The Bureau of Labor Statistics (BLS) employment report released today shows that 261,000 jobs were added in October. In this blog post, I report results from two alternative projections, each of which was calculated using methodology outlined in my past research. However, none of these methods addresses the effects of hurricanes Harvey and Irma that still remain the dominant special factors affecting today’s jobs numbers. I accordingly begin with some discussion of their likely effect. Adjusting for the effects of the hurricanes and an unusually warm October, I estimate that the underlying pace of jobs growth for September and October was 180,000 and 131,000, respectively, for an average pace of 156,000 new jobs.
Hurricanes Harvey and Irma substantially impacted the jobs numbers for September. At the time of last month’s jobs report, the BLS reported a loss of 33,000 jobs in September, the first net job loss in more than 5 years. This morning, the BLS has revised September’s number up, from –33,000 to +18,000. Based on state-level jobs numbers that came out on October 20 and other information, including the fact the September jobs numbers were revised upward by BLS, I estimate that these two hurricanes lowered the September employment growth by about 150,000. In past comparable episodes, the jobs numbers have bounced back by about two-thirds in the next month. Hence, I estimate the October employment numbers were inflated by about 100,000 from the bounce-back effect. Adjusting the BLS Official numbers for September and October, the estimated hurricane effect gives an underlying pace of jobs growth of 168,000 for September and 161,000 for October, which is close to the average monthly gains from the previous 12 months. The rebound from the hurricanes and the rebuilding effort should again be a positive factor for jobs growth in next month’s report.
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 264,000 jobs in October, only slightly more than the official BLS total of 261,000.
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 with Michael Boldin “Weather-Adjusting Economic Data,” we 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, but not including hurricanes. This was because working with national data, we found it difficult to estimate the effect with reasonable precision; it seems essential to use data at the state and local levels to estimate the employment effects of hurricanes. Thus, we did not include a hurricane factor in our preferred empirical specification.
Temperatures in October were nearly 2½ °C warmer than the historical average following a cooler-than-normal September, our highest reading ever for an October. I estimate that this inflated the pace of new employment in October by 30,000 jobs. The Seasonal and Weather Adjusted estimate for October is thus 231,000 jobs. Again, it is important to emphasize that this does not include the effect of the hurricanes, which I estimate separately above. Accounting for the hurricanes, the Seasonal and Weather Adjusted estimates for September and October are 180,000 and 131,000 new jobs, respectively.
Hurricanes Harvey and Irma left a big imprint in the jobs data in both the September and October reports, and the recovery from the September losses is probably not complete. Nonetheless, the average of the BLS Official numbers for September and October is 140,000 jobs per month, which is below the trend of the previous year. But accounting for the hurricane effect, the average underlying pace of growth for September and October is 165,000 jobs.
|Thousands of jobs added||BLS Official||Alternative Seasonal Adjustment||Seasonal and Weather Adjustment||Weather Effect|
Note: Changes in previous months’ numbers reflect revisions to the underlying data.
 Applies a longer window estimate of seasonal effects (see Wright 2013).
 Includes seasonal and weather adjustments, where seasonal adjustments are estimated using the BLS window specifications (see Boldin & Wright 2015).
 BLS Official number less the Seasonal and Weather Adjustment number.
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.
Each month from March 2014 to April 2019, Brookings experts analyzed how weather and seasonality affected job numbers. To read more about this series, please visit our page on adjusting the monthly jobs numbers.