nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2021‒11‒08
twelve papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Do patents really foster innovation in the pharmaceutical sector? Results from an evolutionary, agent-based model By Giovanni Dosi; Elisa Palagi; Andrea Roventini; Emanuele Russo
  2. Distant but close in sight. Firm-level evidence on French-German productivity gaps in manufacturing By Thomas Grebel; Mauro Napoletano; Lionel Nesta
  3. Financing Energy Innovation: Internal Finance and the Direction of Technical Change By Joëlle Noailly, Roger Smeets
  4. For Whom the Bell Tolls: The Firm-Level Effects of Automation on Wage and Gender Inequality By Giacomo Domini; Marco Grazzi; Daniele Moschella; Tania Treibich
  5. Productivity Convergence in Manufacturing: A Hierarchical Panel Data Approach By Guohua Feng; Jiti Gao; Bin Peng
  6. From automation to databased business models - Digitalization and its links to innovation in small and medium-sized enterprises By Thomä, Jörg; Bischoff, Thore Sören
  7. Towards the factory 4.0? Convergence and divergence of lean models in Italian automotive plants By Angelo Moro; Maria Enrica Virgillito
  8. Plugging into Global Value Chains of the Software Industry: The Experiences of India By Shaopeng Huang; Jai Asundi; Yuqing Xing
  9. Specialized Investments and Firms' Boundaries: Evidence from Textual Analysis of Patents By Bena, Jan; Erel, Isil; Wang, Daisy; Weisbach, Michael S.
  10. AI and Jobs: Evidence from Online Vacancies By Daron Acemoglu; David Autor; Jonathon Hazell; Pascual Restrepo
  11. The 2020 EU Industrial R&D Investment Scoreboard By Nicola Grassano; Hector Hernandez; Alexander Tuebke; Sara Amoroso; Mafini Dosso; Aliki Georgakaki; Francesco Pasimeni
  12. Class Struggle in a Schumpeterian Economy By Chu, Angus; Kou, Zonglai; Wang, Xilin

  1. By: Giovanni Dosi; Elisa Palagi; Andrea Roventini; Emanuele Russo
    Abstract: The role of the patent system in the pharmaceutical sector is highly debated also due to its strong public health implications. In this paper we develop an evolutionary, agent-based model of the pharmaceutical industry to explore the impact of different configurations of the patent system upon innovation and competition. The model is able to replicate the main stylized facts of the drug industry as emergent properties. We perform policy experiments to assess the impact of different IPR regimes changing the breadth and length of patents. Results suggest that enlarging the extent and duration of patents yields adverse effects in terms of innovation outcomes, as well as of market competition and consumer welfare. Such general conclusions hold even if one takes into account the possible positive effects on R&D intensity and information disclosure triggered by patents.
    Keywords: Innovation; Intellectual property rights; Market power; Pharmaceutical sector; Agent-based models.
    Date: 2021–10–28
  2. By: Thomas Grebel; Mauro Napoletano (OFCE - Observatoire français des conjonctures économiques - Sciences Po - Sciences Po); Lionel Nesta (OFCE - Observatoire français des conjonctures économiques - Sciences Po - Sciences Po)
    Abstract: We study the productivity level distributions of manufacturing firms in France and Germany, and how these distributions evolved across the Great Recession. We show the presence of a systematic productivity advantage of German firms over French ones in the decade 2003-2013, but the gap has narrowed down after the Great Recession. Convergence is explained by the better growth performance of French firms in the post-recession period, especially of those located in the top percentiles of the productivity distribution. We also highlight the role of sectoral growth, firm size and export intensity in explaining the above convergence. In contrast, the contribution of allocative efficiency was small.
