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Compulsory Schooling and Returns to Education: A Re-Examination

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  • Sophie van Huellen

    (SOAS University of London, Thornhaugh Street, Russell Square, London WC1H 0XG, UK)

  • Duo Qin

    (SOAS University of London, Thornhaugh Street, Russell Square, London WC1H 0XG, UK)

Abstract

This paper re-examines the instrumental variable (IV) approach to estimating returns to education by use of compulsory school law (CSL) in the US. We show that the IV-approach amounts to a change in model specification by changing the causal status of the variable of interest. From this perspective, the IV-OLS (ordinary least square) choice becomes a model selection issue between non-nested models and is hence testable using cross validation methods. It also enables us to unravel several logic flaws in the conceptualisation of IV-based models. Using the causal chain model specification approach, we overcome these flaws by carefully distinguishing returns to education from the treatment effect of CSL. We find relatively robust estimates for the first effect, while estimates for the second effect are hindered by measurement errors in the CSL indicators. We find reassurance of our approach from fundamental theories in statistical learning.

Suggested Citation

  • Sophie van Huellen & Duo Qin, 2019. "Compulsory Schooling and Returns to Education: A Re-Examination," Econometrics, MDPI, vol. 7(3), pages 1-20, September.
  • Handle: RePEc:gam:jecnmx:v:7:y:2019:i:3:p:36-:d:263407
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    Cited by:

    1. Duo Qin, 2019. "Let’s take the bias out of econometrics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 26(2), pages 81-98, April.
    2. Baird Matthew D. & Bozick Robert & Zaber Melanie A., 2022. "Beyond traditional academic degrees: The labor market returns to occupational credentials in the United States," IZA Journal of Labor Economics, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 11(1), pages 1-38, January.

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    More about this item

    Keywords

    instrumental variables; randomisation; research design; average return to education;
    All these keywords.

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • N32 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - U.S.; Canada: 1913-

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