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Correlates of flexible working arrangements, stress, and sleep difficulties in the US workforce: does the flexibility of the flexibility matter?


Using the 2008 National Study of the Changing Workforce, we study how two forms of flextime correlate with family stress, workplace stress, and sleep difficulties. The first flextime measure is the ability to easily take time off for personal and family matters, which correlates with a statistically and economically significant reduction in workplace stress. Subsequently, we find that this same flexibility is associated with 6–10 % reduction in the likelihood of self-reported sleep difficulties for the full sample, and as high as an 11–25 % reduction in a subgroup analysis concerning unmarried females with children. The second flextime measure is the option of a compressed workweek, which also correlates with a statistically reduction in workplace stress, though the estimate is considerably smaller than for the first flexibility; a subsequent analysis finds no statistically significant relationship between this flexibility and sleep difficulties. Our findings suggest that the more flexible flexibility (i.e., more short-notice schedule flexibility) appears to be associated with larger reductions in the probability of being stressed, enough, in fact, to carry through to noticeable improvements in concomitant sleep difficulties. Thus, the first form of flextime may function, based on this observational analysis, as a tangible non-medical way to meet worker flextime desires and firm aspirations for increased safety and less absenteeism, all while potentially offering a positive public health externality. The size and significance of the flextime results prevail through bias assessments and sensitivity analyses.

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    “Flextime” is often used as an umbrella term for several closely related flexible working arrangements wherein the worker can adjust working hours around non-work demands.

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    Because of this mutual advantage, workplace flexibilities have been increasingly studied in high-profile contexts; for example, the President of the United States recently commissioned the Council of Economic Advisors (CEA 2010) to hold a “flexibility summit” to investigate the pros and cons.

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    Statistics from the National Study of Employers illustrate a varying degree of availability of flexibilities in the US. For example, only 32 % of workers can change starting and quitting times on a daily basis and less than 25 % of workers can work from home during regular business hours on a regular basis. However, about 79 % of workers can periodically change start and quitting times within some range of hours and about 50 % of workers can work some regular hours at home occasionally.

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    These response-based restrictions resulted in only 127 lost observations; we revisit this data cleaning decision in the sensitivity analysis section.

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    We consider only those that work more than 20 h per week because studying schedule-based flexibilities among part-time employees is difficult given that the part-time nature of their job is a significant flexibility in and of itself. Self-employed worker were excluded for a similar reason: they have a non-standard interface with flexibilities in their dual capacity as “firm” and “employee.”

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    Our sampling weights are based on the overall sample, not on the restricted sample we examine. We do so because the sample weights provided by the NSCW deal with over/under sampling by adjusting for household size, education, race, and age; however, because we do not restrict the sample by any of these measures, the use of the sample weights based on the entire sample should be sound.

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    There is also a fourth question regarding sleep; however, it asks about several conditions, not just sleep and so we omit it from our analysis. Specifically, the omitted question reads as follows: “In the last month, how often have you been bothered by minor health problems such as headaches, insomnia, or stomach upsets?”

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    According to the National Center for Sleep Disorders Research at the National Institutes of Health, about 30–40 % of adults says they have some symptoms of insomnia within a given year, and about 10–15 % of adults say they have chronic insomnia.

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    While not reported, we also estimated a parsimonious model for each sleep question that excluded subjectively measured controls like Drink, Family Stress, Health, Depression, Lose Job and Physical Job. The flexibility estimates were roughly twice as large, and significant, in these parsimonious models. The inclusion of the more subjectively measured controls appears to attenuate the results. This suggests that if the subjective survey controls are biasing our flexibility estimate, it is downward, so we are reporting conservative estimates by using the full model (which appear in the tables). Results from the parsimonious model are available from the authors upon request.

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    Our drinking variable is an indicator for moderate to heavy drinking.

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    The parlance of PSM includes phrases like “treatment effect” and “control group”; however, this should not be interpreted to mean that PSM is equivalent to an experimental design framework.

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    We also tested if the specification of our covariates changed the results of our baseline analysis. To our baseline models, we added a non-linear profile to age along with categorical dummy variables for the family stress and drinking covariates. Our findings in Table 4 are robust to these changes; Flex1 remains a statistically significantly negative correlate of Sleep1 and Sleep3.

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    As per the data appendix, the definition of “married” includes respondents that are formally married as well as respondents living with someone as a couple.

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    The sample size of unmarried individual respondents with children is only 194 and the standard errors are accordingly large; this suggests that Sleep3 may also be significant for married respondents in the presence of a larger sample. Where this the case, it would suggest Flex1 to be significant for both martial statuses (for Sleep3), though more much more pronounced among unmarried individuals with children.


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We are grateful to Chad D. Cotti, M. Kevin McGee, and two anonymous referees for helpful comments and useful suggestions.

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Corresponding author

Correspondence to M. Ryan Haley.

Data Appendix

Data Appendix

This appendix contains additional details about the covariates.

  • Female: Equal one if respondent is female.

  • Age: Age of respondent in years.

  • Exercise: Number of occasions of vigorous physical exercise during the past 30 days.

  • # of Children: Number of children under 18 currently living with respondent.

  • Eldercare: Equals one if respondent is or has cared for family member age 65 or older in past 5 years.

  • White: Equals one if respondent is white.

  • Black: Equals one if respondent is black.

  • Hispanic: Equals one if respondent is Hispanic.

  • Married/Partnered: Equals one if respondent is married or living with someone as a couple.

  • Divorce/Separated: Equals one if respondent is divorced or separated.

  • Widow: Equals one if respondent is a widow.

  • High School: Equals one if respondent’s highest level of education completed is high school.

  • College: Equals one if respondent’s highest level of education completed is college or more.

  • Logged Hourly Earnings: Logged hourly earnings.

  • Firm Size - Small: Equals one if firm size is under 100 employees.

  • Firm Size - Large: Equals one if firm size is over 1,000 employees.

  • Shift Work: Equals one if respondent works a daytime schedule, evening shift or regular night shift.

  • Drink: Equals one if respondent is a moderate to heavy drinker.

  • Family Stress: Not thinking about work, how stressful has your personal and family life been in recent months? (1: not stressful at all– 5: extremely stressful).

  • Health: Equals one if report health is good or excellent.

  • Depression: Equals one if respondent has been bothered by feeling down, depressed, or hopeless during the past month.

  • Lose Job: Likelihood of losing current job during the next couple years (1: not at all likely–4: very likely)

  • Physical Job: Equals one if respondent strongly or somewhat agrees that his job requires a lot of physical effort.

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Haley, M.R., Miller, L.A. Correlates of flexible working arrangements, stress, and sleep difficulties in the US workforce: does the flexibility of the flexibility matter?. Empir Econ 48, 1395–1418 (2015).

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  • Stress
  • Productivity
  • Absenteeism
  • Work-family balance
  • Compressed workweek
  • Short-notice flexibility

JEL Classification

  • J24
  • J28
  • J30
  • J32
  • J81