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Brookings on Job Numbers

Strong employment growth in February boosted by warm weather


The Bureau of Labor Statistics (BLS) employment report released today shows that 235,000 new jobs were added in February. In this blog post, I will put forward three alternative projections for job growth in February 2017, each of which was calculated using methodology outlined in my past research.

Calculating the Alternative Seasonal Adjustment

Monthly job gains and losses can indicate how the economy is doing once they are corrected to account for the pattern the BLS already expects in a process called seasonal adjustment. The approach for this seasonal adjustment that is presently used by the BLS puts very heavy weight on the current and last two years of data in assessing what are the typical patterns for each month.

In my 2013 paper “Unseasonal Seasonals?” I argue that a longer window should be used to estimate seasonal effects. I find that using a different seasonal filter, known as the 3×9 filter, produces better results and more accurate forecasts by emphasizing more years of data. The 3×9 filter spreads weight over the most recent six years in estimating seasonal patterns, which makes them more stable over time than the current BLS seasonal adjustment method.

To produce the Alternative Seasonal Adjustment, I calculate the month-over-month change in total nonfarm payrolls, seasonally adjusted by the 3×9 filter, for the most recent month, which you can see in table below. The corresponding data as published by the BLS are shown for comparison purposes. According to the Alternative Seasonal Adjustment, the economy added 253,000 jobs in February, 18,000 more than the official BLS total of 235,000.

Calculating the Seasonal and Weather Adjustment

In addition to seasonal effects, abnormal weather can also affect month-to-month fluctuations in job growth. In my 2015 paper “Weather-Adjusting Economic Data,” Michael Boldin and I implement a statistical methodology for adjusting employment data for the effects of deviations in weather from seasonal norms. This is distinct from seasonal adjustment, which only controls for the normal variation in weather across the year. We use several indicators of weather, including temperature and snowfall.

Temperatures in January were mild, and February was milder still. This boosted job gains in the month. Controlling for weather yields a lower Seasonal and Weather Adjustment estimate of 210,000 new jobs, with warmer-than-normal weather inflating jobs growth by 25,000 jobs. The weather effect is modest in part because it follows a mild January. Construction employment rose by 58,000 in February, which is consistent with this large positive weather effect.

Combining the Alternative Seasonal and Weather Adjustments

My Alternative Seasonal Adjustment shows higher job gains than reported by the BLS, but the Seasonal and Weather Adjustment show lower job gains. One can indeed do the two adjustments jointly—both adjusting for weather effects and using a longer window. This is shown in the far-right column of the table labeled Combined Alternative Seasonal and Weather Adjustment.

Making both adjustments, the employment change in February was an increase of 255,000 jobs. This reflects both the weather this year, but also how weather and other shocks in prior years move the seasonal factors. Regardless of the weather effects and estimated seasonal patterns, it’s a solid jobs report any way you look at it.

Thousands of jobs added BLS Official Alternative Seasonal Adjustment[1] Seasonal and Weather Adjustment[2] Weather Effect[3] Combined Alternative Seasonal and Weather Adjustment[4]
2017-February 235 253 210 +25 255
2017-January 238 215 214 +24 198
2016-December 155 165 167 -12 161
2016-November 164 171 162 +2 177
2016-October 124 129 122 +2 127
2016-September 249 237 262 -13 250
2016-August 176 169 162 +14 166
2016-July 291 309 292 -1 316
2016-June 297 294 289 +8 295
2016-May 43 44 34 +9 25
2016-April 153 156 204 -51 222
2016-March 225 200 225 +0 209
2016-February 237 264 212 +25 202

Note: Changes in previous months’ numbers reflect revisions to the underlying data.

[1] Applies a longer window estimate of seasonal effects (see Wright 2013).

[2] Includes seasonal and weather adjustments, where seasonal adjustments are estimated using the BLS window specifications (see Boldin & Wright 2015).

[3] BLS Official number less the Seasonal and Weather Adjustment number.

[4] Includes seasonal and weather adjustments, where seasonal adjustments are estimated using a longer window estimate.

The author did not receive financial support from any firm or person for this article or from any firm or person with a financial or political interest in this article. He is currently not an officer, director, or board member of any organization with an interest in this article.

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