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Predicting postsecondary attendance by family income in the United States using multilevel regression with poststratification

Author

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  • Skinner, Benjamin T.
  • Doyle, William R.

Abstract

Despite billions of dollars spent yearly to fund higher education for low-income youth, no government agency tracks how many low-income young people attend college by state. Whereas proxy measures like Pell grant receipt address the number of already enrolled low-income students, direct estimates from U.S. Census surveys likely overestimate low-income youth enrollment due to their design. Using Bayesian multilevel regression with poststratification (MRP) to estimate postsecondary attendance rates by family income in each of the 50 states and the District of Columbia, we find substantial variation in attendance rates between income groups across the country.

Suggested Citation

  • Skinner, Benjamin T. & Doyle, William R., 2024. "Predicting postsecondary attendance by family income in the United States using multilevel regression with poststratification," Economics of Education Review, Elsevier, vol. 99(C).
    • Handle: RePEc:eee:ecoedu:v:99:y:2024:i:c:s0272775724000025
    DOI: 10.1016/j.econedurev.2024.102508
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    More about this item

    Keywords

    College access; Low income; Multilevel regression with poststratification; MRP;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • I22 - Health, Education, and Welfare - - Education - - - Educational Finance; Financial Aid
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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