Ivoire 6.44 2015
57 Eswatini 6.08 2016
58 Cabo Verde 5.94 2007
59 Zimbabwe 5.75 2019
60 Indonesia 5.47 2019
61 Venezuela 5.46 2006
62 Philippines 4.86 2015
63 Jamaica 4.56 2017
64 Peru 4.35 2019
65 Sri Lanka 4.26 2016
66 Dominican Republic 4.09 2019
67 Myanmar 4.09 2017
68 Pakistan 3.92 2018
69 Senegal 3.84 2011
70 Namibia 3.70 2015
71 Benin 3.53 2003
72 Bolivia 3.43 2019
73 El Salvador 2.83 2019
74 Colombia 2.80 2019
75 Nepal 2.73 2010
76 Angola 2.15 2018
77 Mozambique 2.08 2014
78 Nigeria 2.07 2018
79 Cameroon 1.99 2014
80 South Africa 1.96 2014
81 Chad 1.92 2011
82 The Gambia 1.52 2015
83 Papua New Guinea 1.25 2009
84 Comoros 1.21 2004
85 Cambodia 1.19 2013
86 Botswana 1.14 2015
87 Guatemala 1.14 2014
88 Lao PDR 1.04 2018
89 Paraguay 0.91 2019
90 Honduras 0.79 2017
91 Mali 0.77 2009
92 Togo 0.77 2011
93 Tonga 0.76 2009
94 Kenya 0.75 2015
95 Guinea 0.69 2012
96 Thailand 0.65 2017
97 Dem. Rep. Congo 0.60 2012
98 Burkina Faso 0.54 2018
99 Timor-Leste 0.52 2011
100 Bangladesh 0.48 2016
101 Sierra Leone 0.41 2018
102 Zambia 0.35 2015
103 Lesotho 0.35 2017
104 Ethiopia 0.30 2018
105 Bhutan 0.30 2017
106 Solomon Islands 0.30 2005
107 Afghanistan 0.29 2007
108 Liberia 0.21 2016
109 Uganda 0.19 2016
110 Tanzania 0.16 2014
111 Haiti 0.14 2012
112 Malawi 0.01 2016
113 Niger 0.00 2014

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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