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on Technology and Industrial Dynamics |
| By: | Alessandra Bonfiglioli; Rosario Crinò; Herald Fadinger; Gino Gancia |
| Abstract: | We use French data over the 1994-2013 period to study how imports of industrial robots affect firm-level outcomes. Guided by a simple model, we develop a novel empirical strategy to identify the causal effects of robot adoption. Our results suggest that, while demand shocks generate a positive correlation between robot imports and employment at the firm level, exogenous exposure to automation leads to job losses. We also find that robot exposure increases labor productivity and some evidence that it may raise the relative demand for high-skill professions. |
| Keywords: | Automation, Displacement, Firms, Robots |
| JEL: | J23 J24 O33 D22 |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:mib:wpaper:528&r=tid |
| By: | Flavio Calvino; Luca Fontanelli |
| Abstract: | In this work we characterise French firms using artificial intelligence (AI) and explore the link between AI use and productivity. We relevantly distinguish AI users that source AI from external providers (AI buyers) from those developing their own AI systems (AI developers). AI buyers tend to be larger than other firms, while AI developers are also younger. The share of firms using AI is highest in the ICT sector, which exhibits a particularly high share of developers. Complementary assets, including skills, digital capabilities and infrastructure, play a key role for AI use, with AI buyers and developers leveraging different types of human capital. Overall, AI users tend to be more productive, however this appears largely related to the self-selection of more productive and digital-intensive firms into AI use. This is not the case for AI developers, for which the positive link between AI use and productivity remains evident beyond selection, suggesting a positive effect of AI on their productivity. |
| Keywords: | Technology Diffusion; Artificial Intelligence; Digitalisation; Productivity. |
| Date: | 2023–10–13 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2023/35&r=tid |
| By: | Dario Guarascio; Jelena Reljic; Roman Stoellinger |
| Abstract: | This study provides evidence of the employment impact of AI exposure in European regions, addressing one of the many gaps in the emerging literature on AI's effects on employment in Europe. Building upon the occupation-based AI-exposure indicators proposed by Felten et al. (2018, 2019, 2021), which are mapped to the European occupational classification (ISCO), following Albanesi et al. (2023), we analyse the regional employment dynamics between 2011 and 2018. After controlling for a wide range of supply and demand factors, our findings indicate that, on average, AI exposure has a positive impact on regional employment. Put differently, European regions characterised by a relatively larger share of AI-exposed occupations display, all else being equal and once potential endogeneity concerns are mitigated, a more favourable employment tendency over the period 2011-2018. We also find evidence of a moderating effect of robot density on the AI-employment nexus, which however lacks a causal underpinning. |
| Keywords: | Artificial intelligence; industrial robots; labour; regional employment; occupations |
| JEL: | J21 J23 O33 R1 |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:sap:wpaper:wp243&r=tid |
| By: | Erik Brynjolfsson (Stanford University and NBER); Catherine Buffington (U.S. Census Bureau); Nathan Goldschlag (U.S. Census Bureau); J. Frank Li (Stanford University); Javier Miranda (Halle Institute for Economic Research (IWH), and Friedrich-Schiller University Jena); Robert Seamans (New York University) |
| Abstract: | We use data from the Annual Survey of Manufactures to study the characteristics and geography of investments in robots across U.S. manufacturing establishments. We find that robotics adoption and robot intensity (the number of robots per employee) is much more strongly related to establishment size than age. We find that establishments that report having robotics have higher capital expenditures, including higher information technology (IT) capital expenditures. Also, establishments are more likely to have robotics if other establishments in the same Core-Based Statistical Area (CBSA) and industry also report having robotics. The distribution of robots is highly skewed across establishments’ locations. Some locations, which we call Robot Hubs, have far more robots than one would expect even after accounting for industry and manufacturing employment. We characterize these Robot Hubs along several industry, demographic, and institutional dimensions. The presence of robot integrators and higher levels of union membership are positively correlated with being a Robot Hub. |
| Keywords: | robot, technology adoption, manufacturing, labor |
| Date: | 2023–10–05 |
| URL: | http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2023-013&r=tid |
| By: | Moid, Md Zubab Ibne (University of North Carolina at Greensboro, Department of Economics); Buaka, Emefa (University of North Carolina at Greensboro, Department of Economics); Link, Albert (University of North Carolina at Greensboro, Department of Economics) |
