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Unemployment in the US

April 1, 2009


There is a good interactive map of unemployment rates at the county level across the US in the March 29 New York Times. Here is a snapshot, but be sure to visit the Times site for the interactive version. The map is based on January 2009 data, and it represents a national rate of unemployment of 8.5%. But there is a tremendous range across regions and counties.

There are many noteworthy details on the map. Northern California and Oregon somewhat surprised me; Harney County, Oregon, has a rate of 19.7% unemployment, and Trinity County, California, has a rate of 20.9%. These are staggering numbers for these locales.

My own state, Michigan, has a very wide range of unemployment rates across both rural and urban counties. Wayne County, home of the city of Detroit, has a relatively high rate of 14.2%, and Genesee County, home of Flint, also has a high rate (14.8%). (By comparison, Onondaga County, home of Syracuse, New York, has a rate of 7.4%.) Several Michigan counties with mid-sized cities show relatively low unemployment rates: Washtenaw County (Ann Arbor), Kalamazoo County (Kalamazoo), and Kent County (Grand Rapids) have relatively low rates (7.3%, 8.4%, 9.8%). But several other counties in the state show rates in excess of 18%: Cheboygan County (21.8%), Baraga County in the Upper Peninsula (23.4%), Sanilac County (18.9%), and Iosco County (18.5%). What this shows is that the unemployment crisis is not evenly distributed across the state or the region; some counties are much more seriously affected than others. And some of the highest rates are in counties with agriculture and extraction as primary industries — manufacturing counties in Michigan are generally in the middle rank.

A quick visual inspection suggests that Michigan and South Carolina are the states with the highest proportion of high-unemployment counties; California and Oregon are also clearly on the high end of the unemployment crisis.

The tool also allows the user to select for rural, manufacturing, metropolitan, and “housing bubble” counties.

I suppose that the central truth that this map supports is the fact that the employment crisis has affected regions and economic sectors very differently — across large regions and within states. So here, as with so many social variables, it is important to disaggregate the national and state data, to get a better idea of the range of effects a given economic circumstance is creating for individuals and families.

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