Social protection
ILO: at least one benefit
Effective coverage by at least one social-protection benefit. Administrative ILO coverage is a different construct from ASPIRE survey participation.
% of population
ILO SSI / UN SDG · MIXED VINTAGESSEA-11 · Singapore is regional context, outside the peer five. Country order follows ILO at-least-one coverage; each panel retains its own definition. Scales stay fixed when filtering.
| Country | % of population 0100 | Year | Source & notes |
|---|---|---|---|
| Singapore | 100.0 | 2023 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2023 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 100.0. |
| Thailand | 70.1 | †2020 · OLDER | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2020 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 70.1. |
| Indonesia | 54.3 | 2021 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2021 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 54.3. |
| Vietnam | 38.3 | 2022 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2022 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 38.3. |
| Brunei | 36.0 | 2021 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2021 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 36.0. |
| Philippines | 34.9 | 2022 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2022 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 34.9. |
| Malaysia | 29.2 | 2023 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2023 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 29.2. |
| Timor-Leste | 27.0 | 2024 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2024 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 26.9880583. |
| Cambodia | 20.8 | 2022 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2022 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 20.8. |
| Laos | 15.5 | 2021 | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2021 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 15.5. |
| MyanmarConflict / reporting caveat | 6.3 | †2019 · OLDER | ILO Social Security Inquiry via UN SDG SI_COV_BENFTS (SDG 1.3.1 effective coverage) · year 2019 · as_of 2026-09-06 Observation notesProportion of population covered by at least one social protection benefit (effective coverage). ILO construct — do not mix with ASPIRE household-survey coverage on the same axis. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 6.3. |
Philippines highlighted. Bars start at zero; gaps have no bars. † identifies older observations.
ILO: pension coverage
People above statutory pensionable age receiving a pension. PH is second among PH / MY / TH / VN / ID; observation years differ.
% above statutory pensionable age
ILO SSI / UN SDG · MIXED VINTAGESSEA-11 · Singapore is regional context, outside the peer five. Country order follows ILO at-least-one coverage; each panel retains its own definition. Scales stay fixed when filtering.
| Country | % above statutory pensionable age 0100 | Year | Source & notes |
|---|---|---|---|
| Singapore | 37.3 | 2021 | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2021 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 37.3. |
| Thailand | 82.6 | †2020 · OLDER | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2020 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 82.6. |
| Indonesia | 31.2 | 2021 | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2021 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 31.2. |
| Vietnam | 40.9 | †2019 · OLDER | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2019 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 40.9. |
| Brunei | 100.0 | 2021 | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2021 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 100.0. |
| Philippines | 65.6 | 2021 | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2021 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 65.6. |
| Malaysia | 18.5 | 2023 | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2023 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 18.5. |
| Timor-Leste | 91.6 | 2024 | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2024 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 91.62382451. |
| Cambodia | 8.1 | †2020 · OLDER | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2020 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 8.1. |
| Laos | 7.0 | 2021 | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2021 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 7.0. |
| MyanmarConflict / reporting caveat | 0.9 | †2016 · OLDER | ILO Social Security Inquiry via UN SDG SI_COV_PENSN (SDG 1.3.1 old-age) · year 2016 · as_of 2026-09-06 Observation notesProportion of persons above statutory pensionable age receiving a pension. Includes contributory and non-contributory where reported by ILO. Sex=BOTHSEX. Source tag: ILO - Social Security Inquiry Database. Original CSV value: 0.9. |
Philippines highlighted. Bars start at zero; gaps have no bars. † identifies older observations.
ASPIRE: social protection and labour coverage
Household-survey programme participation, not ILO effective coverage. PH’s 2018 observation is the lowest of the peer five; this is not a same-year comparison.
% of population · direct and indirect beneficiaries
WDI ASPIRE · MIXED VINTAGESSEA-11 · Singapore is regional context, outside the peer five. Country order follows ILO at-least-one coverage; each panel retains its own definition. Scales stay fixed when filtering.
