The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Do Women Avoid Salary Negotiations? Evidence from a Large-Scale Natural Field Experiment
Open accessAbstract
One explanation advanced for the persistent gender pay differences in labor markets is that women avoid salary negotiations. By using a natural field experiment that randomizes nearly 2,500 job seekers into jobs that vary important details of the labor contract, we are able to observe both the extent of salary negotiations and the nature of sorting. We find that when there is no explicit statement that wages are negotiable, men are more likely to negotiate for a higher wage, whereas women are more likely to signal their willingness to work for a lower wage. However, when we explicitly mention the possibility that wages are negotiable, these differences disappear completely. In terms of sorting, we find that men, in contrast to women, prefer job environments where the “rules of wage determination” are ambiguous. This leads to the gender gap being much more pronounced in jobs that leave negotiation of wage ambiguous. This paper was accepted by Gérard P. Cachon, behavioral economics.
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
A threat in the air: How stereotypes shape intellectual identity and performance
Steele, C. M. (1997) · American Psychologist · doi:10.1037/0003-066x.52.6.613 · Cited by 6,770
Gender Differences in Preferences
Croson, R., & Gneezy, U. (2009) · Journal of Economic Literature · doi:10.1257/jel.47.2.448 · Cited by 5,694
Stereotype Threat and Women's Math Performance
Spencer, S. J., Steele, C. M., & Quinn, D. M. (1999) · Journal of Experimental Social Psychology · doi:10.1006/jesp.1998.1373 · Cited by 3,435
Do Women Shy Away From Competition? Do Men Compete Too Much?
Niederle, M., & Vesterlund, L. (2007) · The Quarterly Journal of Economics · doi:10.1162/qjec.122.3.1067 · Cited by 3,186
Performance in competitive environments: gender differences
Gneezy, U., Niederle, M., & Rustichini, A. (2003) · The Quarterly Journal of Economics · doi:10.1162/00335530360698496 · Cited by 1,997
Orchestrating Impartiality: The Impact of “Blind” Auditions on Female Musicians
Goldin, C., & Rouse, C. (2000) · American Economic Review · doi:10.1257/aer.90.4.715 · Cited by 1,754
Blau, F. D., & Kahn, L. M. (2000) · Journal of Economic Perspectives · doi:10.1257/jep.14.4.75 · Cited by 1,458
Strong Evidence for Gender Differences in Risk Taking
Charness, G., & Gneezy, U. (2012) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2011.06.007 · Cited by 1,357
Chapter 113 Men, Women and Risk Aversion: Experimental Evidence
Eckel, C. C., & Grossman, P. J. (2008) · Handbook of Experimental Economics Results · doi:10.1016/s1574-0722(07)00113-8 · Cited by 924
Bowles, H. R., Babcock, L., & Lai, L. (2007) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2006.09.001 · Cited by 857
Cited by
Gender and the labor market: What have we learned from field and lab experiments?
Azmat, G., & Petrongolo, B. (2014) · Labour Economics · doi:10.1016/j.labeco.2014.06.005 · Cited by 314
O’Meara, K., Kuvaeva, A., Nyunt, G., Waugaman, C., & Jackson, R. (2017) · American Educational Research Journal · doi:10.3102/0002831217716767 · Cited by 292
Gender differences in how scientists present the importance of their research: observational study
Lerchenmueller, M. J., Sorenson, O., & Jena, A. B. (2019) · BMJ · doi:10.1136/bmj.l6573 · Cited by 211
Fairness and Bias in Algorithmic Hiring: A Multidisciplinary Survey
Fabris, A., Baranowska, N., Dennis, M. J., Graus, D., Hacker, P., Saldivar, J., Zuiderveen Borgesius, F., & Biega, A. J. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3696457 · Cited by 117
Leibbrandt, A., & List, J. (2018) · doi:10.3386/w25035 · Cited by 43
Self-citation
Metadata
- Authors
- Leibbrandt, A., & List, J. A.
- Venue
- Management Science
- Published
- 2015-09
- Volume
- 61
- Issue
- 9
- Pages
- 2016-2024
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2265773967
- Cited by
- 328
- References
- 29
- FWCI
- 38.80
- 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: Do Women Avoid Salary Negotiations? Evidence from a Large-Scale Natural Field Experiment. https://app.cochat.ai/papers/10.1287/mnsc.2014.1994
- The paper
- Leibbrandt, A., & List, J. A. (2015). Do Women Avoid Salary Negotiations? Evidence from a Large-Scale Natural Field Experiment. Management Science. https://doi.org/10.1287/mnsc.2014.1994
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.