IDEAS home Printed from https://ideas.repec.org/r/pra/mprapa/92062.html

Explaining the labor share: automation vs labor market institutions

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Kostøl, Fredrik B. & Svarstad, Elin, 2023. "Trade Unions and the Process of Technological Change," Labour Economics, Elsevier, vol. 84(C).
  2. Minniti, Antonio & Prettner, Klaus & Venturini, Francesco, 2025. "AI innovation and the labor share in European regions," European Economic Review, Elsevier, vol. 177(C).
  3. Guimarães, Luís & Mazeda Gil, Pedro, 2022. "Looking ahead at the effects of automation in an economy with matching frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
  4. Abeliansky, Ana & Algur, Eda & Bloom, David E. & Prettner, Klaus, 2020. "The Future of Work: Challenges for Job Creation Due to Global Demographic Change and Automation," IZA Discussion Papers 12962, IZA Network @ LISER.
  5. Xiaomeng Zhang & Theodore Palivos & Xiangbo Liu, 2022. "Aging and automation in economies with search frictions," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(2), pages 621-642, April.
  6. Abeliansky, Ana Lucia & Prettner, Klaus, 2023. "Automation and population growth: Theory and cross-country evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 208(C), pages 345-358.
  7. Cui, Guanghui & Zhang, Yi & Ma, Jingwen & Yao, Wenyun, 2023. "Does environmental regulation affect the labor income share of manufacturing enterprises? Evidence from China," Economic Modelling, Elsevier, vol. 123(C).
  8. Alexander Guschanski & Özlem Onaran, 2025. "The Labour Share and Corporate Financialization: Evidence From Publicly Listed Firms," British Journal of Industrial Relations, London School of Economics, vol. 63(3), pages 375-393, September.
  9. Dou, Wei & Zhang, Shengling & Wu, Zihao & Ji, Ruibing & Hao, Yu, 2026. "Income distribution effect of energy marketization reform: Evidence from Chinese enterprises and regions," Energy Economics, Elsevier, vol. 153(C).
  10. Tiago Neves Sequeira & Susana Garrido & Marcelo Santos, 2021. "Robots are not always bad for employment and wages," International Economics, CEPII research center, issue 167, pages 108-119.
  11. Abeliansky, Ana Lucia & Prettner, Klaus, 2017. "Automation and demographic change," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168215, Verein für Socialpolitik / German Economic Association.
  12. Abeliansky, Ana Lucia & Prettner, Klaus, 2021. "Population growth and automation density: theory and cross-country evidence," Department of Economics Working Paper Series 315, WU Vienna University of Economics and Business.
  13. Li, Chao & Lao, Wenyu & Li, Xiang & Zhang, Yuhan, 2024. "Automated workforce, financial precarities and family consumption: The importance of demand-side policies under the background of automation applications," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 1287-1308.
  14. Wu, Haoyue & Yin, Yingkai, 2025. "Data trading platforms and total factor productivity: Insights from biased technical progress," Economic Analysis and Policy, Elsevier, vol. 88(C), pages 377-398.
  15. Bloom, David E. & Prettner, Klaus & Saadaoui, Jamel & Veruete, Mario, 2025. "Artificial intelligence and the skill premium," Finance Research Letters, Elsevier, vol. 81(C).
  16. Sun, Hongye & Gao, Gongjing, 2025. "The impact of intelligent automation on subjective well-being and job satisfaction: A comparison between standard and nonstandard employment," China Economic Review, Elsevier, vol. 94(PB).
  17. Wang, Linhui & Cao, Zhanglu & Dong, Zhiqing, 2023. "Are artificial intelligence dividends evenly distributed between profits and wages? Evidence from the private enterprise survey data in China," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 342-356.
  18. Jacobs, Arthur, 2023. "Capital-augmenting technical change in the context of untapped automation opportunities," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 155-166.
  19. Charalampidis, Nikolaos & Guillochon, Justine, 2025. "Searching for robots," Economic Modelling, Elsevier, vol. 152(C).
  20. Adnan Velic, 2023. "On Finance's Disparate Labor Share Dynamics: A Neoclassical Perspective," Trinity Economics Papers tep1523new, Trinity College Dublin, Department of Economics, revised Feb 2026.
  21. Brzozowski, Michał & Siwińska-Gorzelak, Joanna, 2024. "Did robots make wages less responsive to unemployment?," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
  22. Yuan, Sai & Zhou, Ran & Li, Mengna & Lv, Chengchao, 2023. "Investigating the influence of digital technology application on employee compensation," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
  23. Del Río, Fernando & Rebelo, Francisco, 2025. "OECD labour share trends: Factor efficiency vs. market distortions in a neoclassical framework," Economic Analysis and Policy, Elsevier, vol. 87(C), pages 2554-2591.
  24. Gasteiger, Emanuel & Prettner, Klaus, 2022. "Automation, Stagnation, And The Implications Of A Robot Tax," Macroeconomic Dynamics, Cambridge University Press, vol. 26(1), pages 218-249, January.
  25. Ana L. ABELIANSKY & Eda ALGUR & David E. BLOOM & Klaus PRETTNER, 2020. "The future of work: Meeting the global challenges of demographic change and automation," International Labour Review, International Labour Organization, vol. 159(3), pages 285-306, September.
  26. Hugo Hopenhayn & Julian Neira & Rish Singhania, 2022. "From Population Growth to Firm Demographics: Implications for Concentration, Entrepreneurship and the Labor Share," Econometrica, Econometric Society, vol. 90(4), pages 1879-1914, July.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.