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Cited by 1,918

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems

Card, David·2001·Econometrica

Abstract

This paper reviews a set of recent studies that have attempted to measure the causal effect of education on labor market earnings by using institutional features of the supply side of the education system as exogenous determinants of schooling outcomes. A simple theoretical model that highlights the role of comparative advantage in the optimal schooling decision is presented and used to motivate an extended discussion of econometric issues, including the properties of ordinary least squares and instrumental variables estimators. A review of studies that have used compulsory schooling laws, differences in the accessibility of schools, and similar features as instrumental variables for completed education reveals that the resulting estimates of the return to schooling are typically as big or bigger than the corresponding ordinary least squares estimates. One interpretation of this finding is that marginal returns to education among the low-education subgroups typically affected by supply-side innovations tend to relatively high, reflecting their high marginal costs of schooling, rather than low ability that limits their return to education.

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Metadata

Authors
Card, D.
Venue
Econometrica
Published
2001-09
Volume
69
Issue
5
Pages
1127-1160
ISSN
  • 0012-9682 (ISSN-L)
  • 1468-0262
OpenAlex
W2891018837
Cited by
1,918
References
34
FWCI
93.07
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems. https://app.cochat.ai/papers/10.1111/1468-0262.00237
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Card, D. (2001). Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems. Econometrica. https://doi.org/10.1111/1468-0262.00237

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.