Analysing gender pay disparities and structural barriers among software developers: a cross-country study

Arjun Prakash & Inder Sekhar Yadav

Journal for Labour Market Research2025https://doi.org/10.1186/s12651-025-00407-zarticle
AJG 1
Weight
0.50

What the paper says

This study analyses gender disparity in a highly skilled labour force within the modern knowledge-based economy. It explores the global gender pay disparity among software developers, examining structural barriers like the “glass ceiling” and “sticky floor” effects across different economic and geographical regions. Using quantile regression and Oaxaca-Blinder decomposition, the research analyses countries based on the World Bank classification to understand variations. The study reveals a moderate gender pay gap of 8.8% in High-Income countries, in contrast to 36.6% in lower-middle-income countries and a pronounced 47.9% in South Asia. Further, the study establishes the presence of a glass ceiling phenomenon among high-income and upper-middle-income countries in contrast to the sticky floor effect in lower-middle-income countries. Moreover, the study identifies that the unexplained component is higher in Non-High-Income countries than in High-Income countries. The study emphasises the need for Lower-Middle-Income regions, especially in South Asia, to adopt strategies from High-Income countries to create a more equitable workplace.

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https://doi.org/https://doi.org/10.1186/s12651-025-00407-z

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@article{arjun2025,
  title        = {{Analysing gender pay disparities and structural barriers among software developers: a cross-country study}},
  author       = {Arjun Prakash & Inder Sekhar Yadav},
  journal      = {Journal for Labour Market Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1186/s12651-025-00407-z},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.