This paper provides the first comprehensive, cross-country evidence on the wage returns to digital skills using over 67 million job postings from 29 countries between 2021 and 2024. We develop a harmonized digital skills taxonomy and examine returns across extensive (any digital skill required), intensive (number of digital skills), and qualitative (type of digital skill) margins. Digital skills command substantial wage premiums globally, with particularly pronounced returns in low-and middle-income countries (LMICs) where such competencies remain scarce. Requiring at least one digital skill raises advertised wages by 1.6% on average, with returns of 1.3% in high-income countries (HICs) and 7.5% in LMICs. Each additional digital skill increases wages by 0.5% in HICs and 2.6% in LMICs, while intermediate and advanced skills yield even higher premiums of 0.8% in HICs and 3% in LMICs. Each traditional AI skills offer returns of 2.9% across all countries. Most remarkably, generative AI (GenAI) skills demonstrate the highest premiums: GenAI development skills command 7-9% wage increases in technical occupations, while GenAI literacy skills yield sizable premiums of 25-36% in non-technical professional roles, reflecting both their productivity potential and current scarcity. Returns are consistently higher in digitally intensive industries and occupations, and are amplified by workers' education and experience, suggesting strong complementarities between digital competencies and traditional human capital. These findings highlight the critical importance of digital skills for individual earnings and economic development, particularly in LMICs.
| Repository name | URI |
|---|---|
| Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
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| Author | Affiliation | |
|---|---|---|
| Yan Liu | World Bank | yanliu@worldbank.org |
| Antonio Martins Neto | World Bank | asmartins@worldbank.org |
| Saloni Khurana | World Bank | skhurana@worldbank.org |
| Juan Manuel Porras | World Bank | jporraslopez@worldbank.org |
2026-01-27
| Location | Code |
|---|---|
| World | WLD |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
| Name | URI |
|---|---|
| Modified BSD3 | https://opensource.org/license/bsd-3-clause/ |
| Name | Affiliation | |
|---|---|---|
| Yan Liu | World Bank | yanliu@worldbank.org |
| Reproducibility WBG | World Bank | reproducibility@worldbank.org |
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Reproducibility WBG | DECDI | World Bank - Development Impact Department | Verification and preparation of metadata |
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