An interactive look at participation in the labor force by age

Click an area on the chart to isolate that category. Slide along the GDP growth graph under the chart to look at a different time period.

shaded ), red lines indicate a major change to the CPS survey. Note: This chart is updated monthly. Data is from the Census Bureau's Current Population Survey. Basic monthly data are used and all months are averaged together for each year. The survey was revised in 1989 and 1994; changes to both question wording and survey weights result in discontinuities in these years that may not be attributable to real changes in the economy. GDP data from: US. Bureau of Economic Analysis, Gross Domestic Product [GDP], retrieved from FRED, Federal Reserve Bank of St. Louis https://research.stlouisfed.org/fred2/series/GDP. Recession data from: Federal Reserve Bank of St. Louis, NBER based Recession Indicators for the United States from the Period following the Peak through the Trough [USREC], retrieved from FRED, Federal Reserve Bank of St. Louis https://research.stlouisfed.org/fred2/series/USREC, March 1, 2016. Slide to pick a year (recessions are),indicate a major change to the CPS survey.

Methodology

The data assembled span three versions of the Current Population Survey, with new surveys being instituted in 1989 and 1994. All three surveys feature a labor force participation item that is generated based on responses to a series of yes/no questions on the survey. This variable is called ESR, LFSR, and PEMLR, respectively, on the three versions of the survey. A second variable—called major activity, or MAJACT, on the first two surveys and PENLFACT on the post-1994 survey—was used to distinguish between certain categories of non-labor force respondents. Finally, a question on total hours worked was used to distinguish full-time workers from part-time workers.

The results are fairly consistent across surveys for certain age groups but there are important discrepancies. Most notably, the pre-1989 survey did not allow respondents to specifically identify themselves as retired. Instead, the “other” category included retirees. The wording and question order of the 1989-1993 survey appears to bias respondents in favor of choosing “carer” over “retired,” so another break in the retired series is evident in 1994. Minor changes in the survey may also have contributed to the uptick in respondents identifying as “disabled” in the most recent version of the survey.

This project’s github includes the Python code that was used to analyze the raw monthly CPS data, including our survey-weighting procedure and all coding decisions made.