The BLS Job Openings and Labor Turnover Survey (JOLTS) can be used as a predictor of future jobs growth, and the predictive elements show that the year-over-year growth rate of unadjusted private non-farm job openings was down relative to last month.

Analyst Opinion of JOLTS Data

There was a significant downward adjustment of the rate of growth for job openings for last month. The unadjusted data this month was about average for the rate of growth seen in the last year.

With this JOLTS, it is predicting little change in the employment situation we have seen over the past year.

Note from the BLS:

Job openings, hires, and separations have been revised to incorporate the annual updates to the Current Employment Statistics employment estimates and the JOLTS seasonal adjustment factors. Additionally, a new methodology for item imputation has been implemented.

There were no market expectations from Econoday.

The graphs below use year-over-year growth of JOLTS Job Openings - both the level of openings and rate of openings.

Last month's graphs

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This Month's Graphs

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There is a skills mismatch in the U.S. workforce - as job openings are higher than a number of unemployed people.

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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

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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 jobs 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:

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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 any understanding of the dynamics. One of two months of good or bad data is not predictive.