nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2022‒10‒17
eleven papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. A Lasting Crisis Affects R&D Decisions of Smaller Firms: The Greek Experience By Ioannis Giotopoulos; Alexander S. Kritikos; Aggelos Tsakanikas
  2. China's Development Path: Government, Business, and Globalization in an Innovating Economy By Yin Li; William Lazonick
  3. Robots at work: recent evidence with new data By Derick Almeida; Tiago Miguel Guterres Neves Sequeira
  4. Radical technologies, recombinant novelty and productivity growth: a cliometric approach By Marianna Epicoco; Magali Jaoul-Grammare; Anne Plunket
  5. The Impact of Firm-level Covid Rescue Policies on Productivity Growth and Reallocation By Jozef Konings; Glenn Magerman; Dieter Van Esbroeck
  6. The emergence of a Global Innovation System: an inter-temporal analysis through a network of networks By Leonardo Costa Ribeiro; Jorge Nogueira de Paiva Britto; Eduardo da Motta e Albuquerque
  7. Looking Backward, Innovating Forward: A Theory of Competitive Cascades By Kevin Lim; Daniel Trefler; Miaojie Yu
  8. Does Host Country Intellectual Property Protection Matter for Technology-Intensive Import Flows? By Ridwan Ah Sheikh; Sunil Kanwar
  9. Characterising science-industry patent collaborations: knowledge base, impact and economic value By Ugo RIZZO; Valerio STERZI
  10. Let's Switch to the Cloud: Cloud Adaption and Its Effect on IT Investment and Productivity By Tomaso Duso; Alexander Schiersch
  11. Shaping the transition: Artificial intelligence and social dialogue By Clara Krämer; Sandrine Cazes

  1. By: Ioannis Giotopoulos; Alexander S. Kritikos; Aggelos Tsakanikas
    Abstract: We use the prolonged Greek crisis as a case study to understand how a lasting economic shock affects the innovation strategies of firms in economies with moderate innovation activities. Adopting the 3-stage CDM model, we explore the link between R&D, innovation, and productivity for different size groups of Greek manufacturing firms during the prolonged crisis. At the first stage, we find that the continuation of the crisis is harmful for the R&D engagement of smaller firms while it increased the willingness for R&D activities among the larger ones. At the second stage, among smaller firms the knowledge production remains unaffected by R&D investments, while among larger firms the R&D decision is positively correlated with the probability of producing innovation, albeit the relationship is weakened as the crisis continues. At the third stage, innovation output benefits only larger firms in terms of labor productivity, while the innovation-productivity nexus is insignificant for smaller firms during the lasting crisis.
    Keywords: Small firms, large firms, R&D, innovation, productivity, long-term crisis
    JEL: L25 L60 O31 O33
    Date: 2022
  2. By: Yin Li (Fudan University); William Lazonick (The Academic-Industry Research Network)
    Abstract: We employ the "social conditions of innovative enterprise" framework to analyze the key determinants of China's development path from the economic reforms of 1978 to the present. First, we focus on how government investments in human capabilities and physical infrastructure provided foundational support for the emergence of Chinese enterprises capable of technological learning. Second, we delve into the main modes by which Chinese firms engaged in technological learning from abroad -joint ventures with foreign multinationals, global value chains, and experienced high-tech returnees - that have contributed to industrial development in China. Third, we provide evidence on achievements in indigenous innovation - by which we mean improvements in national productive capabilities that build on learning from abroad and enable the innovating firms to engage in global competition - in the computer, automobile, communication - technology, and semiconductor - fabrication industries. Finally, we sketch out the implications of our approach for current debates on the role of innovation in China's development path as it continues to unfold.
    Keywords: China, investment, infrastructure, knowledge, indigenous innovation, globalization, development.
    JEL: D2 F2 F6 H1 H4 H5 H7 L1 L2 L5 L6 O1 O2 O3 O5 P1
    Date: 2022–08–11
  3. By: Derick Almeida (Ph.D. Student at Faculty of Economics, University of Coimbra); Tiago Miguel Guterres Neves Sequeira (University of Coimbra, Centre for Business and Economics Research, CeBER and Faculty of Economics)
    Abstract: We reassess the relationship between robotization and the growth in productivity in the light of new data and methods. We discover that the effect of robot density in the growth productivity substantially decreased in the post- 2008 crisis period. Moreover, in this more recent period, the less strong positive effect of robot density in the growth of productivity is mostly derived from negative effect of hours worked in productivity, showing that robots lost part of their capacity to increase productivity through value-added. By means of quantile regression, we also learn that the effect of robots on labor productivity is stronger for low productivity sectors and that in the most recent period, the effect of robotization in all sectors, felt significantly throughout the distribution, with special emphasis in the most productive sectors. This highlights one of the possible sources of the secular stagnation in the era of robotization and artificial intelligence technologies.
