Cited by 371School Choice and PerformanceTeacher Professional Development and MotivationLabor market dynamics and wage inequality

Productivity returns to experience in the teacher labor market: Methodological challenges and new evidence on long-term career improvement

Papay, John P., Kraft, Matthew A.·2015·Journal of Public Economics

Integrity signals

Registry

Crossref · 10.1016/j.jpubeco.2015.02.008

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

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Claims the paper makes

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Cites

Flagged first, then by citations

2 of the 45 references couldn’t be matched to a known paper.

Cited by

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Authors
Papay, J. P., & Kraft, M. A.
Affiliations
Brown University (US)
Corresponding author
Papay, John P.
Venue
Journal of Public Economics
Publisher
Elsevier BV
Published
2015-10
Volume
130
Pages
105-119
ISSN
0047-2727 (ISSN-L)
OpenAlex
W1978921279
Cited by
370
References
45
Citations by year
2026: 22 · 2025: 23 · 2024: 25 · 2023: 34 · 2022: 44 · 2021: 32 · 2020: 33 · 2019: 39 · 2018: 50 · 2017: 20 · 2016: 26 · 2015: 11 · 2014: 6 · 2013: 3
FWCI
178.28
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Public Economics (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Education › School Choice and Performance
  • Social Sciences › Education › Teacher Professional Development and Motivation
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
Keywords
teacher productivity, returns to experience, teacher labor market, teacher career advancement, identification assumptions, human capital accumulation, teacher turnover

About these checks

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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