What it means
The index began life with the American Chamber of Commerce Researchers Association, which is where the ACCRA name comes from, and is now published by a successor research organisation under the Cost of Living Index name. It is built from prices collected in participating urban areas for a basket of goods and services bought by a moderately affluent professional or managerial household.
Each area's basket is expressed as a percentage of the national average, which is fixed at 100. The basket is grouped into components, typically groceries, housing, utilities, transportation, health care, and miscellaneous goods and services.
Housing carries the largest single weight, and the miscellaneous group covers everyday spending such as haircuts, restaurant meals and dry cleaning. Because the weights differ by component, two areas with the same overall score can be expensive for completely different reasons.
Businesses use the index for three jobs: pricing a relocation offer, setting regional salary bands, and comparing candidate locations for a new office or plant. It is far cheaper than commissioning bespoke research and it gives both sides of a salary conversation a neutral reference point.
That neutrality is most of its value in a negotiation. The limits matter as much as the number.
The index reflects one particular household profile, covers urban areas only, excludes taxes in most presentations, and says nothing about commute time, schools or quality of life. It also moves with housing markets, so a score from two years ago can be badly out of date in a fast moving area.
A common mistake is applying the whole index to the whole salary. Only the portion of income spent on the basket should be adjusted, and housing choices can be changed by the employee in a way that a blanket index cannot capture.
Careful employers work from the component detail rather than the headline score. Price collection is deliberately narrow so that the comparison is like for like, down to the size and type of item priced.
That precision is a strength for comparing areas and a weakness for describing any individual household, whose actual spending will never match the basket exactly. The score is best treated as a planning input, with the component detail as the part you negotiate over.
In practice
Real-world examples.
Example
A medical devices firm offers an engineer a transfer and uses the index to turn a $95,000 salary into a $118,000 offer for an area scoring about 24% above the origin. The candidate accepts because the basis is published rather than invented. The HR team keeps the calculation on file for the next transfer.
Example
A professional services firm with offices in five areas builds four regional pay bands using index ranges rather than individual scores. The bands are reviewed annually against the published index. Staff moving between offices know in advance which band will apply to them.
Example
A manufacturer comparing two candidate plant locations finds nearly identical overall scores but very different component profiles. One is expensive because of housing, which affects recruitment of senior staff, and the other because of utilities, which affects the plant's own operating cost. The utilities driven location is rejected on operating cost grounds.
Formula
Calculation
The index is a weighted comparison against the national average:
Area Index = Sum of (Component Price Relative x Component Weight), with the national average set at 100
Cost Adjusted Salary = Current Salary x (Destination Index / Origin Index)
Take an employee earning $120,000 in an area with an index of 98, moving to an area with an index of 133. The ratio is 133 / 98 = 1.357, so the equivalent salary is $120,000 x 1.357 = $162,857, which in practice would be rounded to $163,000.
The component detail usually changes the answer. Suppose the destination's score is driven almost entirely by housing, while groceries and transportation sit close to the national average. If the employer covers a $30,000 housing allowance separately, the remaining basket might justify an uplift of only 10%, giving $120,000 x 1.10 = $132,000 of salary plus the allowance, a total package cost of $162,000 for a similar standard of living at a lower permanent salary.Case study
Seen in the real world.
Verity Analytics is a fictional, illustrative data consultancy used here to show the index at work. Verity grew from one office to four and had been setting salaries by negotiating every hire individually, which produced two engineers doing the same work on salaries $34,000 apart in areas with almost identical costs. Staff had noticed, and two resignation letters cited pay fairness directly.
The chief operating officer built a pay framework around a national reference salary for each role and a cost of living multiplier for each office, taken from the published index and refreshed each year. Housing was handled as a separate allowance wherever the index showed housing as the main driver, so that permanent salary did not inflate for a cost the employee could choose to change. The reference salary for a senior analyst was set at $110,000, with multipliers running from 0.95 to 1.28 across the four offices.
Two years on, this illustrative firm had cut pay related attrition noticeably and could answer a pay question in one minute using a published source instead of a long conversation. The framework also made the cost of opening a fifth office predictable, because headcount could be priced before a lease was signed.
Watch out
Common mistakes.
- Multiplying the whole salary by the whole index. Only the part of income spent on the measured basket should be adjusted, and housing is often better handled as a separate allowance.
- Reading the index as a quality of life score. It measures prices for a defined basket and says nothing about commute, climate, schools or safety.
- Using a stale score. Housing costs move quickly, so an index figure more than a year or so old should be refreshed before an offer is built on it.
Questions
People also ask.
What does an index score of 100 mean?
It means the area matches the national average for the measured basket, with higher scores more expensive and lower scores cheaper.
Does the index include income tax?
Most presentations of the index exclude taxes, so a relocation comparison should model the tax position of each location separately.
Can the index be used outside the United States?
It covers participating United States urban areas, so an international move needs a separate international cost of living source built on the same logic.
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