| Abstract: | We identify quantitatively, using cross-country data from the Global Innovation Index, a path through which R&D (research and development) operates to affect economic growth and development. The path we consider is one that relates to enhancing the knowledge economy. Specifically, we contribute to the literature through the quantification of the antecedents and consequences of newly created knowledge: R&D creation of new knowledge economic growth and development. And, we show statistically that the R&D creation of new knowledge relationship is enhanced when businesses collaborate with universities. Not only is this collaborative indirect relationship new to the knowledge creation literature, but also it is based on the estimation of a model specification that has not previously been considered. |
| Keywords: | Global Innovation Index; knowledge economy; R&D; business-university collaboration; |
| JEL: | O33 O47 O50 |
| Date: | 2023–10–18 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2023_008&r=tid |
| By: | OECD |
| Abstract: | This document reports on the final output of the OECD microBeRD+ project. Drawing on the outcomes of previous work, this study presents new evidence on the impact of business R&D support policies – tax incentives and direct forms of support – on business R&D investment (R&D input additionality) and the innovation and economic performance of firms (R&D output additionality). The report also provides an exploratory analysis of R&D spillovers. |
| JEL: | H25 O38 L25 |
| Date: | 2023–10–09 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaac:159-en&r=tid |
| By: | Cascaldi-Garcia, Danilo (Federal Reserve Board); Vukoti, Marija (University of Warwick); Zubairy, Sarah (Texas A&M University and NBER) |
| Abstract: | When is receiving positive news regarding future technological advancements most impactful on the economy: during recessions or economic booms? A recession might represent an opportune time for investing in relatively cheaper, productivityenhancing activities. However, tighter financial constraints during recessions might hinder the ability to secure funds for these activities. We explore this dichotomy by exploiting patent-based innovation shocks, which are constructed using changes in stock market valuations of firms that obtain patent grants. We find that aggregate patent-based innovation shocks have a greater impact on the economy during recessions, leading to a more significant increase in private investment. Additionally, our exploration of firm-level data uncovers supporting evidence that firms tend to boost their capital investment and R&D expenditures in response to these innovation shocks, particularly during recessions. The financial constraints of firms play a crucial role, with capital investments by firms with low default risk driving the larger impact observed during recessions. |
| Keywords: | Innovation shocks ; Patent-Based Innovation Index ; Financial Frictions ; Firms heterogeneity ; State dependency |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:wrk:warwec:1475&r=tid |
| By: | Daisuke Matsuzaki; Yoshiyasu Ono |
| Abstract: | When confronting economic stagnation, innovation (product innovation in particular) is often cited as an effective stimulus because it is assumed to encourage household consumption and lead to higher demand. Using a secular stagnation model with wealth preference, we examine the effects of product innovation on employment and consumption. This study examines three types of product innovation, including quantity-augmenting-like innovation, addictive innovation, and variety expansion. The first works as if a larger quantity were consumed although the actual quantity remains the same, the second reduces the elasticity of the marginal utility of consumption, and the third increases the variety of consumption commodities. We find that the first and third reduce both consumption and employment, whereas the second expands them. It suggests that policy makers should carefully choose the type of product innovation to promote as an economic stimulus: addictive innovation stimulates business activity whereas quantity-augmenting-like innovation and variety expansion worsen stagnation. |
| Date: | 2023–03 |
| URL: | http://d.repec.org/n?u=RePEc:dpr:wpaper:1204rr&r=tid |
| By: | Nilsson, Magnus (CIRCLE, Lund University); Schubert, Torben (CIRCLE, Lund University); Miörner, Johan (CIRCLE, Lund University) |
| Abstract: | This paper analyses the impact of regional anchors on local firms in Swedish regions. Departing from previous idiographic research, we adopt a nomothetic research design relying on a stepwise expert-informed supervised machine learning approach to identify the population of anchor firms in the Swedish economy between 2007 and 2019. We find support for positive anchor effects on the productivity of other firms in the region. These effects are moderated by regional and anchor conditions. We find that the effects are greater when there are multiple anchors within the same industry and that the effects are larger in economically weaker regions. |
| Keywords: | anchor-tenant; productivity; machine learning; anchor firms; Sweden |
| JEL: | D24 O30 R11 R12 |
| Date: | 2023–10–10 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:lucirc:2023_008&r=tid |
