The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Gender Wage Disparities among the Highly Educated
Open accessAbstract
In the U.S. college-educated women earn approximately 30 percent less than their non-Hispanic white male counterparts. We conduct an empirical examination of this wage disparity for four groups of women-non-Hispanic white, black, Hispanic, and Asian-using the National Survey of College Graduates, a large data set that provides unusually detailed information on higher-level education. Nonparametric matching analysis indicates that among men and women who speak English at home, between 44 and 73 percent of the gender wage gaps are accounted for by such pre-market factors as highest degree and major. When we restrict attention further to women who have "high labor force attachment" (i.e., work experience that is similar to male comparables) we account for 54 to 99 percent of gender wage gaps. Our nonparametric approach differs from familiar regression-based decompositions, so for the sake of comparison we conduct parametric analyses as well. Inferences drawn from these latter decompositions can be quite misleading.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Matching As An Econometric Evaluation Estimator
Heckman, J. J., Ichimura, H., & Todd, P. (1998) · Review of Economic Studies · doi:10.1111/1467-937x.00044 · Cited by 3,807
Human Capital and the Rise and Fall of Families
Becker, G. S., & Tomes, N. (1986) · Journal of Labor Economics · doi:10.1086/298118 · Cited by 2,913
Characterizing Selection Bias Using Experimental Data
Heckman, J., Ichimura, H., Smith, J., & Todd, P. (1998) · Econometrica · doi:10.2307/2999630 · Cited by 2,286
Accounting for the Black–White Wealth Gap: A Nonparametric Approach
Barsky, R., Bound, J., Charles, K. K., & Lupton, J. P. (2002) · Journal of the American Statistical Association · doi:10.1198/016214502388618401 · Cited by 374
Cited by
Dynamics of the Gender Gap for Young Professionals in the Financial and Corporate Sectors
Bertrand, M., Goldin, C., & Katz, L. F. (2010) · American Economic Journal: Applied Economics · doi:10.1257/app.2.3.228 · Cited by 1,256
Matching as a Tool to Decompose Wage Gaps
Ñopo, H. (2008) · Review of Economics and Statistics · doi:10.1162/rest.90.2.290 · Cited by 355
Female leadership and gender equity: Evidence from plant closure
Tate, G., & Yang, L. (2015) · Journal of Financial Economics · doi:10.1016/j.jfineco.2014.01.004 · Cited by 259
The Bias That Divides Us: The Science and Politics of Myside Thinking
Stanovich, K. E. (2021) · doi:10.7551/mitpress/13367.001.0001 · Cited by 152
Uunk, W. (2023) · Frontiers in Education · doi:10.3389/feduc.2023.1155492 · Cited by 9
Metadata
- Authors
- Black, D. A., Haviland, A. M., Sanders, S. G., & Taylor, L. J.
- Venue
- Journal of Human Resources
- Publisher
- University of Wisconsin Press
- Published
- 2008
- Volume
- 43
- Issue
- 3
- Pages
- 630-659
- ISSN
- 0022-166X (ISSN-L)
- 1548-8004
- OpenAlex
- W2158117696
- Cited by
- 228
- References
- 4
- FWCI
- 20.48
- Type
- journal article
- Language
- en
- Open access
- green
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Gender Wage Disparities among the Highly Educated. https://app.cochat.ai/papers/10.1353/jhr.2008.0030
- The paper
- Black, D. A., Haviland, A. M., Sanders, S. G., & Taylor, L. J. (2008). Gender Wage Disparities among the Highly Educated. Journal of Human Resources. https://doi.org/10.1353/jhr.2008.0030
Data sources
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.