Methodology
WBG Global Aging Dashboard – Data, frameworks, and scoring systems
Three Frameworks at a Glance
Aging Challenges Dashboard (Quantitative)
The foundational layer comprises 23 quantitative indicators spanning 5 thematic areas: aging level, speed, and resources; productive aging; healthy aging; protected aging; and aged financing. These are drawn from the World Bank, IHME, WHO, OECD, and UN World Population Prospects, standardized to quintiles, and displayed in a heatmap to enable rapid cross-country comparison of aging-related pressures.
Aging Policy Index (67 Binary & Continuous Indicators)
The policy readiness layer measures countries' current policy and institutional response capacity across 3 pillars (Healthy, Productive, Protected). It comprises 67 indicators—61 binary, 6 continuous— harmonized with Lokshin et al. (2024). Seven countries match the published paper exactly. Organized into three cross-cutting themes: policy framework, legal entitlements, and financial mechanisms.
Policy Prioritization Maps (Pressure × Readiness)
Three interactive maps position all 207 countries on a 2×2 framework: Aging Pressure (Y-axis) vs. Pillar Readiness (X-axis), with separate maps for each pillar (Healthy, Productive, Protected). Median splits define four quadrants—Urgent reform priority, Manage visible pressure, Build foundations early, Maintain and monitor—translating country positioning into actionable policy guidance.
Country Coverage
The dashboard covers 207 countries and territories. Ten territories are excluded per World Bank standard practice: American Samoa (ASM), British Virgin Islands (VGB), Gibraltar (GIB), Guam (GUM), Monaco (MCO), New Caledonia (NCL), Northern Mariana Islands (MNP), Sint Maarten (MAF), Taiwan (TWN), and Virgin Islands (VIR).
Regional classification:Israel is mapped to Europe & Central Asia to align with official World Bank regional groupings.
All datasets are reconciled to ISO 3166-1 alpha-3 country codes and updated as new data becomes available from international agencies.
Aging Pressure Score (Y-axis)
The Aging Pressure Score quantifies current and projected demographic aging burden. It is computed as the unweighted percentile-rank average of six indicators:
- Share aged 65+ (2024)
- Share aged 80+ (2024)
- Old-age dependency ratio—OADR (2024)
- Change in share aged 65+, 2024–2055
- Change in share aged 80+, 2024–2055
- Change in OADR, 2024–2055
Methodology
Each indicator is rank-converted to a 0–100 percentile (0 = lowest pressure, 100 = highest) across the 207-country panel. The six percentiles are then averaged—with no explicit weights—to produce the final Aging Pressure Score. Missing data points are excluded; countries with at least three valid indicators receive a score. A higher score indicates greater demographic aging pressure.
Data sources: UN World Population Prospects 2024 (medium variant); World Bank WDI.
Pillar Readiness Scores (X-axis)
Each pillar has a dedicated Readiness Score combining the API pillar score (0–100) with sector-specific indicators. All inputs are converted to percentile ranks and unweighted-averaged.
Healthy Aging Readiness
- API Healthy Aging score (0–100) — from 28 policy indicators in the Aging Policy Index
- Health-adjusted life expectancy at 60 (HALE_60) — higher is better
- NCD mortality as % of all deaths — inverted (lower is better)
- Out-of-pocket health expenditure poverty rate — inverted (lower is better)
- Healthcare quality index — higher is better
- UHC health coverage for NCDs — higher is better
- UHC Service Coverage Index (WHO GHO) — higher is better; 192 countries (Phase 2.3, 2026-04-27)
- Health workforce density (physicians + nurses per 1,000) — higher is better; 205 countries (Phase 2.2)
Productive Aging Readiness
- API Productive Aging score (0–100) — from 22 policy indicators in the Aging Policy Index
- Older-worker labor force participation (ages 55–64, %) — higher is better
- Female-to-male LFPR ratio — inverted (gap = worse readiness)
- Future education (human capital proxy) — higher is better
- Internet use (% population) — higher is better; 205 countries (Phase 2.2)
- Vulnerable employment (% of total employment) — inverted (higher = worse); 205 countries (Phase 2.2)
Protected Aging Readiness
- API Protected Aging score (0–100) — from 17 policy indicators in the Aging Policy Index
- Contributory pension coverage (% of labor force) — higher is better
- Non-contributory pension coverage (% of elderly) — higher is better
- Old-age poverty rate — inverted (higher poverty = worse readiness)
- Savings worry (share anxious about retirement) — inverted
Aggregation Logic
All inputs are percentile-ranked across the 207-country panel. Inverted indicators are flipped (100 − rank) so that “higher = better” uniformly. The final Pillar Readiness Score is the unweighted average of all available percentiles for that pillar. Countries with fewer inputs still receive a comparable score from their available data.
