The Welch Consulting Employment Index rose 0.2 points to 103.3 in December. This modest gain put it at new highs once again, something seen in many recent months.

The Welch Index measures full-time equivalent employment after adjustment for population growth and the aging of the workforce. An Index value of 100.0 indicates that adjusted full-time equivalent employment is the same as its level in the base year of 2004.

Over the past 12 months the Index has risen from 102.1 to 103.3. The increase in the Index over the past year means that full-time equivalent employment has been growing at a faster rate than the adult population.  Full-time equivalent employment increased 1.2% faster than the adult population over the past year (after making adjustments for the aging of the U.S. adult population). Looking back at the most recent 6 months, the Index rose from 102.5 in June to 103.3 currently. The growth rate in the most recent 6 months is stronger than the growth rate of the preceding 6 months. The rate of change over the past year is in line with the trend for the last 3 years of an increase of about 1.2% per year.

In December the index for women rose, while the index for men held steady. The index for women returned to its recent high of 106.9, up from 106.7. The index for women is up from 105.5 a year ago. The index for men held steady at the recent high of 100.3. The index for men is up 0.9 points from its year ago value of 99.4. Over the last three years the index for women is up 5.2 points while the index for men is up 2.3 points.

Technical Note: Full-time equivalent employment equals full-time employment plus one half of part-time employment from the BLS household survey (the Current Population Survey). The data reported for a given month is generally from the calendar week that contains the 12th day of the month. 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.