| Country | % of population · direct and indirect beneficiaries 0100 | Year | Source & notes |
|---|---|---|---|
| Singapore | —GAP · not zero | — | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year not available · as_of 2026-09-06 Observation notesGAP: no ASPIRE/WDI observation for this economy (often high-income or survey not in ASPIRE). Coverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. Original CSV value: not supplied. |
| Thailand | 87.2 | 2021 | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2021 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. Original CSV value: 87.1883451210434. |
| Indonesia | 65.1 | 2022 | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2022 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. Original CSV value: 65.0930131345136. |
| Vietnam | 89.4 | 2020 | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2020 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. Older vintage — badge year. Original CSV value: 89.4056063238231. |
| Brunei | —GAP · not zero | — | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year not available · as_of 2026-09-06 Observation notesGAP: no ASPIRE/WDI observation for this economy (often high-income or survey not in ASPIRE). Coverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. Original CSV value: not supplied. |
| Philippines | 43.0 | †2018 · OLDER | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2018 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. STALE vintage — badge year on chart. Original CSV value: 43.0410765516831. |
| Malaysia | 76.7 | †2016 · OLDER | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2016 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. STALE vintage — badge year on chart. Original CSV value: 76.675353709024. |
| Timor-Leste | 35.3 | †2011 · OLDER | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2011 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. STALE vintage — badge year on chart. Original CSV value: 35.3284098277873. |
| Cambodia | 3.1 | †2013 · OLDER | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2013 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. STALE vintage — badge year on chart. Original CSV value: 3.08597052937646. |
| Laos | 2.2 | †2018 · OLDER | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2018 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. STALE vintage — badge year on chart. Original CSV value: 2.15922345964383. |
| MyanmarConflict / reporting caveat | 14.0 | †2017 · OLDER | World Bank WDI ASPIRE per_allsp.cov_pop_tot · year 2017 · as_of 2026-09-06 Observation notesCoverage of social protection and labor programs (% of population; direct+indirect beneficiaries). Household-survey ASPIRE — mixed/stale vintages; badge year. BRN/SGP typically not in ASPIRE. STALE vintage — badge year on chart. Original CSV value: 13.9684258982423. |
Philippines highlighted. Bars start at zero; gaps have no bars. † identifies older observations.
ASPIRE: benefit adequacy
Transfers as a share of beneficiary welfare, not population coverage. Laos’s high adequacy accompanies very low coverage; Timor-Leste’s 2007 observation is extremely stale.
% of beneficiary household welfare
WDI ASPIRE · MIXED VINTAGESSEA-11 · Singapore is regional context, outside the peer five. Country order follows ILO at-least-one coverage; each panel retains its own definition. Scales stay fixed when filtering.
| Country | % of beneficiary household welfare 0100 | Year | Source & notes |
|---|---|---|---|
| Singapore | —GAP · not zero | — | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year not available · as_of 2026-09-06 Observation notesGAP: no ASPIRE/WDI observation for this economy (often high-income or survey not in ASPIRE). Adequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. Original CSV value: not supplied. |
| Thailand | 78.5 | 2021 | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2021 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. Original CSV value: 78.454776939718. |
| Indonesia | 9.4 | 2022 | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2022 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. Original CSV value: 9.37505195825019. |
| Vietnam | 13.6 | 2020 | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2020 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. Older vintage — badge year. Original CSV value: 13.5742808062998. |
| Brunei | —GAP · not zero | — | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year not available · as_of 2026-09-06 Observation notesGAP: no ASPIRE/WDI observation for this economy (often high-income or survey not in ASPIRE). Adequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. Original CSV value: not supplied. |
| Philippines | 16.9 | †2018 · OLDER | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2018 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. STALE vintage — badge year on chart. Original CSV value: 16.9409583177251. |
| Malaysia | 7.7 | †2016 · OLDER | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2016 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. STALE vintage — badge year on chart. Original CSV value: 7.69487780867106. |
| Timor-Leste | 9.8 | †2007 · OLDER | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2007 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. STALE vintage — badge year on chart. Original CSV value: 9.81442079884581. |
| Cambodia | 12.5 | †2013 · OLDER | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2013 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. STALE vintage — badge year on chart. Original CSV value: 12.5388146489003. |
| Laos | 90.9 | †2018 · OLDER | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2018 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. STALE vintage — badge year on chart. Original CSV value: 90.8567064704859. |
| MyanmarConflict / reporting caveat | 8.7 | †2017 · OLDER | World Bank WDI ASPIRE per_allsp.adq_pop_tot · year 2017 · as_of 2026-09-06 Observation notesAdequacy of SPL benefits among beneficiary households (transfer amount as % of beneficiary welfare). Not the same as coverage; high adequacy can coexist with low coverage. STALE vintage — badge year on chart. Original CSV value: 8.65556803734574. |
Philippines highlighted. Bars start at zero; gaps have no bars. † identifies older observations.
ASPIRE: safety-net reach in the poorest quintile
Coverage among the poorest fifth, not the whole population. PH’s 2018 observation is lowest among the peer five. Brunei, Singapore, Cambodia and Laos have gaps.