| By: | Fernando Alexandre (NIPE/Center for Research in Economics and Management, University of Minho, Portugal); Diogo Ferreira (NIPE/Center for Research in Economics and Management, University of Minho, Portugal); Sandro Mendonça (Business Research Unit (BRU-IUL), University Institute of Lisbon; Research Unit on Complexity and Economics (UECE), Research in Economics and Mathematics (REM), Lisbon School of Economics & Management (ISEG), University of Lisbon; Science Policy Research Unit (SPRU), University of Sussex.); Miguel Portela (NIPE/Center for Research in Economics and Management, University of Minho, Portugal; IZA, Bonn) |
| Abstract: | This paper evaluates the effectiveness of R&D subsidies, provided by the European Regional Development Funds, on firms’ productivity. Using detailed longitudinal firm-level data covering the period 2007-2019, we employ state of the art differences-in-differences estimators to evaluate the impacts of R&D grants. Positive causal effects on gross value added and labour productivity are discernible for micro- and small-sized firms participating in co-promotion but not in individual projects. However, these effects seem to be elusive. No evidence of a positive effect of these grants on firm performance for medium- and large-sized firms or for individual R&D projects is found. This investigation contributes to a more comprehensive understanding of the relative effectiveness of productivity enhancement programs. |
| Keywords: | R&D grants; productivity; European funds; co-promotion |
| JEL: | D22 H25 L25 L52 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:nip:nipewp:08/2023&r=tid |
| By: | Henrekson, Magnus (Research Institute of Industrial Economics); Stenkula, Mikael (IFN - Research Institute of Industrial Economics) |
| Abstract: | Mission-oriented innovation policies are becoming increasingly popular among policymakers and scholars. We maintain that these policies are based on an overly mechanistic view of innovation and economic growth, suggesting that a more bottom-up approach is called for. By invoking an entrepreneurial ecosystem perspective, we point out that innovative entrepreneurship requires many other actors—besides the entrepreneur—whose skills and abilities are necessary to realize an entrepreneurial project. When mission-oriented policies play a large role in the economy, connections between actors in the ecosystem risk becoming distorted. A functioning and well-balanced entrepreneurial ecosystem requires instead an institutional framework that levels the playing field for potential entrepreneurs and encourages productive entrepreneurship. To promote this kind of system, we discuss in more detail eight key areas where appropriate horizontal or bottom-up policy measures can foster innovation and, in the end, the welfare-enhancing productive entrepreneurship policymakers and scholars strive for. |
| Keywords: | collaborative innovation bloc, entrepreneurial ecosystem, entrepreneurship policy, institutions, public choice |
| JEL: | H50 L26 O31 P16 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16487&r=tid |
| By: | Ege Erdil; Tamay Besiroglu |
| Abstract: | We examine whether substantial AI automation could accelerate global economic growth by about an order of magnitude, akin to the economic growth effects of the Industrial Revolution. We identify three primary drivers for such growth: 1) the scalability of an AI ``labor force" restoring a regime of increasing returns to scale, 2) the rapid expansion of an AI labor force, and 3) a massive increase in output from rapid automation occurring over a brief period of time. Against this backdrop, we evaluate nine counterarguments, including regulatory hurdles, production bottlenecks, alignment issues, and the pace of automation. We tentatively assess these arguments, finding most are unlikely deciders. We conclude that explosive growth seems plausible with AI capable of broadly substituting for human labor, but high confidence in this claim seems currently unwarranted. Key questions remain about the intensity of regulatory responses to AI, physical bottlenecks in production, the economic value of superhuman abilities, and the rate at which AI automation could occur. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2309.11690&r=tid |
| By: | Giuntella, Osea (University of Pittsburgh); König, Johannes (DIW Berlin); Stella, Luca (Free University of Berlin) |
| Abstract: | This study explores the relationship between artificial intelligence (AI) and workers' well-being and mental health using longitudinal survey data from Germany (2000-2020). We construct a measure of individual exposure to AI technology based on the occupation in which workers in our sample were first employed and explore an event study design and a difference-in-differences approach to compare AI-exposed and non-exposed workers. Before AI became widely available, there is no evidence of differential pre-trends in workers' well-being and concerns about their economic futures. Since 2015, however, with the increasing adoption of AI in firms across Germany, we find that AI-exposed workers have become less satisfied with their life and job and more concerned about job security and their personal economic situation. However, we find no evidence of a significant impact of AI on workers' mental health, anxiety, or depression. |
| Keywords: | artificial intelligence, future of work, well-being, mental health |
| JEL: | I10 J28 O30 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16485&r=tid |