    Keywords: international productivity gaps,productivity distributions,firm level comparisons
    Date: 2021
  3. By: Joëlle Noailly, Roger Smeets
    Abstract: Achieving the goals of the Paris Agreement and of climate neutrality by 2050 in the European Union will require mobilizing financial investments towards clean energy innovation. This study examines the role of internal finance (cash flows and cash holdings) and financing constraints for innovation in energy technologies. We construct a dataset for 1,300 European firms combining balance-sheet information and patenting activities in renewable (REN) and fossil-fuel (FF) technologies and estimate the sensitivity of patenting activities to firm’s internal finance. We use count estimation techniques and control for a large set of firm-specific characteristics and market developments in REN and FF technologies. We find that patenting activities of firms specialized in REN innovation are significantly more sensitive to a shock in cash flows than firms specializing in FF innovation. Hence, our results emphasize that innovative firms in clean energy may be particularly vulnerable to financing constraints. We discuss the implications of these results for energy transition policies aiming to redirect finance towards clean energy R&D.
    Date: 2021–11–02
  4. By: Giacomo Domini (Erasmus University Rotterdam); Marco Grazzi (Universita' Cattolica del Sacro Cuore); Daniele Moschella (Scuola Superiore Sant'Anna); Tania Treibich (Maastricht University)
    Abstract: This paper investigates the impact of investment in automation- and AI- related goods on within-firm wage inequality in the French economy during the period 2002-2017. We document that most of wage inequality in France is accounted for by differences among workers belonging to the same firm, rather than by differences between sectors, firms, and occupations. Using an event-study approach on a sample of firms importing automation and AI-related goods, we find that spike events related to the adoption of automation- or AI-related capital goods are not followed by an increase in within-firm wage nor in gender inequality. Instead, wages increase by 1% three years after the events at different percentiles of the distribution. Our findings are not linked to a rent-sharing behavior of firms obtaining productivity gains from automation or AI adoption. Instead, if the wage gains do not differ across workers along the wage distribution, worker heterogeneity is still present. Indeed, aligned with the framework in Abowd et al.(1999b), most of the overall wage increase is due to the hiring of new employees. This adds to previous findings showing picture of a `labor friendly' effect of the latest wave of new technologies within adopting firms.
    Keywords: Automation, AI, wage inequality, gender pay gap
    Date: 2021–10
  5. By: Guohua Feng; Jiti Gao; Bin Peng
    Abstract: Despite its paramount importance in the empirical growth literature, productivity convergence analysis has three problems that have yet to be resolved: (1) little attempt has been made to explore the hierarchical structure of industry-level datasets; (2) industry-level technology heterogeneity has largely been ignored; and (3) cross-sectional dependence has rarely been allowed for. This paper aims to address these three problems within a hierarchical panel data framework. We propose an estimation procedure and then derive the corresponding asymptotic theory. Finally, we apply the framework to a dataset of 23 manufacturing industries from a wide range of countries over the period 1963-2018. Our results show that both the manufacturing industry as a whole and individual manufacturing industries at the ISIC two-digit level exhibit strong conditional convergence in labour productivity, but not unconditional convergence. In addition, our results show that both global and industry-specific shocks are important in explaining the convergence behaviours of the manufacturing industries.
    Keywords: growth regressions, convergence in manufacturing, cross-sectional dependence, hierarchical model, asymptotic theory
    JEL: L60 O10 C23
    Date: 2021
  6. By: Thomä, Jörg; Bischoff, Thore Sören
    Abstract: Digitalization is one of the main trends affecting firm-level innovation today. In this context, a better understanding of the multidimensional relationship between digital technologies, competences and firm-level innovation is necessary. For this purpose, this paper examines the role of digital transformation in the context of innovation activities of small and medium-sized enterprises (SMEs). Based on a systematic review of the fourth edition of the Oslo Manual and a subsequent qualitative content analysis (QCA) of interview data on innovating German SMEs, a category system is derived covering different facets of the digitalization-innovation link along seven main categories and 32 sub-categories. This category system is employed to analyze the interview data, with several findings pointing to the heterogeneity of innovating SMEs in terms of digitalization. It emerges that there tend to be two ideal types of "digitalizers" among innovating SMEs. On the one hand, process innovators using digital technologies and practices to generate efficiency and automation benefits, whereby they must build up basic digital competences within the firm to achieve this aim. On the other hand, product innovators with advanced competences in digitalizing their goods and services that have often already gained experiences in adopting a digital business model. The paper concludes with implications for innovation measurement, policy and further research.
