In June the Welch Consulting Employment Index fell back to its April level of 98.2, down from a recent high of 98.5 in May.

This reflects a large drop in the fraction of the population that is either working or looking for work – the labor force participation rate. The labor force participation rate fell to 62.6% in June from 62.9% in May. While the unemployment rate among those who are in the labor force improved this month, falling from 5.5% to 5.2%, this was not enough to offset the increase in those who are not in the labor force.

The Welch Index for women held steady at 100.3, maintaining its highest level since February 2009. In contrast, The Index for men fell from 97.0 to 96.6. With this large gender difference in the last month, women have now seen stronger employment gains over the past year than men have – an increase of 1.4 index points from 98.9 to 100.3 compared to an increase of 0.6 index points for men, from 96.0 to 96.6.

The Welch Index measures full-time equivalent employment, adjusting for population growth and the aging of the workforce. The Welch Index of 98.2 indicates that full-time equivalent employment is 1.5% below its level in the base year of 2004, after adjusting for population growth and changes in the age distribution of the labor force. The decrease in the Index from 98.5 in May to 98.2 in June means that full-time equivalent employment grew at a slower rate than the adult population in the past month.  The Welch Index is about 1.0% higher than it was one year ago.  Full-time equivalent employment has been increasing about 1.0% faster than adult population growth over the past two years (after making adjustments for the aging of the U.S. adult population).

Technical Note: Full-time equivalent employment equals full-time employment plus one half of part-time employment from the BLS household survey.  The Welch index adjusts for the changing age distribution of the population by fixing the age distribution of adults to the distribution in the base year of 2004.  Seasonal effects for the share of workers employed in part-time jobs are removed in a regression framework using monthly indicator variables.