posted on 12 October 2016
Written by Steven Hansen
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 were insignificantly changed from last month. In addition, the growth rate trends declined using the 3 month averages.
There was no market expectations from Bloomberg this month.
this month's graph
The relevance of JOLTS to future employment is obvious from the graphic below which shows JOLTS Job Openings leading or coincident to private non-farm employment. JOLTS job openings are a good predictor of jobs growth turning points - and have similar trend lines..
The graph below uses year-over year growth comparisons of non-seasonally adjusted non-farm private BLS data versus JOLTS Job Openings - and then compare trend lines.
Year-over-Year Change - Unadjusted Non-Farm Private Jobs Openings from JOLTS (blue line, left axis) compared to Unadjusted BLS Non-farm Private (red line, right axis)
Unadjusted Hires (blue line) and Unadjusted Separation Levels (red line) - Non-Farm Private
Please note that Econintersect has not been able 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:
Comparing BLS Non-Farm Employment YoY Improvement (blue line, left axis) with Econintersect Employment Index YoY Improvement (red line, left axis) and The Conference Board ETI YoY Improvement (yellow line, right axis)
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 are not predictive.
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