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Data and codes accompanying the paper: Parteka A., Kordalska A. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data". Technovation, Volume 125, July 2023, 102764
Description
The folder contains the data and codes used in the analysis described in the paper: Parteka A., Kordalska A. (2023) Artificial intelligence and productivity: global evidence from AI patent and bibliometric data. Technovation, Volume 125, July 2023, 102764
Dataset file
REPLICATION PACKAGE.zip
468.9 kB,
S3 ETag
1f5af2c93168371d64ff18c0ae4c89ed-1,
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https://github.com/antespi/s3md5
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.Example script for calculation:
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File details
- License:
-
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CC BY-NC-NDNon-commercial - No Derivative Works - Software:
- stata
Details
- Year of publication:
- 2023
- Verification date:
- 2023-06-01
- Dataset language:
- English
- Fields of science:
-
- economics and finance (Social studies)
- DOI:
- DOI ID 10.34808/rjk6-ry03 open in new tab
- Funding:
- Verified by:
- Gdańsk University of Technology
Keywords
- Technological innovation
- Productivity paradox
- Productivity growth
- Artificial intelligence
- patent data
References
- publication Artificial intelligence and productivity: global evidence from AI patent and bibliometric data .
- dataset Data accompanying the paper: "Productivity effects of trade in natural resources – comparison with mechanisms of technological specialization" (Zarach and Parteka, The World Economy, 2023)
- dataset Data accompanying the paper: Zarach and Parteka (2023), Export diversification and dependence on natural resources , Economic Modelling (Elsevier), 126 (2023) 106436.
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