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

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  • 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.

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File URL: http://www.nber.org/papers/t0328.pdf
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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0328.

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Date of creation: Sep 2006
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Handle: RePEc:nbr:nberte:0328

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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. 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 3.
  2. 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].
  3. 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.
  4. John Cawley & Feng Liu, 2007. "Maternal Employment and Childhood Obesity: A Search for Mechanisms in Time Use Data," NBER Working Papers 13600, National Bureau of Economic Research, Inc.
  5. 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, 02.
  6. 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.
  7. Kristin Mammen, 2011. "Fathers’ time investments in children: do sons get more?," Journal of Population Economics, Springer, vol. 24(3), pages 839-871, July.
  8. 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.

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

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