    Keywords: Digitalization,Digital innovation,Innovation measurement,Qualitative content analysis,SMEs
    JEL: D22 O31 O32 O33
    Date: 2021
  7. By: Angelo Moro; Maria Enrica Virgillito
    Abstract: This paper studies the interplay in terms of techno-organisational change between the adoption of I4.0 technologies and lean production systems. Leveraging on the results of two field-work analyses conducted under a collaboration with the Sabattini Foundation and the metal workers trade union FIOM in the period 2016-2018, we compare an ensemble of factories producing both high-end/highly customised and low-end products. Emerging patterns of convergence and divergence in the techno-organisational configurations of these factories confirm that this wave of technological innovation is far from leading to total automation or the digital revolution. On the contrary, it appears to be integrated into the historical trend of 'leanification' of production processes in the automotive sector, despite the organisational variety shaped by the actual implementation of this production model.
    Keywords: Industry 4.0; Lean production; Automotive; Work organisation; Technological innovation; Organisational innovation.
    Date: 2021–10–28
  8. By: Shaopeng Huang (Research Institute for Global Value Chains, University of International Business and Economics, Beijing, China); Jai Asundi (Center for Study of Science, Technology and Policy (CSTEP), Bengaluru, India); Yuqing Xing (National Graduate Institute for Policy Studies, Tokyo, Japan)
    Abstract: The rise of the software service industry has been the most impressive achievements of the Indian economy in the last few decades. The success story of Indian software service industry is essentially a story of plugging into the GVC by taking up part of the mostly labour-intensive, low value-added tasks outsourced /offshored by lead firms from the developed country. With a view to expand our understanding of GVCs beyond manufacturing, we analyse in this paper the software services industry in India in the context of GVCs. By examining the organization of software value chains, the endowment profile and sources of comparative advantage of India, the relations between foreign (lead) firms and indigenous firm, and the role of Indian governments, this paper try to pin down India’s particular position in the global value chains and its upgrading status, and to demonstrate the structural barriers and future challenges if Indian firms are to upgrade further their positon in the GVC.
    Keywords: GVCs, software; Indian software industry, upgrading
    Date: 2021–10
  9. By: Bena, Jan (University of British Columbia); Erel, Isil (Ohio State University and European Corporate Governance Institute); Wang, Daisy (Ohio State University); Weisbach, Michael S. (Ohio State University and European Corporate Governance Institute)
    Abstract: Inducing firms to make specialized investments through bilateral contracts can be challenging because of potential holdup problems. Such contracting difficulties have long been argued to be an important reason for acquisitions. To evaluate the extent to which this motivation leads to mergers, we perform a textual analysis of the patents filed by the same lead inventors of the target firms before and after the mergers. We find that patents of inventors from target firms become 28.9% to 46.8% more specific to those of acquirers’ inventors following completed mergers, benchmarked against patents filed by targets and a group of counterfactual acquirers. This pattern is stronger for vertical mergers that are likely to require specialized investments. There is no change in the specificity of patents for mergers that are announced but not consummated. Overall, we provide empirical evidence that contracting issues in motivating specialized investment can be a motive for acquisitions.
    JEL: G34 L14 L22
    Date: 2021–08
  10. By: Daron Acemoglu (MIT); David Autor (MIT); Jonathon Hazell (Princeton University and LSE); Pascual Restrepo (Boston University)
    Abstract: We study the impact of AI on labor markets, using establishment level data on vacancies with detailed occupational information comprising the near-universe of online vacancies in the US from 2010 onwards. We classify establishments as "AI exposed" when their workers engage in tasks that are compatible with current AI capabilities.We document rapid growth in AI related vacancies over 2010-2018 that is not limited to the Professional and Business Services and Information Technology sectors and is significantly greater in AI-exposed establishments. AI-exposed establishments are differentially eliminating vacancy postings that list a range of previously-posted skills while simultaneously posting skill requirements that were not previously listed.Establishment-level estimates suggest that AI-exposed establishments are reducing hiring in non-AI positions even as they expand AI hiring. However, we find no discernible impact of AI exposure on employment or wages at the occupation or industry level,implying that AI is currently substituting for humans in a subset of tasks but it is not yet having detectable aggregate labor market consequences.
