This morning, the single most asked question I hear is “So what’s Your NFP Number?”
That’s one of the more interesting side issues about this Maine event/fishing trip/conference. Its overrun with economists and Fed folk, who are the fairly focused on short term data.
Regular readers number I have little interest in making bad predictions about monthly data points that are not all that important. You would think that anyone who tracks the NFP data (such as economists or Fed members) would understand how meaningless any single data point. But its part of their history and monthly routine, and therefor remains disproportionately significant to them. Hence, the silly monthly question.
Phillipa Dunne, the well regarded longtime Employment researcher of the Liscio Report wants to shift the data analysis in a different direction. She believes we should be spending less time thinking about the headline number, and more time time doing a deep dive into the specific details beneath — the Big Data approach. In addition to taking apart the inputs, Dunne wants to break the numbers down by region. She thinks that lots of non-BLS data inputs — Fuel usage, Tax receipts, historical data bases, FOMC data, etc. — are equally important to the analytical process if one wants a 30,000 foot view of the employment sector. The lagged Quarterly Census of Employment and Wages (QCEW) data from actual unemployment insurance records — this is the basis of the benchmarked data that goes into the final numbers on a multi-quarter lag — is similarly important and overlooked.
For those of us who find the monthly obsession with the initial NFP data to be silly, this sort of analytical approach is refreshing. Let’s hope it catches on . . .
NFP Day: The Most Over-Analyzed, Over-Emphasized, Least-Understood Data Point (February 4th, 2011)
An Unusually Unusual NFP Payroll Day! (June 3rd, 2011)
THE MOST IMPORTANT EVER NFP blah blah blah (June 7th, 2013)
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