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Is Gifted Education a Bright Idea? Assessing the Impact of Gifted and Talented Programs on Students

Author

Listed:
  • Sa A. Bui
  • Steven G. Craig
  • Scott A. Imberman

Abstract

We evaluate the impact of Gifted and Talented (GT) programs on students through a regression discontinuity (RD) design, and by analyzing a randomized lottery for elite magnet GT schools. We show that GT students in each analysis are exposed to higher achieving peers and, in the RD sample, a more advanced curriculum. We find that achievement for marginal students neither improves nor worsens from GT services in the short run. We also find that lottery winners only perform better in science. Using a bounding analysis we cannot rule out zero, though we do not find any significant negative effects.

Suggested Citation

  • Sa A. Bui & Steven G. Craig & Scott A. Imberman, 2014. "Is Gifted Education a Bright Idea? Assessing the Impact of Gifted and Talented Programs on Students," American Economic Journal: Economic Policy, American Economic Association, vol. 6(3), pages 30-62, August.
  • Handle: RePEc:aea:aejpol:v:6:y:2014:i:3:p:30-62
    Note: DOI: 10.1257/pol.6.3.30
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    Citations

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    Cited by:

    1. Barrow, Lisa & Sartain , Lauren & de la Torre, Marisa, 2016. "The Role of Selective High Schools in Equalizing Educational Outcomes: Heterogeneous Effects by Neighborhood Socioeconomic Status," Working Paper Series WP-2016-17, Federal Reserve Bank of Chicago.
    2. Glenn Ellison & Ashley Swanson, 2016. "Do Schools Matter for High Math Achievement? Evidence from the American Mathematics Competitions," American Economic Review, American Economic Association, vol. 106(6), pages 1244-1277, June.
    3. Zhang, Hongliang, 2016. "Identification of treatment effects under imperfect matching with an application to Chinese elite schools," Journal of Public Economics, Elsevier, vol. 142(C), pages 56-82.
    4. repec:spr:jlabre:v:39:y:2018:i:2:d:10.1007_s12122-017-9252-9 is not listed on IDEAS
    5. Nirav Mehta, 2015. "An Economic Approach to Generalize Findings from Regression-Discontinuity Designs," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20156, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    6. Park, Albert & Shi, Xinzheng & Hsieh, Chang-tai & An, Xuehui, 2015. "Magnet high schools and academic performance in China: A regression discontinuity design," Journal of Comparative Economics, Elsevier, vol. 43(4), pages 825-843.
    7. Figlio, D. & Karbownik, K. & Salvanes, K.G., 2016. "Education Research and Administrative Data," Handbook of the Economics of Education, Elsevier.
    8. David Card & Laura Giuliano, 2016. "Can Tracking Raise the Test Scores of High-Ability Minority Students?," American Economic Review, American Economic Association, vol. 106(10), pages 2783-2816, October.
    9. Booij, Adam S. & Haan, Ferry & Plug, Erik, 2017. "Can Gifted and Talented Education Raise the Academic Achievement of All High-Achieving Students?," IZA Discussion Papers 10836, Institute for the Study of Labor (IZA).
    10. Booij, Adam S. & Haan, Ferry & Plug, Erik, 2016. "Enriching Students Pays Off: Evidence from an Individualized Gifted and Talented Program in Secondary Education," IZA Discussion Papers 9757, Institute for the Study of Labor (IZA).

    More about this item

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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