nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2020‒04‒20
thirteen papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Environmental Preferences and Technological Choices: Is Market Competition Clean or Dirty? By Philippe Aghion; Roland Bénabou; Ralf Martin; Alexandra Roulet
  2. Robotisation, Employment and Industrial Growth Intertwined Across Global Value Chains By Mahdi Ghodsi; Oliver Reiter; Robert Stehrer; Roman Stöllinger
  3. Foreign Direct Investments and Regional Specialization in Environmental Technologies By Davide Castellani; Giovanni Marin; Sandro Montresor; Antonello Zanfei
  4. Technological revolutions, structural change & catching-up By Fagerberg, Jan; Verspagen, Bart
  5. The Effects of Local Market Concentration and International Competition on Firm Productivity : Evidence from Mexico By Rodriguez Castelan,Carlos; Lopez-Calva,Luis-Felipe; Barriga Cabanillas,Oscar Eduardo
  6. Science and Technology Co-evolution in AI: Empirical Understanding through a Linked Dataset of Scientific Articles and Patents By MOTOHASHI Kazuyuki
  7. The Green Jobs and the Industry 4.0. By Grzegorz Michalski; Małgorzata Rutkowska; Adam Sulich; Robert Rohe
  8. Total factor productivity and the measurement of neutral technology By Moura, Alban
  9. Impact of R&D Activities on Pricing Behaviors with Product Turnover By HARA Yasushi; TONOGI Akiyuki; TONOGI Konomi
  10. The Impact of Foreign Technology & Embodied R&D On Productivity in Internationally-Oriented & High-Technology Industries in Egypt, 2006-2009 By Shimaa Elkony; Hilary Ingham; Robert Read
  11. Where Has All the Data Gone? By Maryam Farboodi; Adrien Matray; Laura Veldkamp; Venky Venkateswaran
  12. Heterogeneous Relationships between Automation Technologies and Skilled Labor: Evidence from a Firm Survey By MORIKAWA Masayuki
  13. Theorization of Institutional Change in the Rise of Artificial Intelligence By Masashi Goto

  1. By: Philippe Aghion; Roland Bénabou; Ralf Martin; Alexandra Roulet
    Abstract: This paper investigates the joint effect of consumers' environmental concerns and product-market competition on firms' decisions whether to innovate “clean” or “dirty”. We first develop a step-by-step innovation model to capture the basic intuition that socially responsible consumers induce firms to escape competition by pursuing greener innovations. To test and quantify the theory, we bring together patent data, survey data on environmental values, and competition measures. Using a panel of 8,562 firms from the automobile sector that patented in 42 countries between 1998 and 2012, we indeed find that greater exposure to environmental attitudes has a significant positive effect on the probability for a firm to innovate in the clean direction, and all the more so the higher the degree of product market competition. Results suggest that the combination of historically realistic increases in prosocial attitudes and product market competition can have the same effect on green innovation as major increase in fuel prices.
    JEL: D21 D22 D62 D64 H23 O3 O31
    Date: 2020–04
  2. By: Mahdi Ghodsi (The Vienna Institute for International Economic Studies, wiiw); Oliver Reiter (The Vienna Institute for International Economic Studies, wiiw); Robert Stehrer (The Vienna Institute for International Economic Studies, wiiw); Roman Stöllinger (The Vienna Institute for International Economic Studies, wiiw)
    Abstract: The global economy is currently experiencing a new wave of technological change involving new technologies, especially in the realm of artificial intelligence and robotics, but not limited to it. One key concern in this context is the consequences of these new technologies on the labour market. This paper provides a comprehensive analysis of the direct and indirect effects of the rise of industrial robots and productivity via international value chains on various industrial indicators, including employment and real value added. The paper thereby adds to the existing empirical work on the relationship between technological change, employment and industrial growth by adding data on industrial robots while controlling for other technological advancements measured by total factor productivity (TFP). The results indicate that the overall impact of the installation of new robots did not statistically affect the growth of industrial employment during the period 2000–2014 significantly, while the overall impact on the real value added growth of industries in the world was positive and significant. The methodology also allows for a differentiation between the impact of robots across various industries and countries based on two different perspectives of source and destination industries across global value chains. Disclaimer This is a background paper for the UNIDO Industrial Development Report 2020. Industrializing in the digital age.
