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If You Don’t Snooze You Lose Health and Gain Weight Evidence from a Regression Discontinuity Design

Author

Listed:
  • Osea Giuntella

    (University of Oxford)

  • Fabrizio Mazzonna

    (Università della Svizzera Italiana (USI))

Abstract
Sleep deprivation is increasingly recognized as a public health challenge. While several studies provided evidence of important associations between sleep deprivation and health outcomes, it is less clear whether sleep deprivation is a cause or a marker of poor health. This paper studies the causal effects of sleep on health status and obesity exploiting the relationship between sunset light and circadian rhythms and using time-zone boundaries as an exogenous source of variation in sleep duration and quality. Using data from the American Time Use Survey, we show that individuals living in counties on the eastern side of a time zone boundary go to bed later and sleep less than individuals on the opposite side of the time zone boundary. These findings are driven by individuals whose biological schedules and time use are constrained by social schedules (i.e., work schedules, school starting times). Exploit- ing these discontinuities, we find evidence that sleep deprivation increases the likelihood of reporting poor health status and the incidence of obesity. Our results suggest that the increase in obesity is explained by both changes in eating behavior and a decrease in physical activity.

Suggested Citation

  • Osea Giuntella & Fabrizio Mazzonna, 2015. "If You Don’t Snooze You Lose Health and Gain Weight Evidence from a Regression Discontinuity Design," IdEP Economic Papers 1505, USI Università della Svizzera italiana.
    • Handle: RePEc:lug:wpidep:1505
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    File URL: http://doc.rero.ch/record/256068/files/wp1505.pdf
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    References listed on IDEAS

    as
    1. Gibson, Matthew & Shrader, Jeffrey, 2014. "Time Use and Productivity: The Wage Returns to Sleep," University of California at San Diego, Economics Working Paper Series qt8zp518hc, Department of Economics, UC San Diego.
    2. Jin, Lawrence & Ziebarth, Nicolas R., 2015. "Does Daylight Saving Time Really Make Us Sick?," IZA Discussion Papers 9088, Institute of Labor Economics (IZA).
    3. Till Roenneberg, 2013. "The human sleep project," Nature, Nature, vol. 498(7455), pages 427-428, June.
    4. Stephanie M. Greer & Andrea N. Goldstein & Matthew P. Walker, 2013. "The impact of sleep deprivation on food desire in the human brain," Nature Communications, Nature, vol. 4(1), pages 1-7, October.
    5. Cohen, D.A. & Story, M., 2014. "Mitigating the health risks of dining out: The need for standardized portion sizes in restaurants," American Journal of Public Health, American Public Health Association, vol. 104(4), pages 586-590.
    6. Biddle, Jeff E & Hamermesh, Daniel S, 1990. "Sleep and the Allocation of Time," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 922-943, October.
    7. Jennifer L. Doleac & Nicholas J. Sanders, 2015. "Under the Cover of Darkness: How Ambient Light Influences Criminal Activity," The Review of Economics and Statistics, MIT Press, vol. 97(5), pages 1093-1103, December.
    8. Daniel S. Hamermesh & Caitlin Knowles Myers & Mark L. Pocock, 2008. "Cues for Timing and Coordination: Latitude, Letterman, and Longitude," Journal of Labor Economics, University of Chicago Press, vol. 26(2), pages 223-246, April.
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    Cited by:

    1. Jin, L. & Ziebarth, N.R., 2015. "Sleep and Human Capital: Evidence from Daylight Saving Time," Health, Econometrics and Data Group (HEDG) Working Papers 15/27, HEDG, c/o Department of Economics, University of York.

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    More about this item

    Keywords

    Health; Obesity; Sleep Deprivation; Time Use; Regression Discontinuity;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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