How Justools estimates cost of living

Key takeaways

1. 01

   The calculator compares your spend with a city baseline built from published statistical tables, not a crowdsourced coffee index.

2. 02

   Housing is usually the city-specific line. In several Asia and Europe markets, groceries and other non-housing spend are still largely national.

3. 03

   We publish three households (Single, Couple, Family) and eight categories, in the local currency.

4. 04

   Ranks stay inside one country. Rank 1 is the cheapest city in that country's set, not in the world.

5. 05

   The September 2026 snapshot carried July 2026 city totals forward. It is not a new rent survey.

6. 06

   Results are estimates. They are not tax, take-home pay, or financial advice.

What the number is

Justools publishes a city baseline for every place the Cost of Living Calculator covers. You pick a country, a city, and a household type. The tool shows a typical monthly total in local currency, a split by category, and how that city ranks against the other cities we cover in the same country.

The number is an estimate of household spend, not a quote from a landlord and not a salary. Those two Family totals below come from the same cube the calculator uses.

We built this so you can see the method, not only the total. If a sentence cannot be traced to a published statistical table or a documented join, it does not belong in the calculator and it does not belong here.

Households and categories

Single is one adult. Couple is two adults. Family is two adults plus children on the family-education line. The public calculator no longer asks you to pick a bedroom count. Each profile uses a default housing band: one bedroom for Single, two for Couple, three for Family.

The eight categories are:

• Housing
• Utilities
• Food
• Transport
• Insurance
• Health and personal care
• Family and education
• Entertainment and leisure

Family and education is zero on the Single and Couple baselines. That is deliberate. It is not missing data.

Every total is monthly. Weekly and annual views in the tool are conversions of that monthly figure. Currency follows the country: Australian dollars in Australia, US dollars in the United States, and so on. We do not show a world ranking, because that would mix bank FX with local baskets.

How we build a city

A city baseline is a stack. In order:

1. 01 · Housing

   From the rent source we can repeat each ingest from a public agency. State rent reports and bonds in Australia, HUD Fair Market Rents (opens the source page) in the United States, ONS private rents (opens the source page) in the United Kingdom, CMHC average rents (opens the source page) in Canada, NZ rental bond data (opens the source page), and the equivalent tables elsewhere.

2. 02 · Non-housing

   From a household expenditure survey. In Australia the scaffold is ABS CPI 17th series capital-city expenditure (opens the source page), which is HES-based. We bridge those older prices with the ABS Consumer Price Index (opens the source page), then apply ABS Monthly Household Spending Indicator, May 2026 (opens the source page) category growth so the basket is not stuck in 2017.

3. 03 · United States non-housing

   Seventeen metros have a direct BLS Consumer Expenditures 2023 (opens the source page) reading. Other metros in our 65-city set use a peer CEX basket scaled by BEA regional price parities on FRED (opens the source page). Housing is still HUD FMR for that metro.

Agencies almost never publish a full city by household by category cube. Where they do not, we join tables and write down the join: CPI ratios, regional total-spend indexes, bedroom scales, or peer-metro parities. That is table arithmetic. It is not a guessed grocery price.

Housing vs the rest

Open two cities in the same country and you will often see rent move more than food. That is usually the data, not a bug. For many Asia and Europe countries in this snapshot, non-housing is still largely national, so the within-country gap is housing-led. We would rather under-claim city grocery differences than invent them.

Australia is the exception that proves the rule: capital-city expenditure exists, then MHSI freshness. The United States has metro CEX for some places and RPP for others. The United Kingdom uses ONS family spending by region (opens the source page) plus private rent. Canada uses Statistics Canada household spending (opens the source page) with household-type scales and CMHC rents.

If you are comparing Lyon and Paris on this tool, do not read the food line as a street-by-street market. Read housing first.

What September 2026 contains

September 2026 is an honest carry-forward month. Agency August and September rent packs were not ingested. City dollars stayed on the July 2026 baselines. We refreshed FX and attached housing bedroom factors. Two-bed is 1.00. One-bed and three-bed use HUD, CMHC, NZ bonds, or ONS bedroom tables where those already existed, and a documented 0.80 / 1.00 / 1.30 fallback elsewhere.

Do not write a news story that prices jumped in September because our as-of label moved. They did not, not in this file.

What we do not model

• Income tax, benefits, visa costs, or school fees beyond the family-education category.
• A mortgage versus rent split. The housing line is a rent-style occupancy cost from published rent tables. If you own outright, your housing cost may be lower. If you just signed a new let in a tight market, it may be higher.
• Suburb-level defaults on the public calculator. Suburbs inside a metro can differ more than two cities in our list. Type your rent.
• World ranks. Salary Swap can move a basket across countries as destination cost divided by origin cost. That is purchasing power for the lifestyle basket, not a bank FX headline. An editable monthly FX rate is display only.

Sources we can actually open

Every row below is a deep permalink we could open when this page was drafted. Method is carry-forward because city totals in snapshot 2026-09 were copied from July 2026. The table covers every country in the cube, including Germany, France, Italy, Spain, the Netherlands, Sweden, Austria, Switzerland, Poland, and South Korea. Where a snapshot still stores an agency homepage, we cite a deep Destatis, INSEE, ISTAT, INE, CBS, SCB, Statistics Austria, BFS, GUS, REB, or MODS bulletin instead. Dutch asking-rent pages on Pararius returned 403, so the Netherlands housing row is the CBS rent bulletin.

The HDB page stored on the Singapore snapshot returned 404. The public link here is the HDB rental statistics dataset on data.gov.sg (opens the source page), which returned 200. Queensland's RTA median-rents path redirected; we cite the destination that loaded.