nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2022‒10‒03
eleven papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Quantifying environmentally relevant and circular plastic innovation: Historical trends, current landscape and the role of policy By Damien Dussaux; Shardul Agrawala
  2. Anatomy of Green Specialisation: Evidence from EU Production Data, 1995-2015 By Bontadini, Filippo; Vona, Francesco
  3. Connecting to power: political connections, innovation, and firm dynamics By Ufuk Akcigit; Salomé Baslandze; Francesca Lotti
  4. Improving Patent Assignee-Firm Bridge with Web Search Results By Yuheng Ding; Karam Jo; Seula Kim
  5. Micro-data based insights on trends in business R&D performance and funding: Findings from the OECD microBeRD+ project By Silvia Appelt; Matej Bajgar; Chiara Criscuolo; Fernando Galindo-Rueda
  6. The Impact of Firm-level Covid Rescue Policies on Productivity Growth and Reallocation By Jozef Konings; Glenn Magerman; Dieter Van Esbroeck
  7. Trade Secret Protection and R&D Investment of Family Firms By Katrin Hussinger; Wunnam Basit Issah
  8. Rethinking regional economic resilience: Preconditions and processes shaping transformative resilience By Michaela Trippl; Sebastian Fastenrath; Arne Isaksen
  9. Working Paper No. 355: The artificial intelligence (AI) data access regime: what are the factors affecting the access and sharing of industrial AI data? By Long, Vicky; Bjuggren, Per-Olof
  10. Participation in Global Value Chains and M&A flows By Ciani, Andrea; Gregori, Wildmer Daniel
  11. Place-Based Productivity and Costs in Science By Jonathan Gruber; Simon Johnson; Enrico Moretti

  1. By: Damien Dussaux (OECD); Shardul Agrawala (OECD)
    Abstract: Innovation is key to reducing the environmental impacts of plastics. However, literature is generally lacking in the field of environmentally relevant plastics innovation. This paper develops an innovative conceptual framework to document and map environmentally relevant plastics innovation. Using this framework, it develops plastics innovation metrics using patents and trademarks to quantify trends over time, across countries, and to establish preliminary empirical links between policies and innovation outcomes.Plastic waste prevention and recycling innovation has increased slightly more rapidly than overall plastics innovation. In contrast, innovation in bioplastics have witnessed a significant slowdown in recent years. Another key finding of this analysis is that environmentally relevant plastics innovation is concentrated in OECD countries and China and that top inventor countries are not specialized in the same technologies. Finally, the patent analysis shows some empirical evidence that recycling regulations may have triggered innovative activity in plastic recycling.
    Keywords: Circular economy, Environmental Policy, Innovation, Plastics, Recycling, Waste
    JEL: O31 O38 Q53 Q55 Q58
    Date: 2022–09–21
    URL: http://d.repec.org/n?u=RePEc:oec:envaaa:199-en&r=
  2. By: Bontadini, Filippo; Vona, Francesco
    Abstract: We study green specialisation across EU countries and detailed 4-digit industrial sectors over the period of 1995-2015 by harmonizing product-level data (PRODCOM). We propose a new list of green goods that refines lists proposed by international organizations by excluding goods with double usage. Our analysis reveals important structural characteristics of green specialisation in the manufacturing sector. First, green production is highly concentrated, with 13 out of 119 4-digit industries, which are high-tech and account for nearly 95% of the total. Second, green and polluting productions do not occur in the same sectors, and countries specialise in either green or brown sectors. Third, our econometric analysis identifies three key drivers of green specialisation: (i) first-mover advantage and high persistence of green specialisation, (ii) complementarity with non-green capabilities and (iii) the degree of diversification of green capabilities. Importantly, once we control for these drivers, environmental policies are not anymore positively associated with green specialisation.
    Keywords: Production Economics, Resource /Energy Economics and Policy
    Date: 2022–06–17
    URL: http://d.repec.org/n?u=RePEc:ags:feemwp:324042&r=
  3. By: Ufuk Akcigit (University of Chicago); Salomé Baslandze (Federal Reserve Bank of Atlanta); Francesca Lotti (Bank of Italy)
    Abstract: How do political connections affect firm dynamics, innovation, and creative destruction? We extend a Schumpeterian growth model with political connections that help firms ease their bureaucratic and regulatory burden. The model highlights how political connections influence an economy's business dynamism and innovation, and generate a number of implications guiding our empirical analysis. We construct a new large-scale dataset, for the period 1993-2014, on the universe of firms, workers, and politicians, supplemented by corporate financial statements, patent and election data, so as to define connected firms as those employing local politicians. We identify a leadership paradox: market leaders are much more likely to be politically connected, but much less likely to innovate. Political connections relate to a higher rate of survival, as well as growth in employment and revenues, but not in productivity. This result was also confirmed using the regression discontinuity design. At the aggregate level, gains from political connections do not offset losses stemming from lower reallocation and growth.