    Keywords: Robots, Robotization, Labor Productivity, Productivity Growth, Stagnation.
    JEL: E23 J23
    Date: 2022–07
  4. By: Marianna Epicoco (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Magali Jaoul-Grammare (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Anne Plunket (RITM - Réseaux Innovation Territoires et Mondialisation - Université Paris-Saclay)
    Abstract: Using inventions with a high degree of recombinant novelty as proxy for radical technologies, this work provides a long-run quantitative analysis of the relationship between radical technologies and productivity growth. The empirical analysis is based on a cliometric approach and relies on Granger's causality to test the sign and direction of causality between the flow of radical technologies and productivity levels, in the USA between 1920 and 2000. At the aggregate level, results show that radical technologies cause a temporary acceleration of productivity growth and explain a considerable part of productivity variations. At technology-field level, the analysis indicates that productivity growth is driven by a few technological fields, mainly concentrated in science based sectors and in the sectors of specialized suppliers of capital equipment. Finally, with respect to the controversial issue of the endogeneity of radical technologies, at the aggregate level we find no causal relationship running from productivity to radical technologies, suggesting that these are exogenous. However, at technology-field level, we find a few endogenous technologies. Most of these are "demand-driven" as their flow increases when productivity grows, but they have no impact on productivity. Only in one technological field, the flow of radical technologies increases when productivity decreases and, at the same time, has a positive impact on productivity. This latter case may explain why technological revolutions and the whole process of longrun economic development are partly endogenous.
    Keywords: Radical technologies,Recombinant novelty,Productivity growth,Cliometrics,Granger's causality,Technological revolutions,Long-run economic development.
    Date: 2022
  5. By: Jozef Konings (Nazarbayev University, Graduate School of Business, KU Leuven and CEPR); Glenn Magerman (ECARES, ULB and CEPR); Dieter Van Esbroeck (KU Leuven)
    Abstract: We analyze the impact of Covid-19 rescue policies on both firm-level and aggregate productivity growth and reallocation. Using administrative data on the universe of firms' subsidies in Flanders, we estimate the causal impact of these subsidies on firm-level outcomes. Firms that received subsidies saw a 7% increase in productivity, compared to firms that applied for, but did not obtain subsidies. Furthermore, the propensity to exit the market was 43% lower for treated firms. Aggregate productivity growth, a share-weighted sum of firms' productivity evolutions, amounted to 6% in 2020. While within-firm productivity growth was similar for both subsidized and non-subsidized firms, there is a reallocation of market shares from subsidized firms to non-subsidized firms. These results suggest that Covid rescue policies helped firms to sustain and preserve productivity, while not obstructing allocative efficiency gains to non-subsidized firms.
    Keywords: Productivity, productivity growth, aggregate productivity, allocative efficiency
    JEL: D22 D24 O4
    Date: 2022–06
  6. By: Leonardo Costa Ribeiro (CEDEPLAR/UFMG); Jorge Nogueira de Paiva Britto (UFF); Eduardo da Motta e Albuquerque (CEDEPLAR/UFMG)
    Abstract: This paper investigates a structural change: the emergence of a Global Innovation System (GIS). Focusing on international knowledge flows (IKFs) we organize the network in three layers according to the type of IKF that connects the institutions: scientific collaboration, patent citation or article citation in patents. We investigate how those three layers overlap and entangle, figuring out a network of networks. We found that each layer follows a free-scale network structure associated with a self-organized system and creates an intrinsic hierarchy. The subnetwork that connects the three layers is also a free-scale network. The intertemporal analysis shows that those properties persist from 2009 to 2017.Therefore, we identified a complex network structure that is very unlike being created by a random process. This structure shows hierarchy, association with self-organized systems, robustness, and specialization, which are the fundamental aspects necessary to define a system. In the context of this analysis, that is the Global Innovation System.
