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Estimating (also…Making Stuff Up)

January 29, 2008

My official job title really is Statistician. (Totally unadorned, most boring job title ever, the looks I get are amazing.)

Anyway a lot of what I do is make estimations about what is going on in my particular segment of the economy. And then I take these estimations and I send them to the press with some commentary and people go “The Fatisticians at Some company said THIS because of blah and blah.” And of course everyone nods nods and our boss gets interviewed on TV and everything is Faaaabulous. Though at best we are making estimations with limited data, at worse we are doing so with an agenda (not so us we just want to be right.)
I don’t want you to read this and think that all math people are dishonest, we are very honestly using the best available methods to come up with this information. (Notice the word available there, that is key.) A lot of times we are working under time constraints and with limited data, so we often go with the most reasonable method that will give us a reasonable answer in the most reasonable amount of time. But as a consumer of information everyone should know that these numbers are literally a statistician’s or an economist’s best guess. They are probably better than say, the guy who walks my dog’s best guess, but that does not make them the truth.

The reason I was thinking on this was this report (Via talkingpointsmemo)that discusses what to expect in the potential upcoming recession. The report overall is interesting if a 2% increase in the unemployment rate is really deeply meaningful for you. What I found MOST interesting though was the methodology. They looked back at the % change caused by previous recessions and applied it to this potential recession. This is a very reasonable way to look at this, with what data is available and it can be done in a reasonable amount of time.

But, and this is not to be incredibly critical of the Center for Economic Policy Research who i’m sure employs much smarter people than me. It does seem to be a very simplistic view of a complicated economic problem. The economy is made up of so many variables that each affect eachother in countless ways. Just a few of the conomic indicators we use: the consumer price index, consumer confidence index, fuel prices, GAFO. The only indicator discussed in this analysis is Unemployment. I would be seriously interested in the effects that a major industry like the housing market has on other economic indicators beyond employment and how those indicators may then affect unemployment.

Plus, there are so many new factors since the last major recession of 1980-1982 (Internet, anyone? Bueller?) that a comparison to that seems fairly weak, on top of that China has become a major economic force, the “environmentally friendly” industry is growing, we are at war with two countries (Afghanistan?…..Bueller?), we’re dealing with lots of illegal immigrants, and more government regulation due to security concerns. Plus, I’m here. So lots of major changes.

But do these changes really matter? I don’t know. To really incorporate all of that information into a model would probably render the model meaningless. So what the CEPR did was the most reasonable method. But not necessarily the most accurate.


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