Comments on: The curious predictability of the payrolls report http://blogs.reuters.com/felix-salmon/2013/01/04/the-curious-predictability-of-the-payrolls-report/ A slice of lime in the soda Sun, 26 Oct 2014 19:05:02 +0000 hourly 1 http://wordpress.org/?v=4.2.5 By: Greycap http://blogs.reuters.com/felix-salmon/2013/01/04/the-curious-predictability-of-the-payrolls-report/comment-page-1/#comment-45427 Fri, 04 Jan 2013 21:14:50 +0000 http://blogs.reuters.com/felix-salmon/?p=20047#comment-45427 What KevyD said. I count 25 observations in your graph of which 5 deviate by more than 100,000. So if the null hypothesis were that job growth was steady, there would actually be too many outliers rather than too few. Though not convincingly too many, for n=25.

Of course, nobody thinks job growth was steady. Well, then how do you think that real monthly (seasonally-adjusted) job growth varies? Suppose it is on the same order as error rate, which by construction is independent. We would naively expect to have to scale the confidence interval by something like root 2. And sure enough, 2 of the 25 observations seem to breach the modified 90% confidence interval. That seems reasonable.

Yes, the last 3 observations have small variations but there was a similar run from 2011-06 to 2001-08. Are you quite sure that is unusual?

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By: leachim http://blogs.reuters.com/felix-salmon/2013/01/04/the-curious-predictability-of-the-payrolls-report/comment-page-1/#comment-45426 Fri, 04 Jan 2013 20:22:07 +0000 http://blogs.reuters.com/felix-salmon/?p=20047#comment-45426 This makes little sense. Stable differences can occur if the underlying addition of jobs is volatile. Suppose 100,000 jobs are added in Month 1, and 200,000 in Month 2. Now if the error is +50,000 in Month 1, and -50,000 in Month 2 (plausible given the BLS information), you end up with 150,000 in Month 1 and 150,000 in Month 2. Exactly what we get here.

In other words, without knowing the true level of added jobs, you cannot make any claim about the difference of differences is.

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By: QCIC http://blogs.reuters.com/felix-salmon/2013/01/04/the-curious-predictability-of-the-payrolls-report/comment-page-1/#comment-45425 Fri, 04 Jan 2013 20:12:44 +0000 http://blogs.reuters.com/felix-salmon/?p=20047#comment-45425 ??? I don’t even understand what you are getting at? Do you understand how statistics even work? The values have to be something, an error is just as likely to erroneously show no change as it is to erroneous show a change, because you don’t know what the actual value is.

Also label your freaking axes. Are those thousands of jobs or percentages or what?

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By: najdorf http://blogs.reuters.com/felix-salmon/2013/01/04/the-curious-predictability-of-the-payrolls-report/comment-page-1/#comment-45421 Fri, 04 Jan 2013 16:43:29 +0000 http://blogs.reuters.com/felix-salmon/?p=20047#comment-45421 Felix, this is utter nonsense. You can’t make statistical claims without using, you know, statistics. You aren’t adding any value on assessment of the sampling error (instead you borrow BLS’s estimate). You don’t actually quantify the volatility. You don’t have a very good data set (25 observations). And since we don’t know the underlying reality, observing month-to-month changes in estimates doesn’t tell us anything about error in those estimates (what if job growth was actually much more volatile, but the errors happened to align to make job growth look steady?).

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By: KevyD http://blogs.reuters.com/felix-salmon/2013/01/04/the-curious-predictability-of-the-payrolls-report/comment-page-1/#comment-45418 Fri, 04 Jan 2013 16:05:18 +0000 http://blogs.reuters.com/felix-salmon/?p=20047#comment-45418 I’m not sure I understand? You say estimates should be off by 100 thousand approximately once a year. While we have no way of knowing if/how many months are actually off; there is a change of greater than 100 thousand 5 times in your graph, and one shows a change of 200 thousand. This would indicate at least one of the months sandwiching that change was off quite a bit as you would expect. Admittingly the last 3 months have very small changes, but 3 observations is extremely small sample. The average of 51,000, with a median of 30,000 seems about right to me (admittingly I don’t have a doctorate in statistics)

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