Article

June 2014

Is the workweek really overestimated?

Previous research published in the Monthly Labor Review has come to conflicting conclusions regarding whether survey respondents correctly report their weekly work hours. This article documents substantial inconsistencies in research claiming that the Current Population Survey overestimates hours worked and confirms that any such bias is small. It also explains the proper interpretation of figures that purport to show the relationship between measurement error in hours worked and reported hours.

The number of hours that people work for pay is an important economic and social indicator. Many household surveys ask respondents to estimate their weekly work hours (we will refer to this type of question as an “estimate question”). One of the main sources of data on work hours is the Bureau of Labor Statistics household labor force survey, the Current Population Survey (CPS), which asks respondents about the usual number of hours worked per week and the actual number of hours worked during the previous week.

One might question the accuracy of hours reports from estimate questions because respondents are faced with the potentially complex cognitive task of remembering how much they worked during the previous week or estimating their “usual” weekly work hours. Moreover, even an accurate estimate of “usual” (modal) work hours may be a poor estimate of mean work hours. To validate hours data from estimate questions, some researchers (ourselves included) have compared responses to those questions to time diaries, which are detailed accounts of the previous day’s activities.1 Time-diary data are generally considered to be more accurate because of the short, typically 1-day, recall period and the requirement that the total time spent on all activities must sum to 24 hours.

The American Time Use Survey (ATUS) is a single-day time-diary survey that is administered to a sample of individuals in households that have recently completed their participation in the CPS. In addition to the time diary, the ATUS collects information about the respondents’ employment status and usual hours worked (the question is the same as that in the CPS). Thus, for each ATUS respondent, responses are available for three estimate questions about hours worked: usual and actual hours worked from the CPS and usual hours worked from the ATUS.

In an earlier article in the Review,2 we compared the responses to these three estimate questions with the time-diary estimates for the same set of respondents. We found that, on average, responses to the two usual-hours questions overestimated work hours, and that the overestimation was greater for the ATUS usual-hours question. But we also found that actual hours worked were correctly reported by CPS respondents.

In this article, we comment on the ATUS–CPS analysis in a 2011 Review article by John Robinson, Steven Martin, Ignace Glorieux, and Joeri Minnen (hereafter Robinson et al.),3 who used time-diary data from the ATUS to argue that hours of work are typically overestimated in household surveys. In contrast to our previous article, these authors found that responses to all three estimate questions overestimated hours worked, and that the magnitude of the overestimation was about the same for all three questions. They also found that reports of longer hours in the estimate questions were associated with larger overestimates relative to time-diary hours.

We examined Robinson et al.’s results closely and found that their main table of results contains extensive internal inconsistencies—evidence of programming or transcription errors.4 When we used the methods described in their article to attempt to replicate the table, the results were consistent with our earlier work and showed a negligible mean difference between CPS actual hours and diary hours. We also attempted to replicate Robinson et al.’s chart 1, which shows how the gap between estimated and diary hours varies with estimated hours. Our replication was qualitatively similar to theirs. However, the chart should be interpreted carefully, and the interpretation in Robinson et al. is somewhat misleading. We note instances of misinterpretation and discuss the proper interpretation.

Notes

1 The ATUS and most time-use surveys collect data for 1 day, but some collect data for more than 1 day.

2 Harley Frazis and Jay Stewart, “What can time-use data tell us about hours of work?” Monthly Labor Review, December 2004, pp. 3–9, http://www.bls.gov/opub/mlr/2004/12/art1full.pdf. See also Frazis and Stewart, “Where does the time go? Concepts and measurement in the American Time Use Survey,” in Ernst Berndt and Charles Hulten, eds., Hard to measure goods and services: essays in memory of Zvi Griliches, NBER Studies in Income and Wealth (Chicago: University of Chicago Press, 2007), pp. 73–97; Frazis and Stewart, “Comparing hours worked per job in the Current Population Survey and the American Time Use Survey,” Social Indicators Research, August 2009, pp. 191–195; and Frazis and Stewart, “Why do BLS hours series tell different stories about trends in hours worked?” in Katharine G. Abraham, James R. Spletzer, and Michael Harper, eds., Labor in the new economy, NBER Studies in Income and Wealth (Chicago: University of Chicago Press, 2010), pp. 343–372, where we find similar results. For similar results for the United Kingdom, see Richard D. Williams, “Investigating hours worked measurements,” Labour Market Trends, February 2004, pp. 71–79.

3 John Robinson, Steven Martin, Ignace Glorieux, and Joeri Minnen, “The overestimated workweek revisited,” Monthly Labor Review, June 2011, pp. 43–53, http://www.bls.gov/opub/mlr/2011/06/art3full.pdf.

4 So far, we have been unable to reproduce the results in Robinson et al.’s table 1. We have shared an earlier draft of this article with Professor Robinson and his coauthors. Robinson, who has written to us to state that he performed the data analysis for the ATUS–CPS comparison in Robinson et al., has been unable to locate the relevant programs as of this writing.

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About the Author

Harley Frazis
frazis.harley@bls.gov

Harley Frazis is a research economist in the Office of Employment and Unemployment Statistics, U.S. Bureau of Labor Statistics.

Jay Stewart
stewart.jay@bls.gov

Jay Stewart is a division chief in the Office of Productivity and Technology, U.S. Bureau of Labor Statistics.