Spending more of the school day in math class: Evidence from a regression discontinuity in middle school
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Average treatment effects are about one-quarter as large as the estimated benefit of a 30 percent reduction in elementary class size, or of doubling middle and high school math class time.
“Additionally, these average treatment effects are also roughly one-quarter the estimated gain from reducing class size by 30 percent in elementary grades (Kruger 1999), or the estimated gain from doubling the amount of class time middle and high school students spend in math (Taylor 2014, Cortes, Goodman, and Nomi 2015).”
From Learning Job Skills from Colleagues at Work: Evidence from a Field Experiment Using Teacher Performance Data (2020) · cites this paper as Taylor 2014
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- Authors
- Taylor, E.
- Affiliations
- Stanford University (US)
- Corresponding author
- Taylor, Eric
- Venue
- Journal of Public Economics
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 117
- Pages
- 162-181
- ISSN
- 0047-2727 (ISSN-L)
- OpenAlex
- W2032344046
- Cited by
- 74
- References
- 73
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 5 · 2023: 10 · 2022: 8 · 2021: 5 · 2020: 5 · 2019: 8 · 2018: 5 · 2017: 11 · 2016: 7 · 2015: 2
- FWCI
- 34.25
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Public Economics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Institute of Education Sciences, U.S. Department of Education (R305B090016)
- Topics
- Social Sciences › Education › School Choice and Performance
- Physical Sciences › Mathematics › Applied Mathematics › Mathematics Education and Pedagogy
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Keywords
- mathematics achievement, junior high school students, student retention, teacher assignment, class size
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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