Using Student Test Scores to Measure Principal Performance

52 Pages Posted: 30 Nov 2012 Last revised: 28 Mar 2021

See all articles by Jason A. Grissom

Jason A. Grissom

University of Missouri at Columbia

Demetra Kalogrides

Stanford University

Susanna Loeb

Stanford University; National Bureau of Economic Research (NBER)

Date Written: November 2012

Abstract

Expansion of the use of student test score data to measure teacher performance has fueled recent policy interest in using those data to measure the effects of school administrators as well. However, little research has considered the capacity of student performance data to uncover principal effects. Filling this gap, this article identifies multiple conceptual approaches for capturing the contributions of principals to student test score growth, develops empirical models to reflect these approaches, examines the properties of these models, and compares the results of the models empirically using data from a large urban school district. The paper then assesses the degree to which the estimates from each model are consistent with measures of principal performance that come from sources other than student test scores, such as school district evaluations. The results show that choice of model is substantively important for assessment. While some models identify principal effects as large as 0.15 standard deviations in math and 0.11 in reading, others find effects as low as 0.02 in both subjects for the same principals. We also find that the most conceptually unappealing models, which over-attribute school effects to principals, align more closely with non-test measures than do approaches that more convincingly separate the effect of the principal from the effects of other school inputs.

Suggested Citation

Grissom, Jason A. and Kalogrides, Demetra and Loeb, Susanna, Using Student Test Scores to Measure Principal Performance (November 2012). NBER Working Paper No. w18568, Available at SSRN: https://ssrn.com/abstract=2183029

Jason A. Grissom (Contact Author)

University of Missouri at Columbia ( email )

332 Cornell Hall
Columbia, MO Columbia 65211
United States

Demetra Kalogrides

Stanford University ( email )

Stanford, CA 94305
United States

Susanna Loeb

Stanford University ( email )

School of Education 402P CERAS, 520 Galvez Mall
Stanford, CA 94305
United States
650-725-4262 (Phone)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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