    Keywords: firm dynamics, innovation, political connections, creative destruction, productivity
    JEL: O3 O4 D7
    Date: 2022–07
    URL: http://d.repec.org/n?u=RePEc:bdi:wptemi:td_1376_22&r=
  4. By: Yuheng Ding; Karam Jo; Seula Kim
    Abstract: This paper constructs a patent assignee-firm longitudinal bridge between U.S. patent assignees and firms using firm-level administrative data from the U.S. Census Bureau. We match granted patents applied between 1976 and 2016 to the U.S. firms recorded in the Longitudinal Business Database (LBD) in the Census Bureau. Building on existing algorithms in the literature, we first use the assignee name, address (state and city), and year information to link the two datasets. We then introduce a novel search-aided algorithm that significantly improves the matching results by 7% and 2.9% at the patent and the assignee level, respectively. Overall, we are able to match 88.2% and 80.1% of all U.S. patents and assignees respectively. We contribute to the existing literature by 1) improving the match rates and quality with the web search-aided algorithm, and 2) providing the longest and longitudinally consistent crosswalk between patent assignees and LBD firms.
    Keywords: Innovation, Patent, Patent-firm Concordance, Linked Administrative Data
    Date: 2022–08
    URL: http://d.repec.org/n?u=RePEc:cen:wpaper:22-31&r=
  5. By: Silvia Appelt; Matej Bajgar; Chiara Criscuolo; Fernando Galindo-Rueda
    Abstract: This report presents new insights on trends in business R&D performance and funding, drawing on the micro-aggregated R&D and tax relief statistics collected for 21 OECD countries as part of the OECD microBeRD project. Micro-aggregated statistics provide an important input for policy analysis, highlighting important variations in business R&D performance and funding across industries and different types of firms that are hard to uncover based on aggregate R&D and tax relief statistics. They shed light on country and industry specific trends in the concentration of R&D activity, business R&D dynamics, the structure of R&D performance among different types of firms and the way that they fund their R&D activities. Such evidence can be relevant in assessing the contribution of different types of firms (e.g. young firms, foreign-controlled affiliates) and individuals (e.g. female R&D staff, doctorate holders) to research and development in the business sector and designing business R&D support policies.
    Keywords: additionality, government support, impacts, research and development, tax incentives
    JEL: O38 H25 L25
    Date: 2022–09–16
    URL: http://d.repec.org/n?u=RePEc:oec:stiaaa:2022/04-en&r=
  6. By: Jozef Konings; Glenn Magerman; Dieter Van Esbroeck
    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
    Date: 2022–09
    URL: http://d.repec.org/n?u=RePEc:eca:wpaper:2013/349952&r=
  7. By: Katrin Hussinger (Université du Luxembourg); Wunnam Basit Issah (University of Leicester)
    Abstract: Family firms are known for their reluctance to invest in research and development. We show that strengthened trade secret protection is associated with higher R&D investment by family firms. More specifically, we show that the association between the strength of trade secret protection through the U.S. Uniform Trade Secrets Act and R&D investment is positively moderated by family control. Our results further show that the positive moderation of family control on the association between the strength of trade secret protection and R&D investment varies with the industry context, being stronger in high tech industries and weaker in discrete product industries.
    Keywords: Family firms; intellectual property protection; trade secret protection; UTSA; R&D investments; socioemotional wealth.
