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Money for nothing and stigma for free? The effect of positive discriminatory policies on education gaps

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  • Jose Mesquita Gabriel
  • Luis Catela Nunes

Abstract

This paper analyzes a compensatory education program in Portugal whose aim is to provide equal educational opportunities for children from lower socioeconomic status (SES) families by ensuring additional school resources for deprived areas. Using two administrative databases covering virtually all public schools in Portugal, we present a comprehensive evaluation of such a program addressing an important effect that has been overlooked so far in the literature: a negative stigma effect, wherein students from higher SES families become less likely to enroll in treated schools. Our staggered difference-in-differences estimates show that: 1) the Student-to-Teacher ratio decreased significantly in treated schools as a result of their entry into the program, corresponding to an average drop of 9% relative to the pre-treatment average value; 2) the proportion of students whose mothers concluded upper secondary school entering treated schools declined substantially, a decrease of around 14% of the average pre-treatment value; and 3) no effects were observed in blind-marked national exam scores in the 4th, 6th-, and 9th-grade for students coming from lower SES families, while some positive effects were found for non-blind sources of evaluation, particularly in schools where the change in additional resources was more pronounced. Our results emphasize the need to account for unanticipated risks of further aggravating segregation across schools when implementing publicly announced programs, in particular when they lead to discontinuities in terms of school eligibility.

Suggested Citation

  • Jose Mesquita Gabriel & Luis Catela Nunes, 2024. "Money for nothing and stigma for free? The effect of positive discriminatory policies on education gaps," Nova SBE Working Paper Series wp668, Universidade Nova de Lisboa, Nova School of Business and Economics.
  • Handle: RePEc:unl:unlfep:wp668
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    References listed on IDEAS

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    1. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    2. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    3. van der Klaauw, Wilbert, 2008. "Breaking the link between poverty and low student achievement: An evaluation of Title I," Journal of Econometrics, Elsevier, vol. 142(2), pages 731-756, February.
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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • H52 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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