    Keywords: artificial intelligence, displacement, labor, jobs, tasks, technology, wages
    JEL: J23 O33
    Date: 2020–12
  11. By: Nicola Grassano (European Commission - JRC); Hector Hernandez (European Commission - JRC); Alexander Tuebke (European Commission - JRC); Sara Amoroso (European Commission - JRC); Mafini Dosso (European Commission - JRC); Aliki Georgakaki (European Commission - JRC); Francesco Pasimeni (European Commission - JRC)
    Abstract: The main objective of the EU Industrial R&D Investment Scoreboard (the Scoreboard) is to benchmark the performance of EU innovation-driven industries against main global counterparts. The 2020 edition of the Scoreboard analyses the 2500 companies investing the largest sums in R&D in the world in 2019. These companies, with headquarters in 43 countries and more than 800k subsidiaries all over the world, each invested over €34.7 million in R&D for a total of €904.2 billion. A main difference in the presentation of data in this Scoreboard edition regards the new composition of the EU following the departure of the UK on 31 January 2020. Henceforth, in this report, the EU is understood as EU27 (i.e. without the UK) and whenever the UK is included for comparative purposes, it will refer to EU28. The 2020 Scoreboard total R&D is equivalent to approximately 90% of the world’s business-funded R&D. The sample includes 421 companies based in the EU27, accounting for 20.9% of the total R&D in the sample, 775 US companies (38.5%), 309 Japanese companies (12.7%), 536 Chinese (13.1%) and 459 from the rest of the world (14.8%).This report analyses companies' R&D and economic indicators over the past years, focussing on the comparative performance of EU companies with respect to their global counterparts. In 2019, global corporate R&D continued to increase substantially, following the trends of the past years, despite a slowdown in companies’ sales and a decline in profits. This is the tenth consecutive year of R&D increases driven by R&D investments in ICT, Health and Automotive industries. Companies based in the EU27 increased significantly R&D (5.6%) but well below the US (10.8%) and Chinese companies (21%) rates. The impact of the covid-19 crisis is not yet reflected in this edition (2019 data), however, experience demonstrates the important role that R&D plays to tackle major socio-economic issues and to underpin the recovery. Indeed, past Scoreboard editions showed that companies sustaining or increasing R&D investment during previous crisis emerged with greatly improved competitive position in the upturn following the crisis. The Scoreboard results stress the need to step-up the implementation of EU policies aimed at supporting industrial R&D and innovation, especially to support the recovery of the covid-19 crisis and the industrial digital and green transitions.
    Keywords: Industrial R&D, top R&D investors, innovation, company performance, economic and innovation performance
    Date: 2021–10
  12. By: Chu, Angus; Kou, Zonglai; Wang, Xilin
    Abstract: This study explores the conflict of interests between workers and capitalists in a Schumpeterian economy. We consider the limit on the market power of monopolistic firms as a policy instrument and derive its optimal levels for workers and capitalists, respectively. Because monopolistic profit provides incentives for innovation, workers may prefer monopolistic firms to have some market power, but they prefer less powerful monopolistic firms than capitalists. Workers' preferred level of monopolistic power is decreasing in their discount rate and increasing in innovation productivity and the quality step size. Capitalists' preferred level of monopolistic power is increasing in the quality step size. We use the difference in levels preferred by workers and capitalists to measure the severity of their conflict of interests, which becomes less severe when workers' discount rate falls or innovation productivity rises. Finally, at a small (large) quality step size, enlarging the step size mitigates (worsens) their conflict.
    Keywords: economic growth; workers; capitalists; class struggle
    JEL: E11 O3 O4
    Date: 2021–11

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