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Explaining race, poverty, and gender disparities in advanced course-taking

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Author Info

  • Dylan Conger

    (Assistant Professor, Trachtenberg School of Public Policy and Public Administration, George Washington University)

  • Mark C. Long

    (Associate Professor, Daniel J. Evans School of Public Affairs, University of Washington)

  • Patrice Iatarola

    (Associate Professor, Department of Educational Leadership and Policy, Florida State University)

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    Abstract

    We use panel data on Florida high school students to examine race, poverty, and gender disparities in advanced course-taking. While white students are more likely to take advanced courses than black and Hispanic students, these disparities are eliminated when we condition on observable pre-high school characteristics. In fact, black and Hispanic students are more likely than observably similar white students to take advanced courses. Controlling for students' pre-high school characteristics substantially reduces poverty gaps, modestly reduces Asian-white gaps, and makes little dent in female-male gaps. Black and Hispanic students attend high schools that increase their likelihood of taking advanced courses relative to observably similar white students; this advantage is largely driven by minorities disproportionately attending magnet schools. Finally, recent federal and state efforts aimed at increasing access to advanced courses to poor and minority students appear to have succeeded in raising the share of students who take advanced courses from 2003 to 2006. However, secular trends (or spillovers of the policies to non-poor, non-minority students) have spurred faster growth for other students, contributing to widening demographic gaps in these years. © 2009 by the Association for Public Policy Analysis and Management.

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    File URL: http://hdl.handle.net/10.1002/pam.20455
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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Policy Analysis and Management.

    Volume (Year): 28 (2009)
    Issue (Month): 4 ()
    Pages: 555-576

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    Handle: RePEc:wly:jpamgt:v:28:y:2009:i:4:p:555-576

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    Web page: http://www3.interscience.wiley.com/journal/34787/home

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    1. Heather Rose & Julian R. Betts, 2004. "The Effect of High School Courses on Earnings," The Review of Economics and Statistics, MIT Press, vol. 86(2), pages 497-513, May.
    2. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," United Kingdom Stata Users' Group Meetings 2003 10, Stata Users Group.
    3. Patrick Royston, 2004. "Multiple imputation of missing values," Stata Journal, StataCorp LP, vol. 4(3), pages 227-241, September.
    4. Joseph G. Altonji, 1995. "The Effects of High School Curriculum on Education and Labor Market Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 30(3), pages 409-438.
    5. Klopfenstein, Kristin, 2004. "Advanced Placement: do minorities have equal opportunity?," Economics of Education Review, Elsevier, vol. 23(2), pages 115-131, April.
    6. James J. Heckman & Paul A. LaFontaine, 2007. "The American High School Graduation Rate: Trends and Levels," NBER Working Papers 13670, National Bureau of Economic Research, Inc.
    7. Mark C. Long & Patrice Iatarola & Dylan Conger, 2009. "Explaining Gaps in Readiness for College-Level Math: The Role of High School Courses," Education Finance and Policy, MIT Press, vol. 4(1), pages 1-33, January.
    8. Clive R Belfield & Milagros Nores & Steve Barnett & Lawrence Schweinhart, 2006. "The High/Scope Perry Preschool Program: Cost–Benefit Analysis Using Data from the Age-40 Followup," Journal of Human Resources, University of Wisconsin Press, vol. 41(1).
    9. Geiser, Saul & Santelices, Veronica, 2004. "The Role of Advanced Placement and Honors Courses in College Admissions," University of California at Berkeley, Center for Studies in Higher Education qt3ft1g8rz, Center for Studies in Higher Education, UC Berkeley.
    10. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
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