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Information Frictions in Education and Inequality

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  • Ana Figueiredo

    (Universitat Pompeu Fabra and Barcelona GSE)

Abstract

Why does the place where children grow up shape their opportunities in life? This paper explores the role of imperfect information and local information transmission as a novel explanation. First, I uncover a new empirical fact: when the college premium is low, a higher share of college graduates living in a school-district is associated with lower college enrollment of students graduating from that district. While this pattern is hard to reconcile through models with local spillovers in the production of human capital, I show that it is consistent with a model featuring imperfect information and local learning. The key elements are uncertainty about the skill premium and learning through signals of wages earned by nearby college graduates. In this environment, more exposure to highly educated neighbors brings more information about the skill premium. However, this only translates into more education if the observed wages generate the perception of a higher skill premium. Calibrating the model to match micro data from Detroit, I find that this novel mechanism explains more than half of the college enrollment gap between children of parents with a college degree and children from parents with a lower education level. Implementing a disclosure policy that corrects inaccurate perceptions about the skill premium closes this gap substantially.

Suggested Citation

  • Ana Figueiredo, 2018. "Information Frictions in Education and Inequality," 2018 Meeting Papers 804, Society for Economic Dynamics.
  • Handle: RePEc:red:sed018:804
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    File URL: https://economicdynamics.org/meetpapers/2018/paper_804.pdf
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    References listed on IDEAS

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    1. repec:eee:pubeco:v:157:y:2018:i:c:p:184-211 is not listed on IDEAS
    2. Teodora Boneva & Christopher Rauh, 2017. "Socio-Economic Gaps in University Enrollment: The Role of Perceived Pecuniary and Non-Pecuniary Returns," Working Papers 2017-080, Human Capital and Economic Opportunity Working Group.
    3. Bleemer, Zachary & Zafar, Basit, 2014. "Information heterogeneity and intended college enrollment," Staff Reports 685, Federal Reserve Bank of New York.
    4. Pablo D. Fajgelbaum & Edouard Schaal & Mathieu Taschereau-Dumouchel, 2017. "Uncertainty Traps," The Quarterly Journal of Economics, Oxford University Press, vol. 132(4), pages 1641-1692.
    5. Patrick Bayer & Fernando Ferreira & Robert McMillan, 2007. "A Unified Framework for Measuring Preferences for Schools and Neighborhoods," Journal of Political Economy, University of Chicago Press, vol. 115(4), pages 588-638, August.
    6. Belfield, Chris & Boneva, Teodora & Rauh, Christopher & Shaw, Jonathan, 2016. "Money or Fun? Why Students Want to Pursue Further Education," IZA Discussion Papers 10136, Institute of Labor Economics (IZA).
    7. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
    8. Bleemer, Zachary & Zafar, Basit, 2018. "Intended college attendance: Evidence from an experiment on college returns and costs," Journal of Public Economics, Elsevier, vol. 157(C), pages 184-211.
    9. Durlauf, Steven N, 1996. "A Theory of Persistent Income Inequality," Journal of Economic Growth, Springer, vol. 1(1), pages 75-93, March.
    10. Rebecca Diamond, 2016. "The Determinants and Welfare Implications of US Workers' Diverging Location Choices by Skill: 1980-2000," American Economic Review, American Economic Association, vol. 106(3), pages 479-524, March.
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