    Date: 2022
    URL: http://d.repec.org/n?u=RePEc:luc:wpaper:22-11&r=
  8. By: Michaela Trippl (University of Vienna); Sebastian Fastenrath (University of Vienna); Arne Isaksen (University of Agder)
    Abstract: The unpredictable impacts of slow-burn processes such as climate change and sudden shocks such as the current COVID-19 crisis have led to a renewed interest into regional economic resilience. Much of the literature focuses attention on how regional economies and industries could bounce back, that is, how they could return to their pre-shock conditions. Other scholars have proposed to construe resilience as bouncing forward to capture the mechanisms and processes that underpin positive adaptation and structural change in response to a crisis. In this article, we argue that both conceptualisations fail to consider shocks and crises as a window of opportunity for regional economies to transform to a radically different and more desirable trajectory. This paper brings a new perspective into play, that is, transformative resilience which places shifts towards more sustainable pathways centre stage. This understanding of regional economic resilience acknowledges that a crisis may bring about permanent structural change and it considers to what extent these transformations are to the benefit of society and the environment. This article seeks to identify in a conceptual way what factors and dynamics are vital for enhancing the transformative resilience of regions. To this end, we link recent insights from the debate on regional economic resilience to challenge-oriented regional innovation systems and elaborate on the role of pre-shock conditions and various core processes in building up regional transformative resilience.
    Keywords: transformative regional resilience, environmental and societal challenges, challenge-oriented regional innovation systems; green path development
    Date: 2022
    URL: http://d.repec.org/n?u=RePEc:aoe:wpaper:2202&r=
  9. By: Long, Vicky (The Ratio Institute); Bjuggren, Per-Olof (The Ratio Institute)
    Abstract: This paper decomposes the factors that govern the access and sharing of machine-generated industrial data in the artificial intelligence era. Through a mapping of the key technological, institutional, and firm-level factors that affect the choice of governance structures, this study provides a synthesised view of AI data-sharing and coordination mechanisms. The question to be asked here is whether the hitherto de facto control—bilateral contracts and technical solution-dominating industrial practices in data sharing—can handle the long-run exchange needs or not.
    Keywords: Artificial intelligence (AI); governance structure; intellectual property rights (IPRs); data trade; industrial data
    JEL: D23 K10 K24 L14 L86 O30
    Date: 2022–05–05
    URL: http://d.repec.org/n?u=RePEc:hhs:ratioi:0355&r=
  10. By: Ciani, Andrea (European Commission); Gregori, Wildmer Daniel (European Commission)
    Abstract: This study investigates to which extent firms operating in sectors more integrated into Global Value Chains (GVC) are more likely to be involved in cross-border Mergers and Acquisitions (M&A) flows. We focus on firms acquired in the EU27 during the period 2008-2020 employing a gravity model. Results show that cross-border investments are indeed associated with sectoral GVC participation, in particular the dependence on intermediate products supplied by other countries (i.e. backward GVC participation) of the target country-sector is positively correlated with M&A flows. This evidence is confirmed when the acquired firm operates in manufacturing or high-tech sectors, and when the investor originates from OECD countries. In addition, results show that companies from countries suppling inputs to other countries are more likely to pursue a cross-border acquisition.
    Keywords: Global Value Chains, Mergers and Acquisitions, Global Economy, Gravity model, EU firms
    JEL: F21 F23 G34
    Date: 2022–08
    URL: http://d.repec.org/n?u=RePEc:jrs:wpaper:202209&r=
  11. By: Jonathan Gruber; Simon Johnson; Enrico Moretti
    Abstract: Cities with a larger concentration of scientists have been shown to be more productive places for additional scientists to do Research and Development. At the same time, these urban areas tend to be associated with higher costs of doing research, in terms of both wages and land. While the literature on the benefits of agglomeration economies is extensive, it offers no direct evidence of how productivity gains from agglomeration compare with higher costs of production. This paper aims to shed light on the balance between local productivity and local costs in science. Using a novel dataset, we estimate place-based costs of carrying out R&D in each US metro area and assess how these place-based costs vary with the density of scientists in each area. We then compare these costs with estimates of the corresponding productivity benefits of more scientist density from Moretti (2021). Adding more scientists to a city increases both productivity and production costs, but the rise in productivity is larger than the rise in production costs. In particular, each 10% rise in the stock of scientists is associated with a 0.11% rise in costs and a 0.67% rise in productivity. This implies that firms moving from cities with a small agglomeration of scientists to cities with a large agglomeration of scientists experience productivity gains that are 6 times larger than the increase in production costs. This finding is consistent with the increased concentration of R&D activity observed over the past 30 years. However, while the productivity estimate has only modest non-linearities, the cost estimates suggest much larger non-linearities as the concentration of scientists increases. For the most concentrated R&D cities, the difference between productivity gains and cost increases is close to zero.
    JEL: H0 J0 R0
    Date: 2022–09
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:30416&r=

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