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Ask the Child or the Parent? Survey Design and the Measurement of School Satisfaction

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Abstract

In 1965, about one thousand children in the third grade of a midsize Swedish town answered a short questionnaire about school, and their parents answered a parallel questionnaire about the same child (a design repeated in grade six and grade nine). This article uses these paired reports to revisit, in a new construct and country, two sensitivities highlighted by Conti and Pudney (2011): that response-scale format and labeling can reshape reported satisfaction distributions, and that response conditions can induce systematic, gender-differentiated departures from classical measurement error. Parents concentrate on the conventional positive category while children spread across the scale; the distributional distance between informants is largest in grade six, where both answered fully labeled five-point scales. An integrative latent model attributes to the child report extreme-category misclassification probabilities of 0.14–0.34 and to the parent report a systematic threshold shift (context/informant perspective) with noise standard deviation close to one (estimates close to the original British ones). The choice of informant changes econometric conclusions: conditional on achievement, cognitive ability is negatively associated with satisfaction only in the child's own reports, and classroom-context coefficients switch between informants. Measured satisfaction is partly an artifact of who is asked and how.

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  • Andrén, Daniela, 2026. "Ask the Child or the Parent? Survey Design and the Measurement of School Satisfaction," Working Papers 2026:5, Örebro University, School of Business.
  • Handle: RePEc:hhs:oruesi:2026_005
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    1. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
    2. Gabriella Conti & Stephen Pudney, 2011. "Survey Design and the Analysis of Satisfaction," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 1087-1093, August.
    3. Sendhil Mullainathan & Marianne Bertrand, 2001. "Do People Mean What They Say? Implications for Subjective Survey Data," American Economic Review, American Economic Association, vol. 91(2), pages 67-72, May.
    4. Clark, Andrew E., 1997. "Job satisfaction and gender: Why are women so happy at work?," Labour Economics, Elsevier, vol. 4(4), pages 341-372, December.
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    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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