nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2020‒08‒24
fourteen papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Working Paper 340 - Innovation and Productivity in Developing Economies By Hanan Morsy; Amira El-Shal
  2. Subsidising Innovation over the Business Cycle By Isabel Busom; Jorge Velez-Ospina
  3. Green Innovation and Income Inequality: A Complex System Analysis By Lorenzo Napolitano; Angelica Sbardella; Davide Consoli; Nicolo Barbieri; Francois Perruchas
  4. Global race for robotisation - Looking at the entire robotisation chain By Zoltan Csefalvay; Petros Gkotsis
  5. Offshoring: What Consequences for Workers? Evidence from Global Value Chains By Katharina Längle
  6. Technological Diffusion through Foreign Direct Investment: A Firm-level Analysis of Indian Manufacturing Industries By Azusa Fujimori; Manabu Furuta; Takahiro Sato
  7. Innovation and growth in the UK pharmaceuticals: the case of product and marketing introductions By Farasat A.S. Bokhari; Franco Mariuzzo; Anna Rita Bennato
  8. Going Revolutionary: The Impact of 4IR Technology Development on Firm Performance By Mario Benassi; Elena Grinza; Francesco Rentocchini; Laura Rondi
  9. Structural adjustment and changes to employment use in Japan By Timothy DeStefano; Filipe Silva; Sho Haneda; Hyeog Ug Kwon
  10. The Geography of Technology Legitimation. How multi-scalar legitimation processes matter for path creation in emerging industries By Jonas Heiberg; Christian Binz; Bernhard Truffer
  11. Robots and employment: evidence from Italy By Davide Dottori
  12. Smart Specialization Strategy: any relatedness between theory and practice? By E. Marrocu; R. Paci; D. Rigby; S. Usai
  13. The geography of innovation and development: global spread and local hotspots By Crescenzi, Riccardo; Iammarino, Simona; Ioramashvili, Carolin; Rodríguez-Pose, Andrés; Storper, Michael
  14. The Effects of EU-Funded Enterprise Grants on Firms and Workers By Muraközy, Balázs; Telegdy, Álmos

  1. By: Hanan Morsy (Research Department, African Development Bank); Amira El-Shal (Research Department, African Development Bank)
    Abstract: We examine the determinants of innovation and its effect on productivity across 52 emerging and developing economies, comparing African firms to their counterparts elsewhere. We use a generalized structural equation model (GSEM) to estimate the causal links while accounting for endogeneity. Our estimates show that access to finance has the strongest effect on firms' decisions to invest in research and development (R&D) in all countries. And while the drivers of innovation are remarkably similar in developed economies, the keys for African firms are access to external knowledge - largely via information and communications technology (ICT)- and skills development via on-the-job training. Only in Africa is the stand-alone effect of ICT adoption on innovation almost as strong as that of R&D; and the combined effect of firms' access to external knowledge through ICT and foreign-technology adoption and training is more than double that of R&D. Regardless of its content, the effect of employee training on innovation in Africa is double that in emerging markets. Finally, innovation is the key determinant of productivity in all countries, but the evidence is much stronger for product innovation by African firms.
    Keywords: Innovation, productivity, R&D, ICT, training, GSEM, latent variable, developing countries, Africa JEL classification: C30, D24, J24, M53, O3, O5
    Date: 2020–06–26
  2. By: Isabel Busom (Department of Applied Economics: Universitat Autonoma de Barcelo); Jorge Velez-Ospina (Science Policy Research Unit (SPRU), University of Sussex)
    Abstract: We investigate whether the impact of direct support for business investment in R&D and innovation varies over the business cycle. We study whether firms that obtain public support in a recession differ from firms that obtain it during expansions; whether the impact of support is smaller in recessions than in expansions, and whether effects vary with the treatment pattern. Using firm-level data from Spain during the period 2005 to 2014, we combine propensity score matching and difference-in-differences methods to estimate firms’ response. We find that (i) while the impact of support on monetary investment in innovation is pro-cyclical, it is counter-cyclical in terms of the employee-time allocation to innovation activities; (ii) the additionality of a one-year treatment is smaller than that of a longer treatment. Direct public support may have thus prevented a decline of the firms’ knowledge capital during the recession.
