nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2023‒06‒12
eleven papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Does Green Transition promote Green Innovation and Technological Acquisitions? By Martinez Cillero, Maria; Gregori, Wildmer Daniel; Bose, Udichibarna
  2. Informing Innovation Management: Linking Leading R&D Firms and Emerging Technologies By Xian Gong; Claire McFarland; Paul McCarthy; Colin Griffith; Marian-Andrei Rizoiu
  3. Antitrust and (Foreign) Innovation: Evidence from the Xerox Case By Robin Mamrak
  4. Evaluating the Principle of Relatedness: Estimation, Drivers and Implications for Policy By Frank Neffke; Yang Li
  5. Innovation in Artificial Intelligence and the Catalyst of Open Data Sharing: Literature Review and Policy implications By Dam, John; Rickon, Henry
  6. Digital de-industrialization, global value chains, and structural transformation: Empirical evidence from low- and middle-income countries By Karishma Banga; Pankhury Harbansh; Surendar Singh
  7. Functional Public Procurement and Innovation – The Concepts By Edquist, Charles
  8. Global Divergence in the De-routinization of Jobs By Lewandowski, Piotr; Park, Albert; Schotte, Simone
  9. Generative AI and Firm Values By Andrea L. Eisfeldt; Gregor Schubert; Miao Ben Zhang
  10. The Dynamics of Labour Market Polarization in Chile: An Analysis of the Link Between Technical Change and Informality By Delaporte, Isaure; Peña, Werner
  11. Structural transformation and international trade: Evidence from the China shock By Clément Nedoncelle; Julien Wolfersberger

  1. By: Martinez Cillero, Maria (European Commission); Gregori, Wildmer Daniel (Banco de Portugal); Bose, Udichibarna (University of Essex)
    Abstract: This analysis explores the implications of technological shifts towards greener and sustainable innovations on acquisition propensity between firms with different technological capacities. Using a dataset of completed control acquisition deals over the period of 2009-2020 from 23 OECD countries, we find that innovative firms are more likely to acquire innovative target companies. We also find that green acquirors (i.e., firms with green patents) are more inclined to enter into acquisition deals with green firms, possibly due to their technological proximity and informational advantages which further enhances their post-acquisition green innovation performances. Our results also show an increase in green acquisitions after the Paris Agreement by non-green acquiror firms, and these are more pronounced for acquirors in climate policy-relevant sectors and countries with low environmental standards than their counterparts. However, green acquisitions after the Paris Agreement do not show any significant impact on their post-acquisition innovation performances, raising concerns related to greenwashing behaviour by investing firms.
    Keywords: Acquisitions, green patents, firm innovation, Paris agreement, green transition
    JEL: G34 O30 Q54 Q55
    Date: 2023–04
  2. By: Xian Gong; Claire McFarland; Paul McCarthy; Colin Griffith; Marian-Andrei Rizoiu
    Abstract: Understanding the relationship between emerging technology and research and development has long been of interest to companies, policy makers and researchers. In this paper new sources of data and tools are combined with a novel technique to construct a model linking a defined set of emerging technologies with the global leading R&D spending companies. The result is a new map of this landscape. This map reveals the proximity of technologies and companies in the knowledge embedded in their corresponding Wikipedia profiles, enabling analysis of the closest associations between the companies and emerging technologies. A significant positive correlation for a related set of patent data validates the approach. Finally, a set of Circular Economy Emerging Technologies are matched to their closest leading R&D spending company, prompting future research ideas in broader or narrower application of the model to specific technology themes, company competitor landscapes and national interest concerns.
    Date: 2023–05
  3. By: Robin Mamrak (LMU Munich)
    Abstract: How does antitrust enforcement against patent-based monopolies affect innovation? I address this question by empirically studying the US antitrust case against Xerox, the monopolist in the market for plain-paper copiers. In 1975, Xerox was ordered to license all its copier-technology patents in the US and abroad. I show that this promoted innovation by other firms in the copier industry, measured by a disproportionate increase in patenting in technologies where Xerox patents became available for licensing. This positive effect is driven by increased innovation by Japanese competitors. They started developing smaller desktop copiers and their innovation became more diverse.
