Determining the gender wage gap through causal inference and machine learning models: evidence from Chile-Reference-Cited by-同舟云学术

Determining the gender wage gap through causal inference and machine learning models: evidence from Chile

Published:2023-02-09 Issue:13 Volume:35 Page:9841-9863
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Kristjanpoller Werner^ORCID,Michell Kevin,Olson Josephine E.

Funder

Agencia Nacional de Investigación y Desarrollo

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-023-08221-9.pdf

Reference52 articles.

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2. Pearl J (2009) Causality. Cambridge University Press, Cambridge

3. Shapley LS (1953) A value for n-person games. Contributions Theor Games 2(28):307–317

4. Alatrista-Salas H, Esposito B, Nunez-del Prado M, Valdivieso M (2017) “Measuring the gender discrimination: A machine learning approach,” in 2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI), pp. 1–6, IEEE

5. Bach P, Chernozhukov V, Spindler M (2018) “Closing the US gender wage gap requires understanding its heterogeneity,” http://arxiv.org/abs/1812.04345

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