Posted by: Josh Lehner | January 6, 2014

US County Employment – Population Ratios

A lot of recent economic research and thought so far during this recovery has focused on the general lack of improvement in measures like the labor force participation rate and also the employment to population ratio. Even as the economy is growing and improving, not everything is well. Some, but certainly not all, of this lack of improvement is due to the aging demographics and so attention is now being paid to the so-called prime working age population — generally defined as those aged 25-54 — to strip out the aging impact.

Using the latest county level data from the American Community Survey, the map below shows the employment-population ratio change for working age adults. Over this period at the national level the ratio declined 3.1 percentage points, according to the ACS figures* and the color coordination of the map is relative to the U.S. trends. Yellow indicates the local decline was about the same as the national average, while orange and red counties saw larger declines and green counties saw smaller declines or outright gains. Data is unavailable for counties with populations less than 20,000, however the counties for which data is available account for about 96% of the population. (Map template here)


There is a clear geographic pattern here, with the hardest hit housing regions faring the worst, the Northeast and Midwest generally performing OK (relative to national trends) while some of the energy producing regions faring better. These results are similar to the previous look at county level growth and the housing rebound, which largely is not too much of a surprise. The scatter plot below shows a county level look at these changes in the employment-population ratio and the labor force participation rate for the working age population. By and large the strong relationship is to be expected and the causation more likely runs from job losses to lower participation rates.


What about the outlook going forward?

Labor force growth and the ability to attract young, educated migrants has long been a benefit to Oregon’s economy, along with the Sun Belt and other Western states. To the extent that an aging population is the disease of slower growth, young working age households are the cure for the regional economy. I have been experimenting with a newly built data set, but keep returning to the standard explanatory factors when examining labor force and participation rates. Having a stronger economy and population growth drives higher labor force growth (surprise!). A more educated workforce, plus having a larger prime working age cohort are also positively related with labor force growth.

When examining the Great Recession years (2007-2012), industrial structure does not appear to play too much of a role. This is likely due to the fact I only examined 2 digit NAICS employment when the impact of industrial differences may be better seen at a more granular level. Another fact may be that the Great Recession was an equal opportunity disaster with all regions taking a hit, as opposed to, say, the 1990 or 2001 recessions where some regions did not experience a downturn. Even so, other studies have found that over a longer period, a more diverse economy is related to stronger economic growth, which in turn will drive higher labor force growth and so on.

In conclusion, while the above shows what has happened in recent years, it will be important to monitor and examine where the employment-population ratio is improving the most in recovery. Which regions are able to attract the young migrants and/or see stronger job gains? So far the evidence suggests the larger metros are succeeding the best at this for both migration and job growth, which is largely to be expected. How these patterns continue to play out and/or spread to more regions and cities will largely explain the strength of the regional economies moving forward.

* BLS data shows a larger decline at 4.3 percentage points. Overall the pattern among the different age cohorts is similar when comparing ACS and BLS data.

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