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The Income-Achievement Gap and Adult Outcome Inequality

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Abstract

This paper discusses various methods for assessing group differences in academic achievement using only the ordinal content of achievement test scores. Researchers and policymakers frequently draw conclusions about achievement differences between various populations using methods that rely on the cardinal comparability of test scores. This paper shows that such methods can lead to erroneous conclusions in an important application: measuring changes over time in the achievement gap between youth from high- and low-income households. Commonly-employed, cardinal methods suggest that this "income-achievement gap" did not change between the National Longitudinal Surveys of Youth (NLSY) 1979 and 1997 surveys. In contrast, ordinal methods show that this gap narrowed substantially for reading achievement and may have narrowed for math achievement as well. In fact, any weighting scheme that places more value on higher test scores must conclude that the reading income-achievement gap decreased between these two surveys. The situation for math achievement is more complex, but low-income students in the middle and high deciles of the low-income math achievement distribution unambiguously gained relative to their high-income peers. Furthermore, an anchoring exercise suggests that the narrowing of the income-achievement gap corresponds to an economically significant convergence in lifetime labor wealth and school completion rates for youth from high- and low-income backgrounds.

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  • Eric R. Nielsen, 2015. "The Income-Achievement Gap and Adult Outcome Inequality," Finance and Economics Discussion Series 2015-41, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2015-41
    DOI: 10.17016/FEDS.2015.041
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    Cited by:

    1. 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.).
    2. Shirin A. Hashim & Thomas J. Kane & Thomas Kelley-Kemple & Mary E. Laski & Douglas O. Staiger, 2020. "Have Income-Based Achievement Gaps Widened or Narrowed?," NBER Working Papers 27714, National Bureau of Economic Research, Inc.
    3. Eric A. Hanushek & Paul E. Peterson & Laura M. Talpey & Ludger Woessmann, 2019. "The Unwavering SES Achievement Gap: Trends in U.S. Student Performance," NBER Working Papers 25648, National Bureau of Economic Research, Inc.
    4. Eric A. Hanushek & Paul E. Peterson & Laura M. Talpey & Ludger Woessmann, 2020. "Long-Run Trends in the U.S. SES-Achievement Gap," CESifo Working Paper Series 8111, CESifo.
    5. Richard J. Murnane & Sean F. Reardon, 2017. "Long-Term Trends in Private School Enrollments by Family Income," NBER Working Papers 23571, National Bureau of Economic Research, Inc.
    6. Christian Belzil & Jörgen Hansen, 2020. "The evolution of the US family income–schooling relationship and educational selectivity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 841-859, November.
    7. Eric A. Hanushek & Paul E. Peterson & Laura M. Talpey & Ludger Woessmann, 2020. "Long-run Trends in the U.S. SES-Achievement Gap," NBER Working Papers 26764, National Bureau of Economic Research, Inc.
    8. Jacob, B & Rothstein, J, 2016. "The measurement of student ability in modern assessment systems," Department of Economics, Working Paper Series qt24r2j30b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    9. Brian Jacob & Jesse Rothstein, 2016. "The Measurement of Student Ability in Modern Assessment Systems," Journal of Economic Perspectives, American Economic Association, vol. 30(3), pages 85-108, Summer.
    10. Eric R. Nielsen, 2015. "Achievement Gap Estimates and Deviations from Cardinal Comparability," Finance and Economics Discussion Series 2015-40, Board of Governors of the Federal Reserve System (U.S.).

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    More about this item

    Keywords

    Achievement inequality; anchoring; human capital; measurement of inequality; ordinal statistics;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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