Publication
Abstract
As demand for AI hardware increases, semiconductor industry policies, through subsidies, tax credits, and targeted financing, are expanding, leading to uneven distribution of policy support documents and strategic frameworks, as well as long implementation delays. This paper proposes a replicable measurement process to identify semiconductor-related interventions in global trade alerts through iterative validation. Each indicator is categorized according to value chain objectives and policy tools, providing a dataset and evaluation framework for semiconductor research.
Keywords
Semiconductor Industrial Policy , AI Hardware , Text Mining , Subsidy Quantification , International Spillovers .
Metadata
Disciplines: Natural Language Processing
Cite This Article
APA Style
Ye, K. (2026). Industrial policy for semiconductors in the ai hardware era: text based measurement and cross country evidence. Journal of Computer Technology and Applied Mathematics, 3(1), 45-54. https://doi.org/10.70393/6a6374616d.333730
Acknowledgments
The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.
FUNDING
INSTITUTIONAL REVIEW BOARD STATEMENT
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
INFORMED CONSENT STATEMENT
CONFLICT OF INTEREST
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
AUTHOR CONTRIBUTIONS
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