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Productivity, technology and intangible assets

Matilde Mas et al.

SERIEs: Journal of the Spanish Economic Association2025https://doi.org/10.1007/s13209-025-00310-3article
AJG 1ABDC B
Weight
0.44

What the paper says

Abstract This paper applies growth accounting methodology to analyse the evolution of labour productivity and total factor productivity (TFP) in Spain and a set of selected countries from the perspective of the growth potential that digitalisation offers. The role of information and communication technologies (ICTs) is viewed from two complementary perspectives. The first considers the role played by ICT assets, as well as R&D and other intangible assets not included in national accounts. The second examines the sectoral composition of production distinguishing between digital producing industries (DP), the most digital intensive using industries (MDIU) and the least digital intensive using industries (LDIU). We find that the notable delay in productivity in Spain compared to other countries is mainly due to: (1) low levels of investment in both ICT and intangible assets, which translates into lower productivity in almost all sectors; and (2) its productive specialisation biased towards the most traditional sectors classified as LDIU. The paper concludes by looking at the future of Spanish productivity in examining the potential role that AI could play in strengthening productivity growth.

3 citations

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https://doi.org/https://doi.org/10.1007/s13209-025-00310-3

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@article{matilde2025,
  title        = {{Productivity, technology and intangible assets}},
  author       = {Matilde Mas et al.},
  journal      = {SERIEs: Journal of the Spanish Economic Association},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s13209-025-00310-3},
}

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Productivity, technology and intangible assets

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Evidence weight

0.44

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

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
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.