    Keywords: antitrust; innovation; patents; compulsory licensing; Japan; Xerox;
    JEL: O30 O34 L41 K21
    Date: 2023–05–12
  4. By: Frank Neffke (Center for International Development at Harvard University); Yang Li
    Abstract: A growing body of research documents that the size and growth of an industry in a place depends on how much related activity is found there. This fact is commonly referred to as the "principle of relatedness." However, there is no consensus on why we observe the principle of relatedness, how best to determine which industries are related or how this empirical regularity can help inform local industrial policy. We perform a structured search over tens of thousands of specifications to identify robust – in terms of out-of-sample predictions – ways to determine how well industries fit the local economies of US cities. To do so, we use data that allow us to derive relatedness from observing which industries co-occur in the portfolios of establishments, firms, cities and countries. Different portfolios yield different relatedness matrices, each of which help predict the size and growth of local industries. However, our specification search not only identifes ways to improve the performance of such predictions, but also reveals new facts about the principle of relatedness and important trade-offs between predictive performance and interpretability of relatedness patterns. We use these insights to deepen our theoretical understanding of what underlies path-dependent development in cities and expand existing policy frameworks that rely on inter-industry relatedness analysis.
    Keywords: Economic Complexity, Structural Transformation, Cities
    Date: 2023–03
  5. By: Dam, John; Rickon, Henry
    Abstract: This literature review aims to elucidate the nuanced relationship between data openness and innovation within the field of Artificial Intelligence (AI). As the significance of AI continues to expand across various sectors, understanding the role of open data in fostering innovation becomes increasingly critical. Through this review, we systematically explore and analyze the wealth of existing literature on the topic. We address key concepts, theoretical perspectives, and empirical findings, shedding light on the multi-dimensional facets of data openness, including accessibility and usability, and their impact on AI innovation. Furthermore, the review highlights the practical implications and potential strategies to leverage data openness in propelling AI innovation. We also identify existing gaps and limitations in current literature, suggesting avenues for future research. This comprehensive review contributes to the evolving discourse in AI studies, offering valuable insights to researchers, data managers, and AI practitioners alike.
    Date: 2023–05–15
  6. By: Karishma Banga; Pankhury Harbansh; Surendar Singh
    Abstract: Digitalization and shifting patterns of globalization are fast changing the rules of the game for countries embarking on a path of industrialization. In this study, we empirically examine the impact of digitalization and global value chains on structural transformation using a cross-country panel of 51 economies in the GGDC/UNU-WIDER Economic Transformation Database for the period 1990-2018.
    Keywords: Deindustrialization, Technology, Structural transformation, Global value chains, Industrialization
    Date: 2023
  7. By: Edquist, Charles (CIRCLE, Lund University)
    Abstract: The literature on the relations between public procurement and innovation has been growing rapidly during the latest couple of decades. However, there are still conceptual problems and unclarities with regard to key concepts. The purpose of this conceptual paper is to sort out and specify the notions of “innovation”, “public procurement”, “product procurement”, “functional procurement” and “innovation partnerships” – as well as the relations between them. <p> Some findings in this paper are: <p> • The distinction between product specifications and functional specifications is a useful dichotomy when discussions of the relations between public procurement and innovation are pursued and when public procurement is carried out in practice. It can be instrumental in transforming procurement that prevents innovations into procurement that enhances innovations. The development of this dichotomy means that we have changed the conceptual framework needed to understand and explain the relationships between (different kinds of) public procurement on one hand and innovation on the other hand. <p> • Functional procurement is not only allowed by the EU procurement directives. It is strongly encouraged “and should be used as widely as possible”, according to the EU directives. <p> • “Innovation partnership” is a new procedure in the EU procurement directives. It is intended to also address R&D results and innovations as outcomes of public procurement processes. However, this procedure has not been used very much. One reason is that the directive needs a much higher specificity to become operatively useful. This procedure should also be related to functional public procurement.
