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Tobit or OLS? An Empirical Evaluation Under Different Diary Window Lengths


  • Jennifer Foster

    () (School of Economics, The University of New South Wales)

  • Charlene Kalenkoski

    () (Department of Economics, Ohio University)


Time use researchers frequently debate whether it is more appropriate to fit censored regression (Tobit) models using maximum likelihood estimation or linear models using ordinary least squares (OLS) to explain individuals’ allocations of time to different activities as recorded in time-diary data. One side argues that estimation of Tobit models addresses the significant censoring (i.e., large numbers of zeros) typically found in time-diary data and that OLS estimation leads to biased and inconsistent estimates. The opposing side argues that optimization occurs over a longer period than that covered by the typical time diary, and thus that reported zeros represent measurement error rather than true non-participation in the activity, in which case OLS is preferred. We use the Australian Time Use Surveys, which record information for two consecutive diary days, to estimate censored and linear versions of a parental child care model for both 24-hour and 48-hour windows of observation in order to determine the empirical consequences of estimation technique and diary length. We find a moderate amount of measurement error when we use the 24-hour window compared to the 48-hour window, but a large number of zeros in the shorter window remain zeroes when we double the window length. Most of the qualitative conclusions we draw are similar for the two windows of observation and the two estimation methods, although there are some slight differences in the magnitudes and statistical significance of the estimates. Importantly, Tobit estimates appear to be more sensitive to window length than OLS estimates.

Suggested Citation

  • Jennifer Foster & Charlene Kalenkoski, 2010. "Tobit or OLS? An Empirical Evaluation Under Different Diary Window Lengths," Discussion Papers 2010-01, School of Economics, The University of New South Wales.
  • Handle: RePEc:swe:wpaper:2010-01

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    Tobit; OLS; time-diary data;

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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