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Potential for significant reductions in dropout rates: Analysis of an entire 3rd grade state cohort

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  • Cratty, Dorothyjean

Abstract

Nineteen percent of 1997–98 North Carolina 3rd graders were observed to drop out of high school. A series of logits predict probabilities of dropping out on determinants such as math and reading test scores, absenteeism, suspension, and retention, at the following grade levels: 3rd, 5th, 8th, and 9th. The same cohort and variables are used to estimate benefits to the 15,737 students admitted to a special program ostensibly for academically and intellectually gifted children. I estimate the probability of admission for schoolmates with similar ability in math and reading to be substantially higher for those from upper income households. Finally, I conclude that extending similar resources to an equal number of high-risk students, as determined by their 3rd grade predicted probabilities, would lead to a 25% reduction in the total cohort dropout rate, and that even dividing existing resources between the two groups could cut dropout rates by half that.

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  • Cratty, Dorothyjean, 2012. "Potential for significant reductions in dropout rates: Analysis of an entire 3rd grade state cohort," Economics of Education Review, Elsevier, vol. 31(5), pages 644-662.
    • Handle: RePEc:eee:ecoedu:v:31:y:2012:i:5:p:644-662
    DOI: 10.1016/j.econedurev.2012.04.001
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    References listed on IDEAS

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    1. Eide, Eric R. & Showalter, Mark H., 2001. "The effect of grade retention on educational and labor market outcomes," Economics of Education Review, Elsevier, vol. 20(6), pages 563-576, December.
    2. Greene, Jay P. & Winters, Marcus A., 2009. "The effects of exemptions to Florida's test-based promotion policy: Who is retained?: Who benefits academically?," Economics of Education Review, Elsevier, vol. 28(1), pages 135-142, February.
    3. Berrara, A., 1989. "The Interactive Effects Of Mother'S Schooling And Unsupplemented Breastfeeding On Child Health," Papers 572, Yale - Economic Growth Center.
    4. Charles T. Clotfelter & Helen F. Ladd & Jacob L. Vigdor, 2006. "Teacher-Student Matching and the Assessment of Teacher Effectiveness," Journal of Human Resources, University of Wisconsin Press, vol. 41(4).
    5. Philip J. Cook & Robert MacCoun & Clara Muschkin & Jacob Vigdor, 2008. "The negative impacts of starting middle school in sixth grade," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 104-121.
    6. Magnuson, Katherine A. & Ruhm, Christopher & Waldfogel, Jane, 2007. "Does prekindergarten improve school preparation and performance?," Economics of Education Review, Elsevier, vol. 26(1), pages 33-51, February.
    7. Kelly Bedard & Chau Do, 2005. "Are Middle Schools More Effective?: The Impact of School Structure on Student Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 40(3).
    8. Rumberger, Russell W. & Lamb, Stephen P., 2003. "The early employment and further education experiences of high school dropouts: a comparative study of the United States and Australia," Economics of Education Review, Elsevier, vol. 22(4), pages 353-366, August.
    9. Boozer, Michael & Rouse, Cecilia, 2001. "Intraschool Variation in Class Size: Patterns and Implications," Journal of Urban Economics, Elsevier, vol. 50(1), pages 163-189, July.
    10. McGee, Andrew, 2011. "Skills, standards, and disabilities: How youth with learning disabilities fare in high school and beyond," Economics of Education Review, Elsevier, vol. 30(1), pages 109-129, February.
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    Cited by:

    1. Figlio, D. & Karbownik, K. & Salvanes, K.G., 2016. "Education Research and Administrative Data," Handbook of the Economics of Education,, Elsevier.
    2. Adamecz-Völgyi, Anna, 2021. "Is raising the school leaving age enough to decrease dropping out?," GLO Discussion Paper Series 985, Global Labor Organization (GLO).
    3. Suzani Mohamad Samuri & Bahbibi Rahmatullah & Norazilawati Abdullah & Aslina Ahmad & Zainiah Mohamed Isa & Hamsa Hammed, 2018. "Early Childhood Research Landscape on Children’s Profile: Coherent Taxonomy, Motivation, Open Challenges, Recommendations and, Pathways for Future Research," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 11(5), pages 1603-1630, October.
    4. Vanessa Hanin & Jennifer Holm, 2023. "How Permeable Are the Beliefs of Future Secondary School Mathematics Teachers to Pre-Service Experiences? Looking Across Their Years of Training," SAGE Open, , vol. 13(4), pages 21582440231, December.

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    More about this item

    Keywords

    Educational economics; Human capital; Resource allocation; State and federal aid;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • H52 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Education
    • H57 - Public Economics - - National Government Expenditures and Related Policies - - - Procurement

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