Accounting for Student Disadvantage in Value-Added Models

Eric Parsons, Cory Koedel and Li Tan
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Li Tan: University of Missouri

Journal of Educational and Behavioral Statistics, 2019, vol. 44, issue 2, 144-179

Abstract: We study the relative performance of two policy-relevant value-added models—a one-step fixed effect model and a two-step aggregated residuals model—using a simulated data set well grounded in the value-added literature. A key feature of our data generating process is that student achievement depends on a continuous measure of economic disadvantage. This is a realistic condition that has implications for model performance because researchers typically have access to only a noisy, binary measure of disadvantage. We find that one- and two-step value-added models perform similarly across a wide range of student and teacher sorting conditions, with the two-step model modestly outperforming the one-step model in conditions that best match observed sorting in real data. A reason for the generally superior performance of the two-step model is that it better handles the use of an error-prone, dichotomous proxy for student disadvantage.

Keywords: accountability; econometric analysis; educational policy; evaluation; policy analysis; teacher research (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Working Paper: Accounting for Student Disadvantage in Value-Added Models (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:44:y:2019:i:2:p:144-179

DOI: 10.3102/1076998618803889

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