EconPapers    
Economics at your fingertips  
 

The direction of technical change in AI and the trajectory effects of government funding

Martina Iori, Arianna Martinelli and Andrea Mina

LEM Papers Series from Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy

Abstract: Government funding of innovation can have a significant impact not only on the rate of technical change, but also on its direction. In this paper, we examine the role that government grants and government departments played in the development of artificial intelligence (AI), an emergent general purpose technology with the potential to revolutionize many aspects of the economy and society. We analyze all AI patents filed at the US Patent and Trademark Office and develop network measures that capture each patent's influence on all possible sequences of follow-on innovation. By identifying the effect of patents on technological trajectories, we are able to account for the long-term cumulative impact of new knowledge that is not captured by standard patent citation measures. We show that patents funded by government grants, but above all patents filed by federal agencies and state departments, profoundly influenced the development of AI. These long-term effects were especially significant in early phases, and weakened over time as private incentives took over. These results are robust to alternative specifications and controlling for endogeneity.

Keywords: R&D; Technical change; Government subsidies; Technology policy; General purpose technology. (search for similar items in EconPapers)
Date: 2021-11-16
New Economics Papers: this item is included in nep-big, nep-ino and nep-tid
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.lem.sssup.it/WPLem/files/2021-41.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ssa:lemwps:2021/41

Access Statistics for this paper

More papers in LEM Papers Series from Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy Contact information at EDIRC.
Bibliographic data for series maintained by ( this e-mail address is bad, please contact ).

 
Page updated 2025-03-22
Handle: RePEc:ssa:lemwps:2021/41