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Test Questions, Economic Outcomes, and Inequality

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Abstract

Standard achievement scales aggregate test questions without considering their relationship to economic outcomes. This paper uses question-level data to improve the measurement of achievement in two ways. First, the paper constructs alternative achievement scales by relating individual questions directly to school completion and labor market outcomes. Second, the paper leverages the question data to construct multiple such scales in order to correct for biases stemming from measurement error. These new achievement scales rank students differently than standard scales and typically yield achievement gaps by race, gender, and household income that are larger by 0.1 to 0.5 standard deviations. Differential performance on test questions can fully explain black-white differences in both wages and lifetime earnings and can explain roughly half of the difference in these outcomes between youth from high- versus low-income households. By contrast, test questions do not explain gender differences in labor market outcomes.

Suggested Citation

  • Eric R. Nielsen, 2019. "Test Questions, Economic Outcomes, and Inequality," Finance and Economics Discussion Series 2019-013, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:2019-13
    DOI: 10.17016/FEDS.2019.013
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    Cited by:

    1. Evan Riehl & Meredith Welch, 2023. "Accountability, Test Prep Incentives, and the Design of Math and English Exams," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(1), pages 60-96, January.

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    More about this item

    Keywords

    Human capital; Inequality; Achievement gaps; Measurement error;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education

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