REAL Seminar
Friday, November 20, 2020
9-10 a.m. CST
Join Zoom Meeting by clicking here
Meeting ID: 997 1523 2314
Passcode: 923169
Alessandra Faggian
Professor, Gran Sasso Science Institute, Italy
alessandra.faggian@gssi.it
"Artificial Intelligence and the Geography of Eco-Innovation"
In this paper we investigate the extent to which Artificial Intelligence (AI) is harnessed by regions for the sake of their sustainable development. By considering the manifold impact that AI is having on innovation, we expect that the local endowment of AI knowledge can help regions eco-innovate and specialize in green technologies, and that its effect is affected by their experience in mastering such technologies and by their relatedness to their extant knowledge-base. Using patents by regional applicants as a proxy of the local knowledge-base, we integrate their OECD-based green classification with the identification of AI patents based on different approaches and look at the relationship between green revealed technological advantages and local AI for EU28 (NUTS3) regions over the period 1981-2013. Econometric results show that AI actually favors the green-tech specialization of regions, but only by conditioning the effect of other green-tech drivers. In particular, AI helps regions specialize in green technologies providing they have already done it in the past, while it even reduces this capacity in non-already green specialized ones.
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Stefan Borsky
Professor, University of Graz, Austria
stefan.borsky@uni-graz.at
"The Role of Global Supply Chains in the Transmission of Weather Induced Production Shocks"
In this paper we combine sectoral input-output linkages based on the production network of 172 countries and 12 sectors from 1990 to 2015 and information on extreme weather events to construct an index measuring the intensity of shocks in the supply chain for each sector and country. This index is then used in an econometric model to determine the impact of supply chain disruptions on a sector's export performance. Our results suggest that a one standard deviation increase in our supply chain shock measure reduces a sector's export value by around 11 percent. Finally, we project that, if no additional adaptation were to occur, climate change will additionally reduce a sector's export value by up to 16 percent with a considerable heterogeneity in strength of the effect between the countries and sectors. Knowledge on the role of input-output linkages in the propagation of extreme weather shocks is important to design more resilient supply chains in future.