    Keywords: Robotisation, digitalisation, global value chains, total factor productivity, industrial growth, employment, value added
    JEL: D57 J21 L16 O14
    Date: 2020–04
  3. By: Davide Castellani (Henley Business School, University of Reading, UK); Giovanni Marin (Department of Economics, Society, Politics, University of Urbino, Italy; SEEDS); Sandro Montresor (Gran Sasso Science Institute, Italy); Antonello Zanfei (Department of Economics, Society, Politics, University of Urbino, Italy)
    Abstract: The paper builds on (eco-)innovation geography and international business studies to investigate the effects of MNEs on regional specialisation in green technologies. Combining the OECD-REGPAT and the fDi Markets datasets with respect to 1,050 European NUTS3 regions over the period 2003-2014, we find that MNEs can positively impact on regions’ specialisation in environmental technologies, when their Foreign Direct Investments (FDIs) occur in industries with a green technological footprint. The effect of green FDIs is further reinforced if they involve R&D activities. We also find that the relatedness of environmental technologies to pre-existing regional specialisations exerts a negative moderating effect on the role of green R&D FDIs in shaping patterns of specialisation. In particular, green R&D FDIs have a larger effect in regions whose prior knowledge base is highly unrelated to environmental technologies. This result is consistent with the idea that MNEs inject the host region with external knowledge, which makes the development of green-technologies less place-dependent.
    Keywords: green regional specialisation; MNEs; FDIs; environmental innovation
    JEL: O31 O33 R11 R58
    Date: 2020–04
  4. By: Fagerberg, Jan (TIK, University of Oslo); Verspagen, Bart (UNU-MERIT, Maastricht University)
    Abstract: Technological revolutions, i.e., clusters of technologies that collectively have a transformational impact on the global economy, are rare events that dramatically influence the opportunities facing countries at different levels of development. A central suggestion in the relevant literature is that countries that manage to adopt the new technologies associated with a specific technological revolution benefit economically from it. This is also assumed to go together with a changing specialisation pattern in international trade. The paper considers the empirical merits of these suggestions, drawing on GDP and trade data for a large number of countries on different levels of development from the post-second-world-war period. The empirical analysis reveals a major divide in the global economy between a group of modern, industrialised countries, specialised in technology-based production, and another group of countries, specialised in commodities and resource-based products, and lagging behind both in terms of technology and income. More to the future, the paper also discusses the extent to which a new green technological revolution, with renewable energy as a central element, is currently emerging, and what impact this possibly might have for catching-up, structural change and economic growth for countries at different levels of development, e.g., China.
    Keywords: Technological revolutions, catching up, specialisation, renewable energy, China
    JEL: O10 O14 O30 O33
    Date: 2020–03–30
  5. By: Rodriguez Castelan,Carlos; Lopez-Calva,Luis-Felipe; Barriga Cabanillas,Oscar Eduardo
    Abstract: Although market concentration is one of the main impediments to productivity growth globally, data constraints have limited its analysis to developed countries or cross-country studies based on definitions of market concentration across nations and industries. This paper takes advantage of a database that is unusual by developing-country standards by means of leveraging the richness of five rounds of the Mexican Manufacturing Census between 1994 and 2014. The data allow estimation of the effects of local industry concentration on productivity. The main results show that a decline by 10 points in the Herfindahl-Hirschman index (on a 0-100 scale), a measure of market concentration, explains an increase by 1 percent in the total factor productivity of revenue. Local industry concentration also has heterogeneous effects on productivity across industries, while its impact on productivity varies by level of exposure to international markets. The results here show that the effect of greater exposure to trade offsets and, in most cases, reverses the negative effects of local concentration on productivity. These results are robust to specifications based on the estimation of firm productivity using the panels of establishment data from the 2009 and 2014 rounds of the economic census, to controlling for a proxy of markups, and to the use of alternate indicators of local industry concentration.
