We’ve often said that the only people worse at their jobs than weathermen are economists. In fact, getting it wrong might as well be in the job description. Here’s what we said back in August:
Here’s the job description: make predictions that are almost never right and then make up any reason you want to explain away the fact that you were wrong. These explanations run the gamut from intentional obfuscation via opaque statistical tinkering (“residual seasonality”) to comically absurd attempts to turn common sense into an excuse for poor outcomes (“snow in the winter”).
The irony there of course is that economists and weathermen have something in common other than the fact that they’re virtually always wrong: they both talk about the weather a lot. Indeed, weather has become a catch-all excuse for poor economic outcomes no matter what time of the year it is.
Indeed, late in September Citi jumped the shark and suggested that what the Fed needs to do is assume that economic data is actually better than it looks to avoid making policy decisions based on faulty numbers. Why are the numbers faulty, you ask? Simple: because of the summer.
Several times during this expansion, the Fed has made important policy decisions in the month of September. The history of payroll revisions for August and September has shown that some of those decisions might have been based on false signals, which could have biased policy toward accommodation.
We have found serious residual seasonality in payroll reports for the period from August through October. Weak August and September readings typically lead substantially stronger October reports, including sharp upward revisions to August and September data. This pattern has given rise to shifting market (and Fed) views of the labor market – from weakness to strength – each fall.
We have seen that the seasonal weakness in August payroll gains has supported accommodative policy decisions during this expansion. For instance, shortly after the extremely weak August 2011 payroll report, the Fed announced the plan to ease through Operation Twist. In 2012, after another soft August figure, the Fed announced QE3. In September 2013, the Fed unexpectedly delayed tapering QE3.
In each case, subsequent data showed that the August jobs data had been misleadingly weak – the labor market had been improving all along.
Well, just as snow in the winter is blamed for recessionary GDP prints and just as the summer is now blamed for bad jobs data, Citi and BofA are now out blaming warm weather for poor October retail sales. From BofA:
Based on the BAC aggregate credit and debit card data, our proxy for seasonally adjusted retail sales ex-autos declined 0.3% in October. This left the three month moving average at -0.3% mom SA, revealing a slowing trend.
We believe abnormal weather patterns may have biased retail ex-auto sales lower in October. There has been a late start to the winter this year: the average temperature in October was 57.4 degrees Fahrenheit, which is the highest since 1963 and above the historical average of 54.3 degrees. Intuitively, this would depress sales of cold weather apparel, such as coats, hats, boots, etc.
No, BofA, there is nothing “intuitive” about that statement. No one would notice a three degree difference when they walk outside and even if they did, it wouldn’t keep them from buying a "hat".
And then there's Citi (again):
Warm weather combined with already weak traffic trends likely led to a shortfall in sales and we expect inventory to appear elevated across the sector (good for BURL, ROST and TJX). We believe this is particularly true for the mid-tier players, and we are lowering our estimates for M and KSS.
Got it. So now, warm weather and cold weather are fair game when it comes to explaining bad data.
We suppose it's only a matter of time before "mild" weather joins the mainstream economist "Axis of Evil."
Finally, for those curious what comes next, here is one answer:
@zerohedge [4] lining up the excuses...
* Warm weather
* Late Thanksgiving
* Weekend Rain
* Lack of snow
* Too much snow
* Polar vortex 3.0— Brian Lantier, CFA (@brianlantier) November 10, 2015 [5]