Four-Quadrant Classification
Within each of the three maps, the median Aging Pressure Score and median Pillar Readiness Score divide countries into four quadrants, each with a distinct policy implication:
| Quadrant | Pressure | Readiness | Policy Meaning |
|---|---|---|---|
| Q1 (Top-left) | High | Low | Urgent reform priority — Strong aging pressure but weak readiness; reform now |
| Q2 (Top-right) | High | High | Manage visible pressure — Already aging; sustain, improve, fine-tune |
| Q3 (Bottom-left) | Low | Low | Build foundations early — Time to prepare; lay foundations now |
| Q4 (Bottom-right) | Low | High | Maintain and monitor — Strong readiness; track future pressures |
Median thresholds
Computed per map from the 207-country distribution. Median Aging Pressure Score and median Pillar Readiness Score are recalculated quarterly as new data is integrated.
Three-Cluster Trajectory Framework
Alongside the Pressure × Readiness positioning framework, the dashboard employs a three-cluster trajectory lens that categorizes countries by their aging pathway. See docs/CLUSTER_FRAMEWORK.md.
Cluster A — Build Foundations Early
Examples: Ethiopia, Ghana, Kenya. Young populations (low pressure) with weak systems. Priority: formalization, primary health care, NCD prevention, contributory pension expansion.
Cluster B — Accelerate Reform While Pressures Rise
Examples:Brazil, Egypt, India, Sri Lanka, Colombia, Costa Rica. Mid-range pressure & readiness with rapid aging. Priority: parametric pension reform, LTC expansion, NCD-focused UHC, labor-market adaptation.
Cluster C — Manage Visible Aging Pressure Now
Examples: China, Croatia, Thailand, Uruguay. High pressure with strong readiness. Priority: fiscal sustainability, phased retirement, integrated LTC, healthy life expectancy.
A country's cluster is determined by overall trajectory and relative readiness positions across pillars, while its urgency within any specific pillar is read off that pillar's Pressure × Readiness map. The two lenses are complementary: positioning shows current status; cluster shows direction.
Projections Methodology
Three projection pages at /projections/{healthcare,pension,ltc} model future spending (2055) using a demographic-only multiplier:
spending_2055 = current_spending × (share_65+_2055 / share_65+_2024)
Healthcare & Pension
Multiplier: ratio of share aged 65+ in 2055 to 2024. Assumes constant per-elderly spending and no behavioral adaptation, policy reform, or income elasticity.
Long-term Care
Multiplier: ratio of share aged 80+ in 2055 to 2024, as a proxy for LTC demand. Pending Phase 2.4 data pull of actual LTC spending by country; currently unavailable outside OECD.
Transparency & Limitations
These projections show demographic pressure only—the isolated effect of aging population structure on spending headcount. They do not model policy reform, income growth, efficiency improvements, or behavioral changes. Users should interpret them as baseline scenarios absent intervention. Full methodology is disclosed on each projection page.
Economic Growth Decomposition
The Economic Growth page under Macro and Fiscal Impacts visualises a tool developed by Diego Wachs (Aging and Pensions Global Solutions Group, Social Policy Global Practice, World Bank) that decomposes the impact of population aging on GDP-per-capita growth into transparent demographic channels.
Short methodological description
The framework starts from a Solow–Swan growth model with a Cobb–Douglas production function, dividing by total population and by the working-age population to express growth in GDP per capita as the sum of four log-linear growth terms:
The tool quantifies the three channels through which population aging operates by comparing observed dynamics with a counterfactual in which the age composition of the population stays constant:
- Quantity effect (g(W/N)) — the impact of a shrinking working-age share on output per capita.
- Capital deepening (α·g(K/L)) — the mitigating effect of a higher capital-to-labour ratio as the workforce contracts.
- Productivity effect (g(A_dem)) — the effect of an older workforce age structure on total factor productivity, using age-specific productivity elasticities from Guénette and Shao (2025).
Historical series come from Penn World Table 10 (Feenstra, Inklaar & Timmer 2015); population projections beyond 2019 are indexed to the United Nations World Population Prospects 2024. Two scenarios are reported. The Baseline includes only the quantity effect and capital deepening, treating the labour-supply channel as a mechanical, well-identified consequence of past fertility. The Pessimistic scenario adds the productivity channel, which is more uncertain and therefore treated as a downside.