    Keywords: International knowledge flows; Innovation systems; Networks of networks
    JEL: O32 O34 O39
    Date: 2022–09
  7. By: Kevin Lim; Daniel Trefler; Miaojie Yu
    Abstract: Innovation depends on exporting and, in particular, on scale and competition in export markets. We develop a theory featuring (1) quality-segmented markets, (2) step-by-step innovation that moves firms forward along the quality ladder, and (3) escape-the-competition motives for innovation. We derive four predictions about the impact on innovation of scale and competition: a firm with a large and less-competitive quality segment ahead or forward of it will have strong incentives to innovate into this profitable segment, while a firm with a small and more-competitive quality segment behind it will also have strong incentives to innovate for fear of facing firms in this segment in the future. We take these predictions to Chinese firm-level data during a period of explosive export growth (2000-2006). Using information about scale and competition by quality segment in China's export markets, we confirm all four hypotheses. By implication, and unlike in standard CES models, the impact of trade on innovation depends critically on how it drives scale and competition in high- versus low-quality segments.
    JEL: F01 F12 F14 O3
    Date: 2022–09
  8. By: Ridwan Ah Sheikh (Department of Economics, Delhi School of Economics); Sunil Kanwar (Department of Economics, Delhi School of Economics)
    Abstract: Using disaggregated industry level data for 1976-2019, we find, unlike much of the received literature, that patent rights have a strong positive effect on developing country knowledge-intensive imports. Using the new gravity model of Anderson-van Wincoop, there is strong evidence of a market expansion effect across knowledge-intensive industries. The overall elasticity of knowledge-intensive imports w.r.t patent rights is 0.28, with considerable variation across industries, being 0.55 for electronics, 0.44 for rubber manufactures, and 0.32 for pharmaceuticals. This increase in imports appears to be (mainly) driven by quantity increases, not just price increases. Our results survive multiple robustness checks. Key Words: Imports, Intellectual property rights, Gravity model, Multilateral resistance JEL Codes: F13, F14, O34
    Date: 2022–09
  9. By: Ugo RIZZO; Valerio STERZI
    Abstract: In this article, we analyse the characteristics of science-industry patents with respect to non-collaborative industry patents and industry-industry collaborative patents. This analysis covers patents filed in the years 1978-2015 (and granted up to 2020) at the European Patent Office (EPO) in four large European countries (Germany, France, Italy and the UK) and in the US. We consider three dimensions to assess the characteristics of patents: the knowledge base, the technological impact, and the economic value. Science-industry collaborative patents are averagely more sophisticated and similar or higher impact than other industry patents. However, depending on the proxy chosen, they are of similar or lower economic value compared to non-collaborative industry patents and to industry-industry collaborative patents. When we control for the experience of private companies in collaborating with academic institutions, we observe that more experienced collaborations produce slightly less sophisticated and impactful patents, but with higher economic value. We discuss different explanations of these findings.
    Keywords: University patent, patent value, patent collaboration, Science-Industry
    JEL: O31 O34
    Date: 2022
  10. By: Tomaso Duso; Alexander Schiersch
    Abstract: The advent of cloud computing promises to improve the way firms utilize IT solutions. Firms are expected to replace large and inflexible fixed-cost investments in IT with more targeted variable spending in cloud solutions. In addition, cloud usage is expected to increase the productivity of firms, as it allows them to quickly customize the IT they require to their specific needs. We assess these assertions using data on a representative sample of firms provided by the German statistical offices for the years 2014 and 2016, which allows to observe who are the cloud users. Our analysis explicitly accounts for the self-selection into cloud adoption within an endogenous treatment regression framework. Broadband availability at the municipality level is used as an exogenous shifter for cloud usage. We show that, while cloud adoption does not impact IT investment in any sectors, it does significantly improve labor productivity for firms in manufacturing and in information and communication services.
    Keywords: Cloud computing, investment, productivity, IT, substitution, firm performance
    JEL: D24 D25 L60 L80 O14 O33
    Date: 2022
  11. By: Clara Krämer; Sandrine Cazes
    Abstract: Rapid advances in the development and adoption of artificial intelligence (AI) technologies provide new opportunities but also raise fears about disruptive labour market and workplace transitions. This working paper examines how social dialogue can shape the AI transition in beneficial ways for both workers and firms. It highlights that social dialogue can generally help foster inclusive labour markets and ease technological transitions, and presents new descriptive evidence together with ongoing initiatives from social partners showing that social dialogue has an important role to play in the AI transition as well. The paper also discusses how AI adoption may affect social dialogue itself, e.g. by adding new pressures on weakening labour relations systems and posing practical challenges to social partners, such as insufficient AI-related expertise and resources to respond to the AI transition. Based on these insights, the paper suggests a few measures for policy makers who would like to support social partners’ efforts in shaping the AI transition.
    JEL: J01 J08 J51 O3
    Date: 2022–10–03

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