    Date: 2020–04–09
  6. By: MOTOHASHI Kazuyuki
    Abstract: The linked dataset of AI research articles and patents reveals that a substantial public sector contribution is found for AI development. In addition, the role of researchers who are involved both in publication and patent activities, particularly in the private sector, increased over time. That is, open science that is publicly available through research articles and propriety technology that is protected by patents are intertwined in AI development. In addition, the impact of data science, measured by AI research articles on innovation, is analyzed by patent citation analysis. It is found that patents invented by AI paper authors are more likely to have more forward citations by other applicants (non-self-citation), in wider technology fields (greater generality index). This implies that the nature of general purpose technology (GPT) for data science is elevated by the fact that patent inventors are also involved with scientific activities and published as research authors.
    Date: 2020–02
  7. By: Grzegorz Michalski; Małgorzata Rutkowska; Adam Sulich; Robert Rohe
    Abstract: This paper presents and discusses The Industry 4.0 and the “green jobs” definitions and their mutual relations. The Industry 4.0 is a synonym for a new age of technological jump based on digitization and extended Internet connection between devices. Next to this progress also important are a sustainable development and its measurable implementation in labour market – green jobs. Green jobs are decent jobs, either in traditional sectors or in the new green ones, which contribute to preserving or restoring a sustainable environment. This combination of innovation and progress approach can be interesting solution not only for business but also for non-profit organisations which are the subject of the research in this paper. Furthermore, the role of non-profit organizations is examined and described in aspect of changes in green economy and The Industry 4.0 with special emphasis on the maintenance of their capital structure.
    Keywords: Industry 4.0; Green economy; Green jobs
    JEL: O31 Q56
    Date: 2020–04–08
  8. By: Moura, Alban
    Abstract: TFP measures constructed from chain-aggregated output, such as those published by the Bureau of Labor Statistics or Fernald (2014), confound contributions from neutral and sector-specific technology. Therefore, they should not be used to infer the path of neutral technology in presence of investment-specific technical change. Two theory-consistent, utilization-adjusted measures of neutral technology at the quarterly frequency are proposed for the US business sector. Both indicate that neutral technology progress declined dramatically after the mid-1970s. In particular, its contribution to US growth fell from more than 85% before 1973 to less than 25% afterward. The associated welfare loss is enormous: if neutral technology had continued on its pre-1970s trend, 2017 US output would have been 70% higher.
    Keywords: total factor productivity, neutral technology, investment-specific technology, sources of growth
    JEL: E22 E23 E32 O41 O47
    Date: 2020–03
  9. By: HARA Yasushi; TONOGI Akiyuki; TONOGI Konomi
    Abstract: This study empirically investigates the impact of research and development (R&D) activity on product turnover based on Point-of-Sales (POS) data. When measuring the inflation rate in an economy, the effects of quantitative, qualitative and volume changes must be isolated from changes in nominal sales figures. Changes in quality can be attributed to corporate R&D activities. In order to examine the effect of R&D activities on price changes in sales data, we construct a unique dataset by combining three datasets: weekly POS data, patent database (IIP Patent DB) data, and the Survey of Research and Development data. We use regression analysis with pooling and panel regression. We observe that while R&D activity may have a causal effect on price increases, a negative effect on the price of incumbent products is also observed. In addition, the relative prices of new and incumbent products tended to be higher for companies with active R&D expenditures. We suggest that continuous R&D is necessary to keep introducing high value products that place upward pressure on prices.
