Methodology & Data Sources

Overview of Our Approach

Afforvia aggregates, harmonizes, and analyzes secondary data from recognized international statistical organizations. We do not conduct primary surveys or collect original data. Our role is to transform publicly available data into accessible, comparable indices that illuminate differences in household purchasing power across countries and regions.

All methodological choices are documented here in full. Where we have made judgment calls — for example, in how to handle missing data or how to define income quintile boundaries across data systems — we explain the rationale and note alternatives we considered.

Economic Indicators Used

Our purchasing power analyses draw on the following categories of economic indicators:

Price-to-Income Ratio (PIR) Calculation

The Price-to-Income Ratio is defined as:

We use median (rather than mean) values throughout to reduce the distortionary effect of high-end property transactions and high-income outliers on the central tendency.

Property prices are taken from national sources where available (transaction-based series are preferred over appraisal-based), supplemented by OECD, UN-Habitat, and Numbeo aggregate data. Income figures are drawn from household income and expenditure surveys conducted by national statistics offices and harmonized in the Luxembourg Income Study (LIS) database.

Where transaction-based price data is unavailable, we use listing-based price estimates with an explicit downward adjustment factor derived from markets where both series are available (typically 5–15% below listing price).

Rent-to-Income Ratio (RIR) Calculation

The Rent-to-Income Ratio is defined as:

We define the "representative dwelling" as an unfurnished apartment of 55–70 m² in a location within 45 minutes commute of the urban core, reflecting typical conditions for a household that is not in the extreme high or low end of the market.

Rental data is sourced from national statistics agencies, Eurostat (for EU member states), HUD (for the United States), and secondary aggregators where primary data is not available. All rental series are for market-rate units; subsidized social housing is excluded.

Purchasing Power Parity (PPP) Adjustment

To enable cross-country comparison of income and price levels, we convert national currency figures to PPP-adjusted international dollars using the World Bank's International Comparison Program (ICP) conversion factors, updated annually.

PPP adjustment accounts for differences in price levels across countries, making it possible to compare the real purchasing power of households in, for example, India and Germany — where nominal exchange rates would give a very misleading picture of relative living standards.

We use the household final consumption expenditure PPP conversion factor (rather than the GDP-based factor) as the most appropriate deflator for household income analyses.

Income Quintile Methodology

All affordability metrics are computed separately for five income quintiles (Q1 = lowest 20% of households by income; Q5 = highest 20%), using the household income distribution reported in the following datasets:

• Luxembourg Income Study (LIS) Database — the primary source for developed economies
• World Bank PovcalNet / Poverty and Inequality Platform — primary source for developing economies
• Eurostat EU-SILC survey — supplementary source for EU member states
• National household income surveys — where LIS or WB data is unavailable or outdated

Quintile boundaries are defined on the basis of equivalized disposable household income — income after taxes and transfers, adjusted for household size using the OECD modified equivalence scale — to ensure comparability across different household compositions.

Primary Data Sources

The table below lists the principal data sources drawn upon in Afforvia's analyses, along with the specific data series we use and the geographic coverage.

Limitations & Caveats

Transparent reporting of limitations is a core commitment of Afforvia. The following constraints apply to all analyses on this platform:

• Data vintage: Most official household income and housing price surveys are published with a 1–2 year lag. Our most current data reflects conditions approximately 12–24 months prior to publication.
• Within-country variation: Regional median figures mask enormous within-country variation. Affordability in major metropolitan areas is typically far worse than national medians suggest. Users should treat national and regional figures as rough benchmarks, not precise local estimates.
• Informal markets: In many developing countries, a substantial share of housing transactions and rentals occur in informal markets not captured by official statistics. Our data is likely to underrepresent the housing conditions of the poorest urban households.
• PPP limitations: PPP conversion factors are derived from broad consumption baskets and may not accurately reflect relative housing costs, which are influenced by local land markets that differ substantially from the overall price level.
• Data gaps: For approximately 30–40 countries, reliable household income or housing price data is unavailable from primary sources. In these cases, we either omit the country from analysis or use regional imputation with explicit notation.

Update Schedule

Afforvia updates its datasets and indices on the following schedule:

• Annual update: Core purchasing power indices, PIR, and RIR tables are refreshed once per year, typically in the second quarter, following the release of World Bank and OECD annual data compilations.
• Ad-hoc updates: Significant revisions to underlying data by primary sources (e.g., methodological changes to ICP PPP factors) may trigger out-of-cycle updates, which are noted on the relevant pages.
• Corrections: Errors identified in published data are corrected promptly with a notation indicating the nature of the correction and the date it was made.

If you identify a potential error or have a question about our data, please use our contact form.