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Measurement error in stylised and diary data on time use

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  • Pudney, Stephen
  • Yee Kan, Â Man

Abstract

We investigate the nature of measurement error in time use data. Analysis of ‘stylised’ recall questionnaire estimates and diary-based estimates of housework time from the same respondents gives evidence of systematic biases in the stylised estimates and large random errors in both types of data. We examine the effect of these measurement problems on three common types of statistical analyses in which the time use variable is used as: (i) a dependent variable, (ii) an explanatory variable, and (iii) a basis for cross-tabulations. We develop methods to correct the biases induced by these measurement errors.

Suggested Citation

  • Pudney, Stephen & Yee Kan, Â Man, 2007. "Measurement error in stylised and diary data on time use," ISER Working Paper Series 2007-03, Institute for Social and Economic Research.
    • Handle: RePEc:ese:iserwp:2007-03
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    1. Gershuny, Jonathan, 2000. "Changing Times: Work and Leisure in Postindustrial Society," OUP Catalogue, Oxford University Press, number 9780198287872.
    2. Iiris Niemi, 1993. "Systematic error in behavioural measurement: Comparing results from interview and time budget studies," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 30(2), pages 229-244, November.
    3. Jens Bonke, 2005. "Paid Work and Unpaid Work: Diary Information Versus Questionnaire Information," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 70(3), pages 349-368, February.
    4. Yee Kan, Â Man, 2006. "Measuring housework participation: the gap between ‘stylised’ questionnaire estimates and diary-based estimates," ISER Working Paper Series 2006-11, Institute for Social and Economic Research.
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    Cited by:

    1. Yee Kan, Â Man, 2006. "Measuring housework participation: the gap between ‘stylised’ questionnaire estimates and diary-based estimates," ISER Working Paper Series 2006-11, Institute for Social and Economic Research.
    2. Almudena Sevilla-Sanz & Mark L. Bryan, 2007. "Does Housework Lower Wages and Why? Evidence for Britain," Economics Series Working Papers 331, University of Oxford, Department of Economics.
    3. Steffen Otterbach & Alfonso Sousa-Poza, 2010. "How Accurate are German Work-time Data? A Comparison of Time-diary Reports and Stylized Estimates," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 97(3), pages 325-339, July.
    4. David Johnston & Carol Propper & Stephen Pudney & Michael Shields, 2014. "Child Mental Health And Educational Attainment: Multiple Observers And The Measurement Error Problem," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 880-900, September.
    5. Man Yee Kan, 2008. "Does gender trump money? Housework hours of husbands and wives in Britain," Work, Employment & Society, British Sociological Association, vol. 22(1), pages 45-66, March.
    6. Man Kan, 2008. "Measuring Housework Participation: The Gap between “Stylised” Questionnaire Estimates and Diary-based Estimates," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 86(3), pages 381-400, May.
    7. Andrea Neri & Roberta Zizza, 2010. "Income reporting behaviour in sample surveys," Temi di discussione (Economic working papers) 777, Bank of Italy, Economic Research and International Relations Area.
    8. Man Kan & Jonathan Gershuny, 2009. "Calibrating Stylised Time Estimates Using UK Diary Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 93(1), pages 239-243, August.
    9. Bettina Sonnenberg & Michaela Riediger & Cornelia Wrzus & Gert G. Wagner, 2011. "Measuring Time Use in Surveys: How Valid Are Time Use Questions in Surveys? Concordance of Survey and Experience Sampling Measures," SOEPpapers on Multidisciplinary Panel Data Research 390, DIW Berlin, The German Socio-Economic Panel (SOEP).

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