There is some very confusing information in the August 2004 unemployment rates produced by the BLS. In this chart, the BLS shows the seasonally adjusted unemployment rate in the District of Columbia at a very high 7.5%. However, in this chart, the BLS shows a non-seasonally adjusted unemployment rate of a very low 3.2%. Why the huge difference? What seasonal adjustment needs to be made in Washington DC? I can see in some places such as Florida or Alaska, there could be differences in employment because of a large reliance on tourism.
The first chart is listed as District of Columbia, the second as Washington DC PMSA. Does including suburban Virginia and Maryland really help lower the overall unemployment rate that much?
It’s hard to tell what portions of MD, VA, and WV are included in the statistics on the second chart. Northern Virginia and Montgomery County, MD are very affluent areas and probably have a very low rate of unemployment. Including WV in the stats seems strange to me. I guess there’s that little eastern tip of WV, but I’m surprised that’s not part of the Cumberland MSA (rank #278).
Regarding seasonal work in the area, both MD and VA have sizable beach towns (Ocean City, etc.), and DC is very much the land of summer interns, though that may balance out with other interns when Congress is in session.
Basic info on some of the areas involved—you can see the huge differences in things like income and educational attainment:
Montgomery County, MD: http://quickfacts.census.gov/qfd/states/24/24031.html
Arlington County, VA: http://quickfacts.census.gov/qfd/states/51/51013.html
Seasonality in unemployment is not caused by seasonal tourism. Some other causes are the school year (college students taking summer vacation jobs, and students thrown onto the job market at the end of the school year), seasonal employment increases before Christmas (Christmas shopping, etc.), and outdoor jobs that cannot be done in the winter (particularly building work).
You betcha! Any central city has highly magnified problems in terms of unemployment, average income, high school dropouts, you name it.
Let’s take an easy to use example. If you don’t own a car, you probably live in a city? Why? Because it’s easier to get around a city with a car than to get around the suburbs. That means people without cars tend to gravitate to cities. So the percentage of car ownership in an entire metropolitan area might be 90%, while in the central city it might only be 50%.