What it means
The value of an index is that it combines three moving parts into one number: prices, incomes and borrowing costs. A house price rise alone tells you little, but an affordability index shows whether that rise was offset by wage growth or made worse by higher interest rates.
Construction is straightforward once you fix the assumptions. You calculate the income needed to buy the median item on standard financing terms, then divide the median income by that qualifying income and multiply by 100.
The assumptions are where the arguments happen. Deposit size, the share of income allowed for repayments, the interest rate and whether taxes and insurance are included all shift the index materially, so two published indices for the same city can differ substantially without either being wrong.
Businesses use affordability indices well beyond housing. Vehicle makers, subscription services and consumer lenders build the same ratio for their own products to decide whether a price rise will be absorbed or will simply push buyers out of the market.
Two cautions are worth carrying. An index built on medians says nothing about the distribution, so affordability can look adequate overall while first-time buyers are locked out entirely.
Directional movement is also more informative than the level, because a fall from 130 to 105 is a meaningful signal even though the index still reads above 100.
In practice
Real-world examples.
Example
A regional homebuilder tracks the local affordability index each quarter and sees it fall from 118 to 94 in a year, driven almost entirely by rate rises. It shifts its next development from four-bedroom houses to smaller two-bedroom units priced $90,000 lower.
Example
A car manufacturer builds an affordability measure comparing median household income with the income needed to service a five-year loan on its mid-range model. When the index drops below 100 it extends loan terms to 72 months rather than cutting the sticker price.
Example
A city economic development team uses an affordability index to support a case for new transport links. It shows that affordability in one suburb reads 128 but that the district is unreachable without a car, which effectively removes the apparent advantage for lower-income households.
Formula
Calculation
Housing affordability index = (median household income / qualifying income) x 100
Qualifying income = annual loan repayment / the maximum share of income allowed for repayments
Worked example. The median home in a metro area costs $360,000, buyers are assumed to put down 20%, the mortgage rate is 6% over 30 years, and lenders allow repayments to take at most 25% of gross income. Median household income is $75,000.
Deposit = $360,000 x 0.20 = $72,000
Loan amount = $360,000 - $72,000 = $288,000
Monthly repayment on $288,000 at 6% over 30 years = $1,727
Annual repayment = $1,727 x 12 = $20,724
Qualifying income = $20,724 / 0.25 = $82,896
Affordability index = ($75,000 / $82,896) x 100 = 90.5
A reading of 90.5 means the median household has about 90% of the income needed, a shortfall of $82,896 - $75,000 = $7,896 a year. If the mortgage rate fell and the monthly repayment dropped to $1,560, qualifying income would fall to $1,560 x 12 / 0.25 = $74,880 and the index would rise to roughly 100, restoring affordability without any change in prices or wages.Case study
Seen in the real world.
Larkspur Homes is an illustrative, fictional regional developer that had always priced new schemes by adding a target margin to build cost. In one year its build costs rose 8% and it passed the increase through, lifting the price of its standard house from $340,000 to $367,000.
Sales stalled. When the fictional company's analyst built an affordability index for the catchment area, she found that the local median income of $71,000 was well short of the $84,500 needed to qualify at the new price, an index reading of 84. Two years earlier, at a mortgage rate of 4.5% and a price of $310,000, the same calculation had produced a reading close to 118.
Larkspur responded by redesigning the standard house to a smaller footprint that could sell at $319,000, which lifted the index to about 97, and by offering a rate buy-down on the first 30 units. In this illustrative case the lesson was that the buyer's constraint was monthly income capacity rather than the headline price, and the index was what made that constraint visible.
Watch out
Common mistakes.
- Comparing indices from different publishers without checking the assumptions. Different deposit sizes, rate assumptions and income caps produce very different numbers for the same market.
- Reading an index above 100 as evidence that everyone can buy. The median household is not the marginal first-time buyer, who typically has lower income and a smaller deposit.
- Ignoring the interest rate input. Affordability can deteriorate sharply while prices are flat, purely because borrowing costs have risen.
Questions
People also ask.
What does a reading of 120 actually mean?
The median household has 20% more income than the minimum needed to qualify for a loan on the median-priced home under the stated assumptions.
Can affordability improve while prices rise?
Yes, if incomes rise faster than the combined effect of prices and interest rates, the index can improve in a rising market.
Should a business build its own index?
If your product is bought on credit and priced near the limit of what customers can service monthly, then yes, because it converts price decisions into a customer capacity question.
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