NonSeasonally Adjusted Data?

In the comments of an earlier post, Roman asks "If you are going to not consider the birth/death adjustment, then its only fair to not count the seasonal adjustment. If you take that out, then the report shows a large gain of jobs. Why does no one here want to talk about that?"

Okay, its a question we might as well address (those of you with statistics or applied mathematics backgrounds please bear with us).

I criticize the B/D model because it has changed what was primarily a measured count (via tax withholding data at established firms) into something more theoretically based. Hence, what was once actual measurement is now primarily a form of modeling. We know that at this late stage of the economic cycle, the modeling creates these bizarre aberrations, such as +45,000 new construction jobs and +8,000 new financial activities jobs in April 2008.

Those data points aren’t merely wrong, they are patently absurd.

But what of seasonal adjustments? What they do is attempt to smooth out or reduce the effect of the regular seasonal patterns that tell us nothing about the economy, and everything about calendar effects: winter weather, school years, planting seasons, holidays, etc.

But since you asked . . .

Let’s do a month-to-month comparison of the non-seasonally adjusted data:

From the CES establishment data, table B-1,we learn that the 2008 numbers were 137,019 in March and in 137,722 in April, for a total nonseasonal adjusted change of +703k. Last year, in 2007, the March was 136,835 versus April 137,668, for nonseasonal adjusted change of +833,000.

So before seasonal adjustments, April 2008 created 130,000 less jobs than April 2007.

Here’s a graphic depiction of the year over year, non-seasonally adjusted NFP:

Chart courtesy of Brian Jacobs

For those of you wonky enough to care, here is the BLS’ explanation as to their Seasonal adjustments:

Over the course of a year, the size of the nation’s labor force and the levels of employment and unemployment undergo sharp fluctuations due to such seasonal events as changes in weather, reduced or expanded production, harvests, major holidays, and the opening and closing of schools.  The effect of such seasonal variation can  be  very large; seasonal fluctuations may account for as much as 95 percent of the month-to-month changes in unemployment.   (emphasis added)

That’s a rather substantial seasonal impact. What do you suppose we should do about it? 

Because these seasonal events follow a more or less regular pattern each year, their influence on statistical trends can be eliminated by adjusting the statistics from month to month. These adjustments make non-seasonal developments, such as declines in economic activity or increases in the participation of women in the labor force, easier to spot.  For example, the large number of youth entering the labor force each June is likely to obscure any other changes that have taken place relative to May, making it difficult to determine if the level of economic activity has risen or declined. However, because the effect of students finishing school in previous years is known, the statistics for the current year can be adjusted to allow for a comparable change. 

Insofar as the seasonal adjustment is made correctly, the adjusted figure provides a more useful tool with which to analyze changes in economic activity . . ."  (emphasis added)

Now you know . . .  Aren’t you glad you asked?

>’

Sources:

EMPLOYMENT SITUATION: APRIL 2007
Table B-1  Employees on nonfarm payrolls by industry sector and selected industry detail 
BLS,
http://www.bls.gov/news.release/History/empsit_05042007.txt

Employees on nonfarm payrolls by industry sector and selected industry detail CURRENT
BLS, Table B-1.
http://www.bls.gov/news.release/empsit.t14.htm