“We don’t have the data collection structure to capture what is happening in a real time way, or what is being traded and how it is affecting workers. We have no idea how to measure the occupations being offshored or what is being inshored.”
-Susan Houseman, senior economist at the W.E. Upjohn Institute for Employment Research
I am on the West Coast for a few more days, but my body clock remains on East Coast time. This means I am three hours behind and somewhat harried.
Even from this sunny California vantage point, I cannot help but point you to a specific NYT column that is dead center in the sweet spot of what I love to do: Dissecting the official economic releases to tease out the flaws inherent in the data modeling, and identifying what they misrepresent.
Or in more colloquial English, sniffing out and fixing bad dope from government geeks (i.e., statisticians, economists, etc.).
Long time regular readers are familiar with some of our favorite topics in this area. The hall of fame of misleading official data is quite long: The Birth Death adjustment, the U3/U6 unemployment measures, Owners Equivalent Rent, anything Boskin Commission related, the construction of GDP, and of course, “Core” Inflation. Many of these have been outed; they are more in the public eye thane ever before, and perhaps a little better understood by investors. However, they remain highly misleading data points.
The good news is that the pros are starting to notice, and they are taking some small steps to fix at least some of the problems:
“A widening gap between data and reality is distorting the government’s picture of the country’s economic health, overstating growth and productivity in ways that could affect the political debate on issues like trade, wages and job creation.
The shortcomings of the data-gathering system came through loud and clear here Friday and Saturday at a first-of-its-kind gathering of economists from academia and government determined to come up with a more accurate statistical picture.
The fundamental shortcoming is in the way imports are accounted for. A carburetor bought for $50 in China as a component of an American-made car, for example, more often than not shows up in the statistics as if it were the American-made version valued at, say, $100. The failure to distinguish adequately between what is made in America and what is made abroad falsely inflates the gross domestic product, which sums up all value added within the country . . .
That may help to explain why the recovery from the 2001 recession was a jobless one for many months and why the recovery from this recession is likely to generate few jobs for many months.”
One small step for data junkies, one giant step for econometricians
Measurement Issues Arising from the Growth of Globalization*
November 6-7, 2009
W.E. Upjohn Institute for Employment Research
National Academy of Public Administration
Economists Seek to Fix a Defect in Data That Overstates the Nation’s Vigor
NYT, November 8, 2009
Category: Data Analysis
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