The estimates are a first-order, structural decomposition rather than an econometric identification of causal effects. They abstract from behavioural responses (notably labour-force participation), use a Cobb–Douglas production function with constant factor shares, hold capital growth fixed across the aging and counterfactual scenarios (conservative for capital deepening), and operate at the aggregate level without sectoral detail or modelled policy reforms.
Downloadable methodological note
The full nine-page methodological note prepared by Diego Wachs — including the analytical derivation, computation assumptions, illustrative Costa Rica results, limitations, and the annex on exogenous versus endogenous capital accumulation — is available as a PDF.
Download the methodological note (PDF)Policy Recommendations & Reference Library
Both datasets are built exclusively from public literature. No internal or confidential World Bank country reports are cited.
Allowed Sources
- WHO, OECD, ILO, IMF, World Bank — public publications and databases
- Peer-reviewed journals with DOIs
- Publicly released national strategy documents
- Regional development banks (AfDB, ADB, IDB, ECLAC, EU)
Enforcement
The parse-policy-recommendations.ts parser enforces this rule at build time. It scans all primarySource, sourceDoc, and section fields against a blocklist of confidential-report patterns and fails the build if any match is detected.
See POLICY_RECOMMENDATIONS_METHODOLOGY.md for detailed sourcing rules and country-by-country coverage roadmap.
Data Sources & Version History
| Dataset | Source(s) | Latest Year | Countries | Version |
|---|---|---|---|---|
| Quantitative Indicators (23) | WB WDI, IHME GBD, WHO, OECD, UN WPP | 2024 | 207 | 2.2.0 |
| Aging Policy Index (67 indicators) | Country-level policy data + Lokshin et al. (2024) | 2026-04 | 207 | 2.1 |
| Policy Recommendations (60) | Public literature (WHO, OECD, ILO, WB) | 2026-04 | 207 (generic); 9 with country evidence | 1.1.0 |
| UN WPP Projections (population 2055) | UN World Population Prospects 2024 (medium variant) | Projection: 2055 | 282 (237 with 2055 data) | 2024 |
| Readiness Inputs (UHC, workforce, etc.) | WHO GHO, WB WDI, ILO ILOSTAT | 2024 | 192–205 | Phase 2.2–2.3 |
| Literature Reference Library (seed) | Public literature | 2026-04 | 19 URLs (seed only) | 0.1.0 |
Citation
For the full dashboard:
World Bank Group (2026). Global Aging Dashboard. https://aging.ramyzeid.com. Accessed [date].
For specific datasets, use the respective original sources:
- UN WPP: UN Department of Economic and Social Affairs. (2024). World Population Prospects.
- IHME GBD: Global Burden of Disease Study; IHME.
- WHO: WHO Global Health Observatory.
- OECD: OECD.Stat.
- World Bank: WDI, ASPIRE, or relevant World Bank publications.
- Aging Policy Index: Lokshin et al. (2024) and dashboard country-level updates.
Known Limitations & Roadmap
Projection Scenarios
All demographic projections use the UN WPP 2024 medium variant only. High and low fertility scenarios are not included. Projections assume no policy change, income growth effects, or behavioral adaptation.
Data Gaps in Readiness Inputs
UHC Service Coverage Index (192 countries), health workforce density (205), internet use (205), and vulnerable employment (205) have varying coverage. Sub-Saharan Africa and some least-developed countries have limited data; readiness scores in those regions are computed from available inputs.
Long-term Care Spending
LTC spending data (% GDP) is available only for OECD countries. Projections for non-OECD economies use share aged 80+ as a proxy. Phase 2.4 (pending) will attempt to extend LTC spending coverage.
Caregiver & Protection Systems Index
No composite index yet. The Protected Aging Readiness Score uses pension and income-protection policies; caregiver systems, social-care workforce, and unpaid-care infrastructure require manual curation and will be added in Phase 3+.
Policy Recommendations Coverage
v1.1.0 (2026-04-25) contains 60 generic recommendations sourced from public literature. Country- specific evidence is available for Costa Rica, Ethiopia, Ghana, India, Kenya, Saudi Arabia, and Thailand. Expanding to Brazil, China, Croatia, Egypt, Colombia, Sri Lanka, and Uruguay in v1.2.0.
Upcoming Work
- Phase 2.4: LTC spending data pull (OECD + national sources)
- Phase 3: Caregiver / protection systems manual index
- Phase 4: Landing page redesign + navigation restructuring
- Phase 5: Policy Recommendations literature extension (14 priority countries)
- Phase 6: Expert-panel Delphi scoring of policy recommendations