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Cited by 1,241School Choice and PerformanceEducational Assessment and ImprovementTeacher Education and Assessments

Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates

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Chetty, Raj, Friedman, John N., Rockoff, Jonah E.·2014·American Economic Review
DOI 10.1257/aer.104.9.2593
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Abstract

Are teachers' impacts on students' test scores (value-added) a good measure of their quality? One reason this question has sparked debate is disagreement about whether value-added (VA) measures provide unbiased estimates of teachers' causal impacts on student achievement. We test for bias in VA using previously unobserved parent characteristics and a quasi-experimental design based on changes in teaching staff. Using school district and tax records for more than one million children, we find that VA models which control for a student's prior test scores provide unbiased forecasts of teachers' impacts on student achievement. (JEL H75, I21, J24, J45)

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  • Recent experimental and quasi-experimental analyses provide strong empirical support for the claim that teacher effect estimates are not biased by non-random sorting of students to teachers when student achievement is the outcome.

    “Recent experimental (Kane, McCaffrey, Miller, & Staiger, 2013) and quasi-experimental (Chetty et al., 2014) analyses provide strong empirical support for this claim when student achievement is the outcome of interest.”

    From Teacher and Teaching Effects on Students’ Attitudes and Behaviors (2017) · cites this paper as Chetty et al., 2014

  • This corresponds to an increase of roughly 0.9 percentile points in the test score distribution (von Hippel, 2025) and about one-fifth of the gain associated with a one standard deviation increase in teacher value added (Chetty, Friedman and Rockoff, 2014).

    “For comparison, this corresponds to an increase of roughly 0.9 percentile points in the test score distribution (von Hippel, 2025) and about one-fifth of the gain associated with a one standard deviation increase in teacher value added (Chetty, Friedman and Rockoff, 2014).”

    From The Effects of School Phone Bans: National Evidence from Lockable Pouches (2026) · cites this paper as Chetty, Friedman and Rockoff, 2014

  • This concentration of effects in math is consistent with a broader literature in the economics of education finding that interventions often generate larger or more detectable impacts in math than in ELA.

    “This concentration of effects in math is consistent with a broader literature in the economics of education finding that interventions often generate larger or more detectable impacts in math than in ELA (e.g., Dee and Jacob, 2011; Dobbie and Fryer Jr, 2011; Chetty, Friedman and Rockoff, 2014).”

    From The Effects of School Phone Bans: National Evidence from Lockable Pouches (2026) · cites this paper as Chetty, Friedman and Rockoff, 2014

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Authors
Chetty, R., Friedman, J. N., & Rockoff, J. E.
Affiliations
  • Harvard University (US)
  • Columbia University (US)
ORCID
Chetty, Raj
Venue
American Economic Review
Publisher
American Economic Association
Published
2014-09-01
Volume
104
Issue
9
Pages
2593-2632
ISSN
0002-8282 (ISSN-L)
DOI
10.1257/aer.104.9.2593
OpenAlex
W1984288743
Cited by
1,241
References
6
Citations by year
2026: 71 · 2025: 99 · 2024: 101 · 2023: 105 · 2022: 144 · 2021: 100 · 2020: 119 · 2019: 101 · 2018: 90 · 2017: 94 · 2016: 112 · 2015: 67 · 2014: 29 · 2013: 4 · 2012: 1
FWCI
519.46
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • American Economic Review (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
Funders
National Science Foundation
Topics
  • Social Sciences › Education › School Choice and Performance
  • Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
  • Social Sciences › Education › Teacher Education and Assessments
Keywords
teacher value-added, teacher quality, measurement bias, academic performance, test scores, teacher turnover

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