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On the measurement of tasks: Does expert data get it right?

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  • Storm, Eduard

Abstract

Using German survey and expert data on job tasks, this paper explores the presence of omitted-variable bias suspected in conventional task data derived from expert assessment. I show expert task data, which is expressed at the occupation-level, introduces omitted-variable bias in task returns on the order of 24-34%. Motivated by a theoretical framework, I argue this bias results from expert data ignoring workplace heterogeneity rather than fundamental differences on the assessment of tasks between experts and workers. My findings have important implications for the interpretation of conventional task models as task returns expressed at the occupation-level are overestimated. Moreover, a rigorous comparison of the statistical performance of various models offers guidance for future research regarding choice of task data and construction of task measures.

Suggested Citation

  • Storm, Eduard, 2022. "On the measurement of tasks: Does expert data get it right?," Ruhr Economic Papers 948, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:948
    DOI: 10.4419/96973111
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    References listed on IDEAS

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    1. David Card & Jörg Heining & Patrick Kline, 2013. "Workplace Heterogeneity and the Rise of West German Wage Inequality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(3), pages 967-1015.
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    3. Brad Hershbein & Lisa B. Kahn, 2018. "Do Recessions Accelerate Routine-Biased Technological Change? Evidence from Vacancy Postings," American Economic Review, American Economic Association, vol. 108(7), pages 1737-1772, July.
    4. David H. Autor & Michael J. Handel, 2013. "Putting Tasks to the Test: Human Capital, Job Tasks, and Wages," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 59-96.
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    10. Alexandra Spitz-Oener, 2006. "Technical Change, Job Tasks, and Rising Educational Demands: Looking outside the Wage Structure," Journal of Labor Economics, University of Chicago Press, vol. 24(2), pages 235-270, April.
    11. Cortes, Guido Matias & Salvatori, Andrea, 2019. "Delving into the demand side: Changes in workplace specialization and job polarization," Labour Economics, Elsevier, vol. 57(C), pages 164-176.
    12. Storm, Eduard, 2021. "Task specialization and the native-foreign wage gap: Evidence from worker-level data," Ruhr Economic Papers 928, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. Dengler, Katharina & Matthes, Britta & Paulus, Wiebke, 2014. "Occupational Tasks in the German Labour Market : an alternative measurement on the basis of an expert database," FDZ Methodenreport 201412_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Expert vs survey task data; workplace heterogeneity; omitted-variable bias;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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