Innovation without borders? The geography of technological diffusion

Ursel Baumann, Ester Faia, Annalisa Ferrando, Judit Rariga, Zoe Cullen and Ricardo Perez-Truglia

No 3246, Working Paper Series from European Central Bank

Abstract: How well does innovation diffuse across geographic boundaries? To shed light on this question, we present a large-scale field experiment involving 3,300 firms across twelve European Union countries. We elicit firms’ perceptions of the share of similar firms in their own country that had invested in artificial intelligence (AI), as well as the corresponding share among similar firms in Germany, France, and Italy. We randomly provide half of the sample with accurate information about both domestic and foreign AI investment. We show that firms substantially underestimate competitors’ current AI investment, both domestically and abroad, and that they update their expectations about competitors’ future AI investment in response to the information treatment. The treatment also causes a statistically significant increase in firms’ own expected AI investment rate. We find strong strategic complementarities within borders: a 1 pp increase in the expected share of domestic peers investing in AI raises a firm’s own expected AI investment rate by 0.570 pp. These complementarities are absent across borders: the effect of an increase in the expected share of foreign peers investing in AI on a firm’s own expected AI investment rate is statistically insignificant. Overall, our evidence shows that innovation diffusion and strategic complementarities in AI investment are much stronger domestically than internationally. JEL Classification: O33, D22, C93, L21

Keywords: artificial intelligence; field experiment; innovation diffusion; survey data (search for similar items in EconPapers)
Date: 2026-06
Note: 345263
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