Net Job Creation Through November 2019

Figure 1 shows the three-month moving average (3MMA) of the number of jobs created monthly since 2000 as the brown bars and the total number employed as the black line. Economy.com reported as follows: “Employment gains blew the consensus and our expectations out of the water. Payroll employment increased by 266,000 jobs in November and gains for September and October were revised higher by a combined 41,000. As expected, the settling of the UAW strike helped to boost manufacturing by 54,000. Healthcare also grew strongly. Retail was the wild card given the holiday season, and it added only 2,000 jobs, though transportation/warehousing offset some of this weakness. The unemployment rate edged down to 3.5 percent as labor force gains moderated. Average hourly earnings increased by 7 cents, or 3.1 percent year over year, somewhat stronger than recent trend.”

Figure 1a shows the raw monthly data since January last year and that the variability has been worse in 2019 than it was in 2018. The average monthly job creation in 2018 was 223,300, and in the first 11 months of 2019 was 179,700.

We prefer to use three-month moving averages in our analyses to reduce short-term variability. In averaging employment statistics in this way, we even out what is notoriously volatile data.

The employment data has been seasonally adjusted. We have developed Figure 2 to examine if any seasonality is left in the data after adjustment. We think it’s significant to look at the results this way because there is so much variability in the numbers that a long term context is necessary, and it doesn’t look as though the BLS seasonal adjustment is very effective. In the nine years since and including 2011, the average month-on-month change from October to November has been negative 4.0 percent. This year the change was positive 71 percent. Without the GM effect the gain would have been positive 44 percent, therefore November was historically excellent.

In order to get another look at the degree of change, we have developed Figure 3. This shows the same total employment line as Figure 1, but includes the year-over-year growth on a percentage basis and shows more clearly the steady improvement that occurred during 2018 and the slowdown in 2019. Considering the variability of the raw monthly data, we think the year-over-year view is the best way to evaluate what’s really going on.

According to the latest BLS economic news release, in November, average hourly earnings for all employees on private nonfarm payrolls rose by 7 cents to $28.29. Over the last 12 months, average hourly earnings have increased by 3.1 percent. In November, average hourly earnings of private-sector production and nonsupervisory employees rose by 7 cents to $23.83. The average workweek for all employees on private nonfarm payrolls was unchanged at 34.4 hours in November. In manufacturing, the average workweek increased by 0.1 hour to 40.5 hours, while overtime decreased by 0.1 hour to 3.1 hours. The average workweek of private- sector production and nonsupervisory employees held at 33.5 hours.

The official unemployment rate, U3, reported in the BLS Household survey (see explanation below) declined from 3.7 percent in June, July and August to 3.5 percent in November. U3 has ranged from 3.5 to 4.0 percent in each of the last 17 months. This is not a very representative number. The more comprehensive U6 unemployment rate at 6.9 percent was down from 8.1 percent in January (Figure 4). The difference between these two measures in November was 3.4 percent, which is historically excellent and the lowest since August 2001. U6 includes individuals working part time who desire full-time work and those who want to work but are so discouraged they have stopped looking.

The labor force participation rate is calculated by dividing the number of people actively participating in the labor force by the total number of people eligible to participate. This measure was 63.2 percent in November and hasn’t changed much in three years. Another gauge is the number employed as a percentage of the population, which we think is more definitive. In November, the employment-to-population ratio was 61.0 percent, the highest since November 2008. Figure 5 shows both measures on one graph.

In the 47 months since and including January 2016, there has been an increase of 8,822,000 full-time and a decrease of 386,000 part-time jobs. Figure 6 shows the rolling 12-month change in both part-time and full-time employment. This data comes from the Household survey and part-time is defined as less than 35 hours per week. Because the full-time/part-time data comes from the Household survey and the headline job creation number comes from the Establishment survey, the two cannot be compared in any given month. To overcome the volatility in the part-time numbers, we look at a rolling 12 months for the full-time and part-time employment picture shown in Figure 6.

The job openings report known as JOLTS is reported on about the 10th of the month by the Federal Reserve and is over a month in arrears. In the November employment report, JOLTS data was reported for September. Figure 7 shows the history of unfilled jobs. In September, openings stood at 7,024,000, which was still historically high but down from 7,626,000 in November 2018. There are still more job openings than there are people counted as unemployed.

Initial claims for unemployment insurance, reported weekly by the Department of Labor, have been exceptionally low since 2014. The U.S. is enjoying the longest streak since 1973 of initial claims below 300,000 (Figure 8). This data stream is part of our recession outlook report and at present shows no sign of an imminent problem.

Challenger Grey and Christmas produced a monthly report of job cuts in the U.S. Job cuts were 44,600 in November, which was below average for the year (Figure 9). Economy.com reported: “Job cuts decreased to 44,569 in November, down 11 percent from a month ago and 16 percent from a year earlier. November layoffs were driven primarily by cuts in technology and automotive sectors. The November reading does not signal major softening in the economy given that firm restructuring efforts and bankruptcies accounted for 30 percent of job cuts. Technology and retail topped the industry list in terms of most layoffs. Firms reported branch closings and restructuring as the most prevalent reasons for job cuts in November. Announced hiring plans were lower than last month, but stronger than a year ago.”

SMU Comment: This report was excellent and made even better by upward revisions to September and October’s data. Having said that, it is still a fact that job creation this year is less than was the case in 2018. Therefore, a couple more excellent months are needed to confirm the November result and suggest a turnaround.

Explanation: On the first Friday of each month, the Bureau of Labor Statistics releases the employment data for the previous month. Data is available at www.bls.gov. The BLS reports on the results of two surveys. The Establishment survey reports the actual number employed by industry. The Household survey reports on the unemployment rate, participation rate, earnings, average workweek, the breakout into full-time and part-time workers and lots more details describing the age breakdown of the unemployed, reasons for and duration of unemployment. At Steel Market Update, we track the job creation numbers by many different categories. The BLS database is a reality check for other economic data streams such as manufacturing and construction. We include the net job creation figures for those two sectors in our “Key Indicators” report. It is easy to drill down into the BLS database to obtain employment data for many subsectors of the economy. For example, among hundreds of sub-indexes are truck transportation, auto production and primary metals production. The important point about all these data streams is the direction in which they are headed. Whenever possible, we try to track three separate data sources for a given steel-related sector of the economy. We believe this gives a reasonable picture of market direction. The BLS data is one of the most important sources of fine-grained economic data that we use in our analyses. The states also collect their own employment numbers independently of the BLS. The compiled state data compares well with the federal data. Every three months, SMU examines the state data and provides a regional report, which indicates strength or weakness on a geographic basis. Reports by individual state can be produced on request.