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How important are omitted variables, censored scores and self-selection in analysing high-school academic achievement?

Author

Listed:
  • Guyonne Kalb

    (University of Melbourne)

  • Sholeh Maani

    (University of Auckland)

Abstract

Using a rich longitudinal data set from birth, we explore three estimation issues related to academic performance analysis. Our paper primarily examines the effect of omitting childhood and teenage characteristics (childhood ability, parental resources at different times and peer effects), which are traditionally unavailable in data sets. Additionally, we explore the potential endogeneity of pre-exam school-leaving choices (self-selection) to academic performance; and we demonstrate the effect of accounting for censored academic performance measures. We find that omitting background characteristics results in overestimation of coefficients on other characteristics (the effect of current income is overestimated by 0.21 standard deviations of the average academic performance and the effect of ethnicity by 1.38 standard deviations). This then affects the policy implications drawn: for the group who did not take the exam, the predicted performance goes from a fail to a C (or pass). We also find that accounting for censored academic performance measures affects the estimation results, but allowing for selection correction does not.

Suggested Citation

  • Guyonne Kalb & Sholeh Maani, 2011. "How important are omitted variables, censored scores and self-selection in analysing high-school academic achievement?," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 14(3), pages 307-332.
  • Handle: RePEc:ozl:journl:v:14:y:2011:i:3:p:307-332
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    References listed on IDEAS

    as
    1. Willis, Robert J & Rosen, Sherwin, 1979. "Education and Self-Selection," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 7-36, October.
    2. Stinebrickner Ralph & Stinebrickner Todd R., 2008. "The Causal Effect of Studying on Academic Performance," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 8(1), pages 1-55, June.
    3. Sandra E. Black & Paul J. Devereux & Kjell G. Salvanes, 2011. "Too Young to Leave the Nest? The Effects of School Starting Age," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 455-467, May.
    4. Montgomery, James D, 1991. "Social Networks and Labor-Market Outcomes: Toward an Economic Analysis," American Economic Review, American Economic Association, vol. 81(5), pages 1407-1418, December.
    5. Maani, Sholeh A. & Kalb, Guyonne, 2007. "Academic performance, childhood economic resources, and the choice to leave school at age 16," Economics of Education Review, Elsevier, vol. 26(3), pages 361-374, June.
    6. Beatrice Schindler Rangvid, 2010. "Source country differences in test score gaps: evidence from Denmark," Education Economics, Taylor & Francis Journals, vol. 18(3), pages 269-295.
    7. Anne C. Case & Lawrence F. Katz, 1991. "The Company You Keep: The Effects of Family and Neighborhood on Disadvantaged Youths," NBER Working Papers 3705, National Bureau of Economic Research, Inc.
    8. Card, David & Rothstein, Jesse, 2007. "Racial segregation and the black-white test score gap," Journal of Public Economics, Elsevier, vol. 91(11-12), pages 2158-2184, December.
    9. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    10. Clark, Melissa & Rothstein, Jesse & Schanzenbach, Diane Whitmore, 2009. "Selection bias in college admissions test scores," Economics of Education Review, Elsevier, vol. 28(3), pages 295-307, June.
    11. Elizabeth U. Cascio & Diane Whitmore Schanzenbach, 2016. "First in the Class? Age and the Education Production Function," Education Finance and Policy, MIT Press, vol. 11(3), pages 225-250, Summer.
    12. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 979-1014.
    13. Todd E. Elder & Darren H. Lubotsky, 2009. "Kindergarten Entrance Age and Children’s Achievement: Impacts of State Policies, Family Background, and Peers," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    14. Jonathan Sandy & Kevin Duncan, 2010. "Examining the achievement test score gap between urban and suburban students," Education Economics, Taylor & Francis Journals, vol. 18(3), pages 297-315.
    15. Kelly Bedard & Elizabeth Dhuey, 2006. "The Persistence of Early Childhood Maturity: International Evidence of Long-Run Age Effects," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(4), pages 1437-1472.
    16. Robert Haveman & Barbara Wolfe, 1995. "The Determinants of Children's Attainments: A Review of Methods and Findings," Journal of Economic Literature, American Economic Association, vol. 33(4), pages 1829-1878, December.
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    More about this item

    Keywords

    Labour Force and Employment; Size; and Structure; Human Capital; Skills; Occupational Choice; Labour Productivity; Fertility; Child Care; Demographic Economics; Public Policy;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • J18 - Labor and Demographic Economics - - Demographic Economics - - - Public Policy

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