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How to Use the Cost of Living Index (COLI) Reports

The Council for Community and Economic Research (C2ER) leads and supports the collection and release of a national cost of living index. Cities, towns, and metro areas choose to participate in the index and may stop or start participating at any point. Communities that choose to participate collect prices for more than 60 goods or services during a specific timeframe. Each price collected has specific standards set by C2ER to reduce noise and discrepancies in the data.

This data set is frequently used by individuals, media, and organizations to make informed decisions and comparisons about the costs of living in different places. To empower decisions driven from this data it is important to understand the purpose of the data and how to interpret index data.

The cost of living was created to measure how communities, primarily urban cities, compare in terms of cost for moderately affluent professional and managerial households. Although this may seem identical to comparing average standards of living across diverse communities in the United States, it is very different. The cost of living is focused on the costs for a business or professional family with an income that is much higher than median incomes within a community. This means the index is not measuring the costs for the average resident. Per the data manual, the kind of household on which the Cost-of-Living Index is based has the following characteristics:

  • The household consists of both spouses and one child.
  • Both spouses hold college degrees; at least one has an established professional or managerial career with a record of growing responsibility and authority and is salaried rather than paid by the hour.
  • Household income is in the top quintile (20%) for the area. In most parts of the country in the 21st century, the specified household will generally have an annual income between $70,000 and $100,000. The appropriate income range will be higher in traditionally high-cost places like New York, Boston, San Francisco, Los Angeles, and San Diego metropolitan areas, and it will often be somewhat lower in small metropolitan or non-metropolitan places.

It is important to understand that while C2ER has specific requirements for all items priced, it is not always possible to follow the requirements 100% of the time. For example, apartments priced are supposed to be newly built apartments at a specific size. Not every community has enough new built apartments to use prices from only recently constructed facilities. The data is collected by many people in different communities which introduces a small amount of noise to the data.

When communicating index results it is important to understand how indices work and how human-induced noise impacts the results. The cost-of-living index is not a time series dataset. This means that it is not correct to make comparisons over time. Because the communities that participate and the goods priced change, different values over time can be driven by these changes not actual changes to the areas cost of living.

To determine a percent using an index you subtract the base, 100 for the cost of living, from the value. The value of 100 in the Cost-of-Living Index is the national average cost for that collection period. For a city with an index value of 88.5, it costs 11.5% less than the national average. Another city with an index value of 125.0, costs 25% above the national average. To account for noise and general variability, C2ER recommends a threshold of 5% to denote a real difference. This means that if two cities have a cost-of-living value of 90 and 93 that there is not a large enough difference between the two to say that one is higher than the other. This also holds for cities between 95 and 105 with respect to the national average. A community with an index value of 103.5 does not meet the threshold of a 5-point difference and therefore is not significantly different than the national average.

An important characteristic of this index is that it would be possible for the index value to change when a real cost change does not happen. A great example of this is gas prices. If gas prices in Colorado Springs stay the same and prices in other cities increase, the Colorado Spring’s index value for gas will drop. This is important to understand as changes to the index may not always reflect noticeable changes or any price change to consumers. The same consistent price with a change in the index can also happen in a very expensive or very low-cost city that drops off the index. A great example of this is New York, costs in New York are so much higher than most other places that it brings the national average up. If New York dropped off the index, then many cities that are currently about equal to the national average would be above the national average.

Data can be a powerful tool when used properly.

 

 

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