Yes, believe or not, Goldman Sachs whips out precise Excel models even when it comes to determining the hiring impact of a snowicane:
Jan Hatzius @ Goldman: Exhibit 2 below incorporates the knowledge from our model, assessing the snowstorm impact on payrolls with fully revised data, after removing the estimated impact of temperature changes. The logic here is that snowstorms sometimes—but not always, and not this February—come along with much colder than usual weather, which can intensify their impact on employment. The pattern, shown by the solid diamonds, is now quite striking—a tightly clustered group of points around a line that suggests a substantially smaller impact from the snow itself, perhaps 50,000 to 100,000 on the payroll report.
Accurate much? Apparently they’ve used historical data to plot past payroll impacts vs. the severity of a storm based on Northeast Snowfall Impact Scale (NESIS). Love the two-decimal-place precision:
Our forecast of a decline of 100,000 payroll jobs assumes an impact at the higher end of this range. Despite this, we are inclined to think the risk remains on the side of a still bigger impact from the snowstorm itself.
Yet to be fair, while the model’s accuracy remains to be seen, it is probably one of the best guesses we’ve got right now. In the end some people are paid (handsomely) to forecast huge unknowns, and they’ll make every effort to do so, as shown above.
So there we have it. About -100,000 new hires were delayed or lost in February due to bad weather, which results in an overall net payrolls forecast of -100,000 jobs lost for the month. Let’s see how they do this Friday.
Moreover, even if Goldman’s weather impact estimate has a huge margin of error, their data shows that the government is probably entitled to take a mulligan this Friday after all. Historically, bad weather has slammed hiring, delaying it until future months.
(Via Goldman Sachs, U.S. Daily, Jan Hatzius)
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