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Permanent Income and the Black-White Test Score Gap

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  • Rothstein, Jesse
  • Wozny, Nathan

Abstract

Analysts often examine the black-white test score gap conditional on family income. Typically only a current income measure is available. We argue that the gap conditional on permanent income is of greater interest, and we describe a method for identifying this gap using an auxiliary data set to estimate the relationship between current and permanent income. Current income explains only about half as much of the black-white test score gap as does permanent income, and the remaining gap in math achievement among families with the same permanent income is only 0.2 to 0.3 standard deviations in the CNLSY and ECLS samples. When we add permanent income to the controls used by Fryer and Levitt (2006), the unexplained gap in 3rd grade shrinks below 0.15 SDs, less than half of what is found with their controls.

Suggested Citation

  • Rothstein, Jesse & Wozny, Nathan, 2011. "Permanent Income and the Black-White Test Score Gap," Department of Economics, Working Paper Series qt86k5x83k, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
  • Handle: RePEc:cdl:econwp:qt86k5x83k
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    Cited by:

    1. David Brady & Marco Giesselmann & Ulrich Kohler & Anke Radenacker, 2018. "How to measure and proxy permanent income: evidence from Germany and the U.S," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(3), pages 321-345, September.
    2. David (David Patrick) Madden, 2020. "The Socioeconomic Gradient of Cognitive Test Scores: Evidence from Two Cohorts of Irish Children," Working Papers 202020, School of Economics, University College Dublin.
    3. Tymon Sloczynski, 2018. "Average Gaps and Oaxaca–Blinder Decompositions: A Cautionary Tale about Regression Estimates of Racial Differences in Labor Market Outcomes," Working Papers 127, Brandeis University, Department of Economics and International Business School.
    4. Jesse Rothstein, 2019. "Inequality of Educational Opportunity? Schools as Mediators of the Intergenerational Transmission of Income," Journal of Labor Economics, University of Chicago Press, vol. 37(S1), pages 85-123.
    5. Robert W. Fairlie & Florian Hoffmann & Philip Oreopoulos, 2014. "A Community College Instructor Like Me: Race and Ethnicity Interactions in the Classroom," American Economic Review, American Economic Association, vol. 104(8), pages 2567-2591, August.
    6. Katherine Michelmore & Susan Dynarski, 2016. "The Gap within the Gap: Using Longitudinal Data to Understand Income Differences in Student Achievement," NBER Working Papers 22474, National Bureau of Economic Research, Inc.
    7. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.
    8. Bhashkar Mazumder & Jonathan Davis, 2011. "Parental Earnings and Children's Well-Being and Future Success: An Analysis of the SIPP Matched to SSA Earnings Data," Working Papers 11-12, Center for Economic Studies, U.S. Census Bureau.
    9. Bradley Hardy, 2014. "Childhood Income Volatility and Adult Outcomes," Demography, Springer;Population Association of America (PAA), vol. 51(5), pages 1641-1665, October.
    10. Giannelli, Gianna Claudia & Rapallini, Chiara, 2019. "Parental occupation and children’s school outcomes in math," Research in Economics, Elsevier, vol. 73(4), pages 293-303.
    11. Bradley L. Hardy & Dave E. Marcotte, 2022. "Ties that bind? Family income dynamics and children’s post-secondary enrollment and persistence," Review of Economics of the Household, Springer, vol. 20(1), pages 279-303, March.
    12. Nathaniel G. Hilger, 2015. "The Great Escape: Intergenerational Mobility in the United States Since 1940," NBER Working Papers 21217, National Bureau of Economic Research, Inc.
    13. 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.
    14. Bruce Bradbury & Jane Waldfogel & Elizabeth Washbrook, 2019. "Income-Related Gaps in Early Child Cognitive Development: Why Are They Larger in the United States Than in the United Kingdom, Australia, and Canada?," Demography, Springer;Population Association of America (PAA), vol. 56(1), pages 367-390, February.
    15. Nathaniel Hilger, 2016. "Upward Mobility and Discrimination: The Case of Asian Americans," NBER Working Papers 22748, National Bureau of Economic Research, Inc.

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    Keywords

    Social and Behavioral Sciences;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination

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