% of poorest quintile · pre-transfer welfare
WDI ASPIRE · MIXED VINTAGESSEA-11 · Singapore is regional context, outside the peer five. Country order follows ILO at-least-one coverage; each panel retains its own definition. Scales stay fixed when filtering.
| Country | % of poorest quintile · pre-transfer welfare 0100 | Year | Source & notes |
|---|---|---|---|
| Singapore | —GAP · not zero | — | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year not available · as_of 2026-09-06 Observation notesGAP: no ASPIRE/WDI observation for this economy (often high-income or survey not in ASPIRE). Coverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. Original CSV value: not supplied. |
| Thailand | 97.1 | 2021 | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year 2021 · as_of 2026-09-06 Observation notesCoverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. Original CSV value: 97.0817980530811. |
| Indonesia | 69.4 | 2022 | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year 2022 · as_of 2026-09-06 Observation notesCoverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. Original CSV value: 69.3947287707268. |
| Vietnam | 88.6 | 2020 | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year 2020 · as_of 2026-09-06 Observation notesCoverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. Older vintage — badge year. Original CSV value: 88.5530031653385. |
| Brunei | —GAP · not zero | — | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year not available · as_of 2026-09-06 Observation notesGAP: no ASPIRE/WDI observation for this economy (often high-income or survey not in ASPIRE). Coverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. Original CSV value: not supplied. |
| Philippines | 57.2 | †2018 · OLDER | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year 2018 · as_of 2026-09-06 Observation notesCoverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. STALE vintage — badge year on chart. Original CSV value: 57.2387197621073. |
| Malaysia | 97.6 | †2016 · OLDER | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year 2016 · as_of 2026-09-06 Observation notesCoverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. STALE vintage — badge year on chart. Original CSV value: 97.6300839192343. |
| Timor-Leste | 41.4 | †2011 · OLDER | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year 2011 · as_of 2026-09-06 Observation notesCoverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. STALE vintage — badge year on chart. Original CSV value: 41.3972437968797. |
| Cambodia | —GAP · not zero | — | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year not available · as_of 2026-09-06 Observation notesGAP: no ASPIRE/WDI observation for this economy (often high-income or survey not in ASPIRE). Coverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. Original CSV value: not supplied. |
| Laos | —GAP · not zero | — | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year not available · as_of 2026-09-06 Observation notesGAP: no ASPIRE/WDI observation for this economy (often high-income or survey not in ASPIRE). Coverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. Original CSV value: not supplied. |
| MyanmarConflict / reporting caveat | 10.4 | †2017 · OLDER | World Bank WDI ASPIRE per_sa_allsa.cov_q1_tot · year 2017 · as_of 2026-09-06 Observation notesCoverage of social safety nets among the poorest quintile (pre-transfer welfare). Targeting / progressive reach metric. STALE vintage — badge year on chart. Original CSV value: 10.3804112290422. |
Philippines highlighted. Bars start at zero; gaps have no bars. † identifies older observations.
Key findings from this pack
- PH pension coverage is second among the peer five, while its older ASPIRE reach is the lowest.
- ILO effective coverage and ASPIRE household-survey participation are different constructs.
- Adequacy describes transfers among beneficiaries, not the proportion of people covered.
- PH ASPIRE observations are from 2018; Brunei and Singapore’s ASPIRE cells remain intentional gaps.
Cite this page
ASEAN in Data (2026). Social protection. /topics/social-protection
Methods & coverage
ILO and ASPIRE are separate systems
ILO Social Security Inquiry via UN SDG measures effective coverage by at least one benefit and pension receipt above statutory pensionable age. ASPIRE uses household surveys to measure programme participation, including direct and indirect beneficiaries. Their levels are not interchangeable; missing ASPIRE observations are never replaced with ILO coverage.
Reach is not adequacy
ASPIRE adequacy measures transfers as a share of beneficiary household welfare, not the share of the population covered. Laos illustrates high adequacy alongside very low reach. Poorest-quintile safety-net coverage uses pre-transfer welfare to identify the poorest fifth. It is distinct from population-wide safety-net coverage.
Mixed vintages and intentional gaps
Philippine ASPIRE observations are †2018; peer comparisons span different survey years. Myanmar’s pension observation is †2016, and its ILO at-least-one observation is †2019. Timor-Leste ASPIRE coverage is †2011 and adequacy is †2007. Every row retains its original source, year and as_of. Older-year marks flag ILO observations before 2021 and ASPIRE observations before 2020; unmarked years are still not necessarily current.
Brunei and Singapore have no ASPIRE observations by design. Cambodia and Laos also lack safety-net and poorest-quintile safety-net observations. Timor-Leste has no ASPIRE social-insurance observation. Empty cells are gaps, never zeros. Singapore’s ILO reporting reflects its scheme structure and does not fill its ASPIRE cells.
Original coverage & vintage notes · Pack definitions · Source provenance