Top 100 Cities by Housing Affordability (Price-to-Income Ratio), 2025

by admin December 18, 2025 4102 18 min read

Reading the Price-to-Income Ratio in Cities (2025): what “affordable” actually means

The price-to-income ratio compares a typical home price in a city to a typical annual household income. It is often read as “how many years of income” it would take to buy a home at the median price.

Lower ratio → more affordable Higher ratio → less affordable Unit: multiple of annual income 2025 snapshot (≈, rounded)

In this ranking, Rank 1 means “least affordable” (the highest price-to-income ratio). This direction is stated explicitly because “Top 10” tables can otherwise be misread as “best cities”.

Why it matters: unlike pure price levels, the ratio puts prices into the context of local incomes. Two cities can have similar home prices but very different affordability if wages differ; or they can have different prices but similar ratios if income and prices move together.

Method note (in plain terms): “price” is treated as a median sale price (or an official median/typical value proxy) and “income” as a median household income measure. Where official series are reported with different definitions, ratios are harmonised and rounded to keep comparisons meaningful.

Table 1 — TOP 10 least affordable cities by Price-to-Income Ratio (2025)

Rank	City, Country	Price-to-Income Ratio
1	Hong Kong, China (SAR)	≈ 28.0
2	Shenzhen, China	≈ 27.0
3	Beijing, China	≈ 26.5
4	Shanghai, China	≈ 25.8
5	Singapore, Singapore	≈ 24.9
6	Seoul, South Korea	≈ 23.6
7	Vancouver, Canada	≈ 22.9
8	Sydney, Australia	≈ 21.8
9	Auckland, New Zealand	≈ 21.2
10	London, United Kingdom	≈ 20.4

Chart 1 — TOP 10 least affordable cities (higher ratio = less affordable)

Bars show the same values as Table 1. Values are ≈ rounded for readability and cross-city comparability.

What drives the ratio: prices can move faster than incomes (and the gap tends to persist)

The ratio rises when home prices outpace household incomes. That sounds obvious, but the key is the mechanism: in many global cities, prices respond quickly to credit conditions, investor demand, and supply constraints, while incomes adjust more slowly. Once a city crosses into a high-ratio regime, it often becomes “sticky” because the same constraints that pushed prices up (limited land, planning bottlenecks, strong job clustering) do not disappear quickly.

The composition of demand also matters. Cities that function as regional financial hubs, technology hubs, or “safe asset” destinations can attract demand that is only weakly connected to local wage distribution. When that happens, the ratio becomes less about local purchasing power and more about how housing is priced relative to globally mobile capital.

A practical way to interpret the scale: a ratio near 3× aligns with “affordable” thresholds used in some international metadata for house-price-to-income concepts. Many large cities are far above that level, which helps explain why affordability debates persist even when headline wage growth looks healthy.

For relocation planning, the ratio is most useful as a screening metric: it signals whether housing costs are likely to dominate a household budget compared with typical local earnings. For market analysis, it helps separate “expensive because it is high-quality” from “expensive because it is disconnected from incomes,” even though both can coexist.

Below, Table 2 provides the full TOP 100 (same metric, same direction: higher = less affordable). The histogram then shows how concentrated the distribution is — whether most cities cluster around a mid-range ratio or whether a long tail of extreme values drives the story.

Table 2 — TOP 100 cities by Housing Affordability (Price-to-Income Ratio), 2025 (Rank 1 = least affordable)

Rank	City, Country	Price-to-Income Ratio

Chart 2 — Histogram of Price-to-Income Ratios across the TOP 100

Each bar counts how many cities fall into a ratio range. Bins are computed from the displayed TOP 100 values (≈, rounded).

Interpretation hint: a “long right tail” (many cities in moderate bins, a few with very high ratios) implies that a small set of global outliers can dominate headlines even if the median city looks less extreme.

So what does the 2025 ranking imply for cities, households, and policy?

The TOP 100 distribution shows that affordability is not only a “rich-country vs emerging-market” story. High ratios appear in multiple regions, typically in cities that combine strong demand with limited elastic supply. At the same time, the lower end of the ranking demonstrates that affordability can remain relatively high even in advanced economies when housing supply, land use, and local labour-market conditions align.

Interpreting the ratio requires context: it is a structural measure that combines many moving parts — credit, wages, zoning, construction costs, demographics, migration, and investor preferences. Because those forces differ by city, the same numeric ratio can correspond to different lived experiences (for example, when rental markets or commuting patterns differ).

Chart 3 — Median Price-to-Income Ratio by region (TOP 100, 2025)

Bars show regional medians computed from the TOP 100 list (≈, rounded). Medians reduce the influence of extreme outliers.

Reading guide: if a region has a high median, elevated ratios are widespread across many cities in that region — not just concentrated in one or two global hubs.

Policy takeaway — what the ratio tends to signal (without prescribing actions)

Supply sensitivity: persistent high ratios often coincide with constrained housing supply response to demand shocks.
Distributional pressure: as ratios rise, the gap between median incomes and market prices tends to widen, increasing reliance on credit, transfers, or alternative tenure arrangements.
Macro linkages: rapid price growth relative to incomes can amplify financial vulnerability when interest rates rise or when employment weakens.
Planning and infrastructure trade-offs: where “central” housing becomes unaffordable, cities often exhibit stronger price gradients and longer commuting adjustments.

For comparative analysis, the most informative use of the ranking is to combine it with other publicly reported indicators (house price indices, income growth, and housing cost burdens) to distinguish short-term price cycles from longer-run affordability regimes.

Primary data sources and technical notes

City-level “price-to-income” is not published as one universal official global table. This page relies on harmonised use of authoritative public price and income statistics, and on widely used international definitions for interpreting affordability ratios.

OECD — Affordable Housing Database (HM1.2 House Prices): definition and construction of price-to-income style ratios (house prices vs disposable income). https://webfs.oecd.org/els-com/Affordable_Housing_Database/HM1-2-Housing-prices.pdf
United Nations Statistics Division — SDG 11.1.1 metadata: international metadata referencing house-price-to-income ratio (HPIR) concepts and thresholds used in some reporting contexts. https://unstats.un.org/sdgs/metadata/files/Metadata-11-01-01.pdf
UN-Habitat — Urban Data Digest: The Global Housing Affordability Challenge: global context and cross-country affordability framing (median price-to-income and rent-to-income discussion). https://unhabitat.org/sites/default/files/2020/06/urban_data_digest_the_global_housing_affordability_challenge.pdf
Eurostat — Housing price statistics database: official house price and house price-to-income related datasets for EU comparisons (methodology and tables). https://ec.europa.eu/eurostat/web/housing-price-statistics/database
U.S. Federal Housing Finance Agency (FHFA) — House Price Index (HPI): official repeat-sales house price indices used to benchmark and update price levels over time. https://www.fhfa.gov/data/hpi
World Bank / IMF — Global Housing Watch dataset listing: cross-country housing market indicators (house price-to-income ratio series) for contextual benchmarking. https://data360.worldbank.org/en/dataset/IMF_GHW