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Connected networks in principal value-added models

Author

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  • Bartanen, Brendan
  • Husain, Aliza N.

Abstract

A growing literature uses value-added (VA) models to quantify principals’ contributions to improving student outcomes. Principal VA is typically estimated using a connected networks model that includes both principal and school fixed effects (FE) to isolate principal effectiveness from fixed school factors that principals cannot control. While conceptually appealing, high-dimensional FE regression models require sufficient variation to produce accurate VA estimates. Using simulation methods applied to administrative data from Tennessee and New York City, we show that limited mobility of principals among schools yields connected networks that are extremely sparse, where VA estimates are either highly localized or statistically unreliable. When comparing principals across schools, employing a random effects shrinkage estimator is shown to alleviate estimation error to increase the reliability of principal VA in our simulations. For within-school rankings of principals, VA estimates from models with both principal-by-school FE and school FE perform best.

Suggested Citation

  • Bartanen, Brendan & Husain, Aliza N., 2022. "Connected networks in principal value-added models," Economics of Education Review, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:ecoedu:v:90:y:2022:i:c:s0272775722000668
    DOI: 10.1016/j.econedurev.2022.102292
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    References listed on IDEAS

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    1. Di Liberto, Adriana & Giua, Ludovica & Schivardi, Fabiano & Sideri, Marco & Sulis, Giovanni, 2023. "Managerial Practices and Student Performance: Evidence from Changes in School Principals," IZA Discussion Papers 16203, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Value-added models; School leadership; Principal quality; Panel data methods;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J45 - Labor and Demographic Economics - - Particular Labor Markets - - - Public Sector Labor Markets

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