Two big pieces of employment news Thursday couldn't have been more jarring.
First came a hopeful sign for manufacturing in Minnesota's April unemployment data: 1,500 new positions and a fourth straight month of gains.
Hours later, Polaris Industries announced it would shut down a western Wisconsin plant.
Together, they got me thinking about the roller coaster ride manufacturing jobs have been on the past decade. A look at some long term data shows just how far we've fallen and the steep climb back.
Here's manufacturing employment since the recession began in December 2007.
That looks bad enough. But check out this chart of manufacturing employment since 1990 and you can feel your neck snap back as you contemplate the drop.
Here's a chart of monthly manufacturing employment, seasonally adjusted, since 1990, using federal Bureau of Labor Statistics Data.
(click on the chart for a larger view)
Looking at the charts, it's hard to believe Minnesota will find its way back on manufacturing. Employment in durable goods manufacturing (equipment, technology, machinery, etc.) is down nearly 30 percent from its peak in the 2000s (August 2000) -- more than 75,000 jobs gone.
During 2008, manufacturing boasted roughly 340,000 jobs -- 13 percent of the state's workforce, generating 15 percent of all wages paid.
Two years later, manufacturing's down below 300,000 jobs and 11 percent of the workforce.
A recent survey shows some optimism among the state's small and mid-sized manufacturers.
But it's a long road back to the summer of 2000 when some 400,000 Minnesotans were making things that built the economy.
Got a different view or better data? Post below or contact us directly.
I am assuming that all of the charts are "seasonally adjusted."
While I certainly understand the value of evaluating trends using seasonally adjusted data, the reality is that "not seasonally adjusted" data is the more accurate short-term tool. Workers from the manufacturing sector are employed or unemployed.
In addition, I would argue that while the goal of using SA data takes into account seasonal variations in production, it may also mitigate the true impact when the next season rolls around and the manufacturing worker is not called back. There is also the case of the worker who is called back, but only on a PT basis.
The general premise is spot on, however.
awesome post, but only for those who understands)