Written by Steven Hansen
The BLS Job Openings and Labor Turnover Survey (JOLTS) can be used as a predictor of future job growth, and the predictive elements show that the year-over-year growth rate of unadjusted private non-farm job openings significantly declined and remains in contraction.
Analyst Opinion of JOLTS Data
The unadjusted data this month remained well below average for the rate of growth seen in the last year. With this low average rate of growth, JOLTS is predicting lower employment growth than we have seen over the past year. Jolts predicted the slowing of employment growth. However, this month the coronavirus pandemic was little noticed by JOLTS – and expect a very large drop of open positions next month.
Market expectations from Econoday were 3.100 M to 6.250 M (consensus 5.900 M) with actual at 6.191 M.
The graphs below use the year-over-year growth of JOLTS Job Openings – both the level of openings and rate of openings.
Last month’s graphs
This Month’s Graphs
There is a skills mismatch in the U.S. workforce – as job openings are higher than a number of unemployed people.
The JOLTS Unadjusted Private hires rate (percent of hires compared to the size of the workforce) and the separations rate (percent of separations compared to the size of the workforce – separations are the workforce which quit or was laid off).
Unadjusted Hires (blue line) and Unadjusted Separation Levels (red line) – Non-Farm Private
Please note that Econintersect has not been able to use the hire rate or the separation rate (or a combination thereof) to help in understanding future job growth. A Philly Fed study agrees with Econintersect’s assessment. JOLTS is issued a month later than the jobs data – and correlates against one-month-old data.
For information, the Econintersect Employment Index and the Conference Board’s Employment Index:
Caveats on the Use of JOLTS
This data series historically is very noisy which likely is a result of data gathering issues and/or seasonal adjustments. Therefore this series must be trended to provide an understanding of the dynamics. One of two months of good or bad data is not predictive.
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