August 2018 Headline JOLTS Job Openings At Series High -

August 2018 Headline JOLTS Job Openings At Series High

Oct 16, 2018Jeremy ParkinsonFinance0

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 improved relative to last month. The headline data was also little changed from last month.

Analyst Opinion of JOLTS Data

Even though the headline job openings data was at series highs – the BLS stated:

The job openings rate was 4.6 percent. The number of job openings was little changed for total nonfarm, total private, and government. Job openings increased in federal government (+15,000). The number of job openings was little changed in all four regions.

The unadjusted data analysis shows rate of growth is about average seen since 2010.

Market expectations from Econoday was 6.800 M to 7.000 M (consensus 6.900 M) versus actual of 7.1 million.

The graphs below uses 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

The JOLTS Unadjusted Private hires rate (percent of hires compared to size of workforce) and the separations rate (percent of separations compared to size of 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 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:

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 tended to provide any understanding of the dynamics. One of two months of good or bad data are not predictive.