While last winter every downtick in corporate earnings was promptly "explained away" by executives using the harsh weather excuse, one has heard not a peep from companies on the topic of an abnormally accommodative climate over the past 4 months. And why would they - after all it would mean that any gains, not that there have been many as most companies have reported below average results, have been artificially boosted by one-time events. Needless to say, the mainstream media would rather not touch this topic with a ten foot pole: there is an election to be won and the public can not be disturbed with facts (heaven forbid someone should mention seasonal adjustments - that's a death sentence). Which is why ironically we have to go to Goldman, which as noted recently, has once again turned bearish on the economy for one reason or another, to quantify the impact of the balmy winter. "Reported growth in the CAI is 2.8% for December and 2.9% for January. The estimates here imply that excluding the effect of warm weather, growth would have been 2.5% in December and 2.5-2.7% in January. Note that although January was very warm relative to seasonal norms, this followed a gradual warming in temperatures in October through December. We think our estimates of the weather impact may be on the low side, given that snowfall was also below seasonal norms this year. Lower precipitation can raise activity in some sectors. Our estimates imply that a normalization in temperatures could be a modest headwind to growth over the next few months. The extent of the drag depends on the specification, but a plausible range would be 10-40bp in March if temperatures return to seasonal norms by that month." Looks like Newton was right after all, despite all attempts by central planners to deny reality.
From Goldman Sachs:
Growth Impact of a Mild Winter
We have shown in previous research that atypical weather patterns can have short-run effects on many economic indicators (see for example Andrew Tilton and Seamus Smyth, “What’s With the Weather?” US Economics Analyst, January 12, 2007). Today’s report on personal income and spending for January was a classic example: real personal consumption expenditures on services were depressed in part because warm weather caused households to spend less on home heating last month. In cases like this, warm winter weather reduces economic activity. In many other cases, mild weather is a net positive for growth. For instance, our research has shown that warm weather seems to boost construction spending and nonfarm payroll employment. The Federal Reserve’s Beige Book also noted this week that warm weather had lifted residential real estate activity and tourism in some areas. In this US Daily, we use our Current Activity Indicator (CAI)—a statistical summary measure of real activity—to estimate some simple rules of thumb for the impact of weather conditions on overall growth.
A widely used metric of national weather conditions is the index of Heating Degree Days (HDD) produced by the National Oceanic and Atmospheric Administration (NOAA). The HDD index is a population-weighted measure of how far temperatures are below a benchmark level. For each day, the NOAA measures the number of degrees by which average temperatures fall below 65 degrees, and then totals them for each week or month. Therefore, colder temperatures imply higher values for the HDD index.
By this measure the winter of 2011-12 has been exceptionally mild (we discussed this issue earlier in Andrew Tilton, “’Tis the Season for Seasonal Adjustment.” US Economics Analyst, January 13, 2012). Exhibit 1 shows the difference between the HDD index for each month and the average for that month over the previous five years. This measure has been below zero—meaning temperatures have been above the trailing five-year average—in every month since October, and temperatures have become increasingly warm (relative to the seasonal norm) in each subsequent month. January was especially warm across the country, with an HDD index reading more than two standard deviations from the norm.
To measure the relationship between atypical weather and economic growth, we estimated a few simple regression models relating our CAI to the HDD index. We used two specifications: one including only the CAI and the change in the HDD measure, and another which also included two lags of the CAI. Which specification should be preferred is not immediately obvious. On the one hand, the CAI displays clear evidence of persistence, so it is natural to include lags of the dependent variable in the regression. On the other hand, in the case of weather-related shocks, we would not expect the impact on activity to persist for very long. And in fact our earlier work found negative “payback” effects from weather shocks for many indicators. We therefore show both results, and consider them to be the likely range of possible effects.
The chart below summarizes the results, showing the contribution to annualized growth in the CAI from changes in the HDD index. In both regressions, a one standard deviation change in the HDD index implies a 20 basis point (bp) impact on annualized growth for the month. For the model including lags of the CAI, the impact shown in the chart is a simulation starting in October relative to a baseline in which temperatures remained in line with their five year average (i.e. no deviation in the HDD index shown above). In this model, the effects are larger and there is less payback later because positive effects from the weather shocks are assumed to persist. For the model without lags, the chart shows the simple static impact on the CAI of changes in the HDD index for each month. For February, we have estimated heating degree days based on weekly data available through February 25. Thereafter we assume weather conditions return to normal.
The estimates suggest that warm weather added about 30bp to growth in our CAI measure in December (both models are consistent for this month) and 20-40bp in January. Reported growth in the CAI is 2.8% for December and 2.9% for January. The estimates here imply that excluding the effect of warm weather, growth would have been 2.5% in December and 2.5-2.7% in January. Note that although January was very warm relative to seasonal norms, this followed a gradual warming in temperatures in October through December. Our models are based on changes in the HDD index, and therefore show a smaller impact in January than otherwise would be the case (a sudden warming in temperatures in January would have lifted the CAI by 50-60bp, according to the models). Finally, we think our estimates of the weather impact may be on the low side, given that snowfall was also below seasonal norms this year. Lower precipitation can raise activity in some sectors.
Our estimates imply that a normalization in temperatures could be a modest headwind to growth over the next few months. The extent of the drag depends on the specification, but a plausible range would be 10-40bp in March if temperatures return to seasonal norms by that month.