Data Spotlight: Measuring a Region's Health via Pull Factor

Published on Aug 4, 2009

Updated on Jan 26, 2024

Written by Emsi Burning Glass

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Here is a handy economic development metric. It’s called “pull factor,” and it indicates how well (or poorly) a retail business community captures local trade and pulls in customers from outside its region. A pull factor above 1.00 means a region is bringing more shoppers into the area while a pull factor below 1.00 indicates more folks are going to other areas to shop.

Pull factor is simple to calculate, and it can be done using EMSI’s labor market tools.

Here’s a quick example:

Ada County, Idaho, is home to Boise, a medium-sized city that has seen substantial population growth in recent years. As a result, it’s a central retail hub for a large area of southwestern Idaho.

Step one: To measure Ada County’s pull factor, we first gather the 2009 total sales figure for the retail trade industry in the Economic Impact tool. It can be found under the “Economic Base” tab and the “Jobs, Earnings, Sales” report. For Ada county — about $2 billion.

Step two: Calculate the per capita sales by dividing the overall sales amount ($2 billion) by the county’s population (391,589), which can be found in Economic Forecaster. This leaves us with a per capita sales figure of approximately $5,164.

Step three: Repeat the same process, only this time use state-level numbers. Total retail sales for Idaho is estimated to be roughly $6.5 billion in 2009 and the total population is 1,553,491. The per capita sales figure is $4,200.

Step four: Divide Ada County’s per capita sales ($5,164) by the state’s ($4,200).

Results: Ada County has a pull factor of 1.23 ($5,164/$4,200 = 1.23). This means that the county brings in 23% more sales (in dollars) than the average area. This is a very healthy number, especially in comparison to Idaho’s second largest county, Canyon, which has a pull factor of 0.69.

Pull factor can be particularly useful when trying to see how a community has grown and developed over a series of years.