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Re-Examining the Public–Catholic School Gap in STEM Opportunity to Learn: New Evidence from HSLS

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  • Shangmou Xu

    (Department of Educational Foundations, Organizations, and Policy, School of Education, University of Pittsburgh, Pittsburgh, PA 15260, USA)

  • Sean Kelly

    (Department of Educational Foundations, Organizations, and Policy, School of Education, University of Pittsburgh, Pittsburgh, PA 15260, USA)

Abstract

This paper examines public–Catholic gap in STEM opportunity to learn in the US using Mahalanobis-distance matching and adjacent categories models. Consistent with prior studies, there are significant public–Catholic differences in math and science course sequence level and total credits earned. However, we find that these gaps are largely accounted for by selection processes among students of differing family background. Moreover, we find that the Catholic school advantage in STEM opportunity to learn differs by subject; Catholic school students are more likely to enroll in advanced math courses relative to middle-level courses, while their advantage in science is concentrated in the middle of the course-taking hierarchy.

Suggested Citation

  • Shangmou Xu & Sean Kelly, 2020. "Re-Examining the Public–Catholic School Gap in STEM Opportunity to Learn: New Evidence from HSLS," Social Sciences, MDPI, vol. 9(8), pages 1-27, July.
    • Handle: RePEc:gam:jscscx:v:9:y:2020:i:8:p:137-:d:392378
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    References listed on IDEAS

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    1. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    2. Eric A. Hanushek & Ludger Wössmann, 2006. "Does Educational Tracking Affect Performance and Inequality? Differences- in-Differences Evidence Across Countries," Economic Journal, Royal Economic Society, vol. 116(510), pages 63-76, March.
    3. Markus Frlich, 2004. "Finite-Sample Properties of Propensity-Score Matching and Weighting Estimators," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 77-90, February.
    4. Vandenberghe, V. & Robin, S., 2004. "Evaluating the effectiveness of private education across countries: a comparison of methods," Labour Economics, Elsevier, vol. 11(4), pages 487-506, August.
    5. Alexis Diamond & Jasjeet S. Sekhon, 2013. "Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 932-945, July.
    6. Ulrich Kohler & Kristian Bernt Karlson & Anders Holm, 2011. "Comparing coefficients of nested nonlinear probability models," Stata Journal, StataCorp LLC, vol. 11(3), pages 420-438, September.
    7. King, Gary & Nielsen, Richard, 2019. "Why Propensity Scores Should Not Be Used for Matching," Political Analysis, Cambridge University Press, vol. 27(4), pages 435-454, October.
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