Re: [Pen-l] Sandwichman predicts...

[Sandwichman <lumpoflabor@xxxxxxxxx>]

Doug, thanks for your questions.

The technique is not really all that original. My inspiration was the article explaining the birth/death model, "Impact of business births and deaths in the payroll survey," in the May 2006 Monthly Labor Review. The birth/death model does indeed "work pretty well" annually, as evaluated from comparing the B/d adjusted estimate with the actual benchmark revision. But if you look at the monthly numbers, there's a remarkable seasonal variation, with April being the high point of the year for adding in "births" and January and July actually recording "negative births" (or could they be firm deaths in excess of reported deaths?) 

My point being that the seasonal variation of the b/d imputation exceeds the seasonal adjustment factor of the overall employment number. And, in a sense, there's little the BLS can do about reconciling this because the data they use for modeling is QUARTERLY, not monthly. Well, actually, the BLS could go to a quarterly birth/death adjustment but then their reports wouldn't be as timely. It's all a question of balancing the timeliness of the data reporting with its quality. 

Again, if you're evaluating the accuracy of the results on the basis of an ANNUAL benchmark, it hardly matters that your QUARTERLY data are slightly skewing your MONTHLY reports. Got it? It's all in the different time frames. If I'm wrong here about how BLS evaluates accuracy, then I can only attrbute it to my source, a BLS report titled "How the Business Birth/Death Model Improves Payroll Employment Estimates". One can only assume that the BLS evaluates accuracy the same way they report the evaluation.

My use of the word "prediction" is tongue in cheek. All I'm doing is a linear trend projection based on the empirical observation that the January to June seasonal variation is pretty regular. As you point out, January is a month of heavy layoffs, followed by a pretty steady seasonal run-up in jobs. From year to year the slope of the January to June unadjusted numbers (taking January as the seasonal trough and June as the seasonal peak) may be different each year but within each year it's a fairly straight line. Such steadiness makes sense if you think about employment being a relatively stable process. A seasonally adjusted decline in employment sometimes refers to an unadjusted increase in employment that was , however, less than the usual increase for the month.

My prediction for May is thus based on two things: a linear projection from the January to April seasonally-unadjusted trend (such as can be observed in the 1992-2008 data) and the conclusion that "nothing happened in April" to signal a turning point in employment, that is to say the apparent deceleration of job loss in April to 539,000 from 699,000 in March and 681,000 in February was a statistical hiccup and not a turning point. And some of that hiccup gets added to the May number. 

Just to be perfectly clear, my 'prediction' for May is based on the assumption that nothing has changed, fundamentally, and nothing will change this month. If you take the average of the April report and my May prediction, you get -657,000 to -687,000 -- pretty much in line with the reported March and February numbers.

On Sun, May 10, 2009 at 12:56 PM, Doug Henwood <dhenwood@xxxxxxxxx> wrote:

On May 10, 2009, at 3:25 PM, Sandwichman wrote:

May BLS Non-farm payroll employment decline: -775,000 to -835,000 jobs lost.

http://econospeak.blogspot.com/2009/05/prediction.html

Those are some original techniques you're using there, Comrade Sandwich.

You say:.

Another thing I noticed is that seasonally unadjusted January to June employment numbers consistently display a steady slope, with the seasonally-adjusted employment figures intersecting that line at April. So far this year, the January to April segment of that line has been flat, with a minor dip down in February and March followed by a small bounce in April. That small bounce might reflect the 62,000 census workers plus the residual unadjusted seasonal variation from the birth/death model.

The BLS has been working on the birth/death model for a long time, and it works pretty well. If you think you've discovered a problem with it, then maybe you should let them know.

But I don't get your point at all about the slope of the unadjusted numbers. January is normally a month of heavy layoffs, so the SA takes out almost 3 million jobs that month at current employment levels. Feb-June are normally months when SA adds jobs - a little over 3 million all together. Over the course of a year, the seasonal factors cancel out. But if you look at the pattern for the first half of the year alone, you might find some sort of slope.

For example, if unadjusted employment were unchanged at April's NSA level of 132.295 million, you'd get the following changes after SA (in thousands):

Jan           +2,870
Feb             -649
Mar             -692
Apr             -734
May             -751
Jun             -402
Jul           +1,218
Aug             -123
Sep             -423
Oct             -724
Nov               +8
Dec             +269

Actual monthly changes, so far this year:

      SA       NSA
Jan    -741    -3,615
Feb    -681    -  164
Mar    -699    -   84
Apr    -539    +  241
     -----    ------
tot  -2,660    -3,622

How does this suggest anything about what might happen in May?

Doug



_______________________________________________
pen-l mailing list
pen-l@xxxxxxxxxxxxxxxxxx
https://lists.csuchico.edu/mailman/listinfo/pen-l

-- 
Sandwichman
_______________________________________________
pen-l mailing list
pen-l@xxxxxxxxxxxxxxxxxx
https://lists.csuchico.edu/mailman/listinfo/pen-l