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Non-response in the American Time Use Survey: Who Is Missing from the Data and How Much Does It Matter?

Author

Listed:
  • Katharine G. Abraham
  • Aaron Maitland
  • Suzanne M. Bianchi

Abstract

This paper examines non-response in a large government survey. The response rate for the American Time Use Survey (ATUS) has been below 60 percent for the first two years of its existence, raising questions about whether the results can be generalized to the target population. The paper begins with an analysis of the types of non-response encountered in the ATUS. We find that non-contact accounts for roughly 60 percent of ATUS non-response, with refusals accounting for roughly 40 percent. Next, we examine two hypotheses about the causes of this non-response. We find little support for the hypothesis that busy people are less likely to respond to the ATUS, but considerable support for the hypothesis that people who are weakly integrated into their communities are less likely to respond, mostly because they are less likely to be contacted. Finally, we compare aggregate estimates of time use calculated using the ATUS base weights without any adjustment for non-response to estimates calculated using the ATUS final weights with a non-response adjustment and to estimates calculated using weights that incorporate our own non-response adjustments based on a propensity model. While there are some modest differences, the three sets of estimates are broadly similar. The paper ends with a discussion of survey design features, their effect on the types and level of non-response, and the tradeoffs associated with different design choices.

Suggested Citation

  • Katharine G. Abraham & Aaron Maitland & Suzanne M. Bianchi, 2006. "Non-response in the American Time Use Survey: Who Is Missing from the Data and How Much Does It Matter?," NBER Technical Working Papers 0328, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberte:0328
    Note: CH LS TWP
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    References listed on IDEAS

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    1. Jeffrey E. Zabel, 1998. "An Analysis of Attrition in the Panel Study of Income Dynamics and the Survey of Income and Program Participation with an Application to a Model of Labor Market Behavior," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 479-506.
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    Cited by:

    1. Jonas Wood & Karel Neels & Tine Kil, 2014. "The educational gradient of childlessness and cohort parity progression in 14 low fertility countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(46), pages 1365-1416, December.
    2. Jens Bonke & Mette Deding & Mette Lausten & Leslie S. Stratton, 2008. "Intra-Household Specialization in Housework in the United States and Denmark," Social Science Quarterly, Southwestern Social Science Association, vol. 89(4), pages 1023-1043.
    3. Laura Fumagalli & Heather Laurie & Peter Lynn, 2013. "Experiments with methods to reduce attrition in longitudinal surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 499-519, February.
    4. Cawley, John & Liu, Feng, 2012. "Maternal employment and childhood obesity: A search for mechanisms in time use data," Economics & Human Biology, Elsevier, vol. 10(4), pages 352-364.
    5. Burns, Christopher & Prager, Daniel & Ghosh, Sujit & Goodwin, Barry, 2015. "Imputing for Missing Data in the ARMS Household Section: A Multivariate Imputation Approach," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205291, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    6. Kleinert, Corinna & Ruland, Michael & Trahms, Annette, 2013. "Bias in einem komplexen Surveydesign : Ausfallprozesse und Selektivität in der IAB-Befragung ALWA," FDZ Methodenreport 201302_de, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    7. repec:spr:jhappi:v:19:y:2018:i:1:d:10.1007_s10902-016-9817-y is not listed on IDEAS
    8. Stella Chatzitheochari & Sara Arber, 2011. "Identifying the Third Agers: An Analysis of British Retirees' Leisure Pursuits," Sociological Research Online, Sociological Research Online, vol. 16(4), pages 1-3.
    9. Joshua Graff Zivin & Matthew Neidell, 2014. "Temperature and the Allocation of Time: Implications for Climate Change," Journal of Labor Economics, University of Chicago Press, vol. 32(1), pages 1-26.
    10. Kristine L. West, 2014. "New Measures of TeachersÕ Work Hours and Implications for Wage Comparisons," Education Finance and Policy, MIT Press, vol. 9(3), pages 231-263, July.
    11. Suzanne Bianchi & Laurent Lesnard & Tiziana Nazio & Sara Raley, 2014. "Gender and time allocation of cohabiting and married women and men in France, Italy, and the United States," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(8), pages 183-216, July.
    12. Yoonjoo Lee & Sandra L. Hofferth & Sarah M. Flood & Kimberly Fisher, 2016. "Reliability, Validity, and Variability of the Subjective Well-Being Questions in the 2010 American Time Use Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 126(3), pages 1355-1373, April.
    13. William Michelson & Ugo Lachapelle, 2016. "Patterns of Walking Among Employed, Urban Canadians: Variations by Commuting Mode, Time of Day, and Days of the Week," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 11(4), pages 1321-1340, December.
    14. Charlene Kalenkoski & Karen Hamrick & Margaret Andrews, 2011. "Time Poverty Thresholds and Rates for the US Population," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 104(1), pages 129-155, October.
    15. Julie L. Hotchkiss, 2017. "Decennial Census Return Rates: The Role of Social Capital," Working Papers 17-39, Center for Economic Studies, U.S. Census Bureau.
    16. Jay Stewart, 2014. "The importance and challenges of measuring work hours," IZA World of Labor, Institute for the Study of Labor (IZA), pages 1-95, November.
    17. John Cawley & Feng Liu, 2007. "Mechanisms for the Association Between Maternal Employment and Child Cognitive Development," NBER Working Papers 13609, National Bureau of Economic Research, Inc.
    18. Katharine G. Abraham & Sara E. Helms & Stanley Presser, 2008. "How Social Processes Distort Measurement: The Impact of Survey Nonresponse on Estimates of Volunteer Work," NBER Working Papers 14076, National Bureau of Economic Research, Inc.
    19. Jorik Vergauwen & Jonas Wood & David De Wachter & Karel Neels, 2015. "Quality of demographic data in GGS Wave 1," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(24), pages 723-774, March.
    20. Kristin Mammen, 2011. "Fathers’ time investments in children: do sons get more?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 24(3), pages 839-871, July.

    More about this item

    JEL classification:

    • J2 - Labor and Demographic Economics - - Demand and Supply of Labor

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    1. Papers and articles using the American Time Use Survey (ATUS)

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