    Date: 2020–01
  10. By: Shimaa Elkony; Hilary Ingham; Robert Read
    Abstract: This paper investigates the domestic productivity and spillover effects of foreign technology and embodied R&D on Egyptian manufacturing industries, 2003 to 2009. It also analyses the heterogeneous sectoral effects of technology transfer by focusing specifically on the productivity effects on highly internationalised and technology intensive industries. These are expected to have greater absorptive capacity with respect to foreign technology and therefore greater productivity effects because of their greater exposure to foreign competition and greater technological capacity respectively. The study is the first to analyse the efficiency effects of foreign technology by classifying industries in this manner. The study finds that foreign technology and embodied R&D have positive and significant industry-specific effects on domestic productivity and TFP in technology intensive industries but these are weaker in internationally-oriented industries. The findings suggest that only the technological intensive industries in Egypt have sufficient absorptive capacity to assimilate foreign technology effectively. The paper’s findings highlight the key role of foreign technology in domestic productivity growth, subject to the absorptive capacity of the domestic labour force, and the need for improved policies to promote the domestic benefits of technology transfer through the accumulation of local technological competences.
    Keywords: Foreign Technology, International R&D, Industrial Productivity, Trade
    JEL: D24 L60 O30
    Date: 2020
  11. By: Maryam Farboodi; Adrien Matray; Laura Veldkamp; Venky Venkateswaran
    Abstract: As financial technology improves and data becomes more abundant, do market prices reflect this data growth? While recent studies documented rises in the information content of prices, we show that, across asset types, there is data divergence. Large, growth stock prices increasingly reflect information about future firm earnings. This is the rise reflected in the previous studies. But over the same time period, the information content of small and value firm prices was flat or declining. Our structural estimation allows us to disentangle these informational trends from changing asset characteristics. These facts pose a new puzzle: Amidst the explosion of data processing, why has this data informed only the prices of a subset of firms, instead of benefiting the market as a whole? Our structural model offers a potential answer: Large growth firms' data grew in value, as big firms got bigger and growth magnified the effect of these changes in size.
    JEL: G14
    Date: 2020–04
  12. By: MORIKAWA Masayuki
    Abstract: Based on an original survey of Japanese firms, this study presents evidence of the use of recent automation technologies—artificial intelligence (AI), big data analytics, and robotics—and discusses the relationship between these technologies and skilled employees at the firm-level. The result indicates that while the number of firms already using these technologies is small, the number of firms interested in using them is large. The use of AI and big data is positively associated with the share of highly educated employees, particularly those with a postgraduate degree; however, such a relationship is absent in the case of the use of industrial robots in the manufacturing industry. Studies have not distinguished between robotics and other automation technologies, such as AI, but the result suggests a heterogeneous complementarity with high-skilled employees for each type of automation technology.
    Date: 2020–01
  13. By: Masashi Goto (Research Institute for Economics and Business Administration, Kobe University, Japan)
    Abstract: This study explores how professional institutional change is theorized in the context of the emergence of disruptive technology as a precipitating jolt. I conducted a case study of two Big four accounting firms in Japan on their initiatives to apply artificial intelligence (AI) to their core audit services between 2015 and 2017. The data shows the process for incumbent dominant organizations to collaborate and develop social perceptions about the changing but continuing relevance of their profession. The analysis suggests that the retheorization can advance even without concrete alternative templates when disruptive technology is perceived to have overwhelming influences, following multi-level steps progressing from internal to external theorization. This article proposes a grounded theory model of the process of professional institutional change: (1) Theorizing change internally at the field, (2) Developing solutions by experimentations in organizations, (3) Exploring solutions driven by individuals in organizations and (4) Theorizing change externally by organizations. It contributes to the profession and institutional scholarship by expanding our knowledge about the diversity of professional institutional field change process in this age of increasing technology influences on organizations.
    Keywords: Institutional change; Professions; Artificial intelligence; Qualitative research; Grounded theory
    Date: 2020–03

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