    Keywords: Innovation; System of innovation; Innovation policy; Holistic innovation policy; Linear view; Research Policy
    JEL: O30 O38 O49 O52
    Date: 2023–05–08
  8. By: Lewandowski, Piotr (Institute for Structural Research); Park, Albert (Asian Development Bank); Schotte, Simone (United Nations–University World Institute for Development Economics Research)
    Abstract: This study introduces a methodology to estimate the economy-specific task content of occupations across economies at different income levels. Combining these with employment data in 87 economies, the results show that occupations in low- and middle-income economies are more routine-intensive than in high-income economies, which is attributed to lower technology use in less-developed economies. Non-routine work continues to dominate in high-income economies while routine work remains in low-income and middle-income economies. These findings, using economy-specific estimates of occupational task content, contradict the assumption based on conventional measures that task content of occupations is converging globally. The finding of divergent trends in the relative routine intensity of work in developed and developing economies has important policy implications. Investment in skills, technology use, and participation in global value chains are key factors for work content and productivity to converge with those in high-income economies. The assumption that occupations are converging globally may also overestimate the role of routine-replacing technological change in explaining wage inequality in low- or middle-income economies.
    Keywords: occupational task content; routine-task intensity; skills; jobs divergence; wage inequality
    JEL: J24 J31 O14 O15
    Date: 2023–05–12
  9. By: Andrea L. Eisfeldt; Gregor Schubert; Miao Ben Zhang
    Abstract: What are the effects of recent advances in Generative AI on the value of firms? Our study offers a quantitative answer to this question for U.S. publicly traded companies based on the exposures of their workforce to Generative AI. Our novel firm-level measure of workforce exposure to Generative AI is validated by data from earnings calls, and has intuitive relationships with firm and industry-level characteristics. Using Artificial Minus Human portfolios that are long firms with higher exposures and short firms with lower exposures, we show that higher-exposure firms earned excess returns that are 0.4% higher on a daily basis than returns of firms with lower exposures following the release of ChatGPT. Although this release was generally received by investors as good news for more exposed firms, there is wide variation across and within industries, consistent with the substantive disruptive potential of Generative AI technologies.
    JEL: E0 G0
    Date: 2023–05
  10. By: Delaporte, Isaure; Peña, Werner
    Abstract: In spite of the growing literature on polarization, relatively little is known about the individual-level patterns underlying the decline of routine occupations and its link with informal employment in a middle-income country context. To shed light on this, we examine the ows of formal and informal workers into and out of routine and non-routine occupations over the period 1980-2015 in Chile. Using rich longitudinal data from the Social Protection Survey of Chile, we first reconstruct individuals' occupational trajectories by classifying individuals into different states at a monthly frequency. We then use a series of multilevel competing risk event history models and a decomposition ow approach to study the ows underlying the decline of routine occupations over time. Our results suggest a process of displacement and occupational downgrading for routine manual workers: workers in routine manual formal employment become increasingly unemployed or use informality as a buffer against job loss, and workers in routine manual informal employment become unemployed or transit to non-routine manual informal occupations. By contrast, workers in routine cognitive occupations seem to be relatively more protected against job displacement and occupational downgrading. Lastly, we find that the decrease in the share of routine occupations in Chile is mostly due to a decrease in the in ow transition rate from unemployment as well as an increase in the out ow transition rates to unemployment and informality.
    Keywords: Occupations, Tasks, Routinization, Labour Market Displacement, Unemployment, Informality
    JEL: E24 E26 J21 J23 J24 O30
    Date: 2023
  11. By: Clément Nedoncelle; Julien Wolfersberger
    Abstract: How does international trade affect structural transformation in developing countries? We use data on sectoral allocation of labour and value-added in 46 developing economies over the period 1995-2017 and exploit for identification plausibly exogenous variation in manufacturing imports from China. We find that the so-called 'China shock' largely slows down the transformation of low- and middle-income economies out of agriculture. In our main specification industrialization decreases by 0.49 per cent on average for each additional per cent of manufacturing imports from China.
    Keywords: Developing countries, Industrialization, Structural transformation, Trade
    Date: 2023

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