    Keywords: R&D subsidies, policy evaluation, business cycle, additionali
    JEL: O25 O38 C14 C21 D22 L29 L53 H5
    Date: 2020–06
  3. By: Lorenzo Napolitano; Angelica Sbardella; Davide Consoli; Nicolo Barbieri; Francois Perruchas
    Abstract: The objective of this paper is to analyse the relationship between income inequality and environmental innovation. We use a complexity-based algorithm to compute an index of green inventive capacity in a panel of 57 countries over the period 1970–2010. The empirical analysis reveals that, on average, inequality is detrimental to countries’ capacity to engage complex green technologies knowledge bases. Using non-parametric methods allows us to further articulate this general finding and to uncover interesting non-linearities in the relationship between innovation and inequality
    Keywords: Complexity; Environmental Innovation; Inequality
    Date: 2020–07
  4. By: Zoltan Csefalvay (European Commission - JRC); Petros Gkotsis (European Commission - JRC)
    Abstract: Where does Europe stand in the global robotisation race? This paper aims to answer this question by developing a novel theoretical and analytical framework which applies the concept of a global value chain to robotisation. By doing this, we investigate in detail the entire robotisation chain, from robotics developers to robot manufacturers, and companies that deploy industrial robots. For the research and development (R&D)-intensive part of the chain (robotics development), we analyse the robotics patent data of the Worldwide Patent Statistical Database (PATSTAT) combined with ORBIS, while for the capital-intensive part (deployment of robots), our information is sourced from the International Federation of Robotics (IFR). Our results show that although the ‘big five’ (Europe, USA, China, Japan, and Korea) dominate the global robotisation landscape they do not all hold equally strong positions across the whole robotisation chain. Japan and Korea are the early first-movers and today’s global leaders, as they are robustly engaged in every part of the chain. Europe is very strong in robot manufacturing and robot deployment, but is behind global leaders in robotics development. The USA has its firm competitive advantages in robotics development, while at present the latecomer China is a rival only in the industrial deployment of robots. Nevertheless, in Europe, some smaller and advanced economies are specialising in certain parts of the robotisation chain, as Austria, Denmark, France, the Netherlands, and Sweden are performing well in robotics development; not only this, Belgium, Italy, and Spain are making extensive use of industrial robots for various kinds of manufacturing. European economies which are lagging behind the rest – largely consisting of Central and Eastern European countries – are involved in the robotisation chain only insofar as they are involved in robot deployment. Since there are only 43 countries globally who are taking part in robotisation, the eminent policy challenge remains to find ways for countries to become integrated into the robotisation chain, and for those countries already engaged in robotisation, the main focus is to create policies which support upgrading across the chain, as the reshoring of previously offshored production becomes more prevalent.
    Keywords: robotisation, global value chain, robotics patent, industrial transformation, territorial development, Europe
    JEL: O3 O14 O30 O25
    Date: 2020–07
  5. By: Katharina Längle (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics)
    Abstract: This paper investigates the question which aspects of offshoring harm low skilled workers using data from the WIOD for 14 manufacturing industries in 16 countries between 1995 and 2008. By considering the use of foreign production factors in domestic production, the paper shows that low skilled workers are directly and negatively affected by offshoring of low skilled tasks. Importantly, the paper determines a further indirect channel highlighting the role of growing foreign competition in domestic markets for intermediate goods. Accordingly, wage shares of low skilled workers decline when competition in domestic downstream value chains increases. Interpreting this channel in the light of the literature on defensive skill-biased innovation, the shift in wage shares away from low skilled workers might be provoked by skill intensive investments in response to tougher foreign competition in domestic markets for intermediate goods.
    Keywords: Global value chains,Input-Output Tables and Analysis,Organization of Production,Empirical Studies of Trade
    Date: 2020–04
  6. By: Azusa Fujimori (Department of Management, Osaka Seikei University, Japan); Manabu Furuta (Department of Economics, Aichi Gakuin University, Japan); Takahiro Sato (Research Institute for Economics and Business Administration, Kobe University, Japan)
    Abstract: This study examines technology diffusion resulting from foreign direct investment (FDI) in the domestic manufacturing sector in India. We employ unit-level panel data (where a unit refers to an enterprise within the manufacturing sector) from 2000 to 2007, covering all medium- and large-size manufacturing enterprises in India, obtained from India's Central Statistics Office. We attempt to empirically capture evidence of FDI technology spillover effects through two key mechanisms: horizontal spillover (technology diffusion within the same industry) and vertical spillover (technology diffusion between foreign firms and their customer or suppliers). Vertical spillover effects can be further divided into backward linkages (technology diffusion from foreign firms to upstream industries), and forward linkages (technology diffusion from foreign firms to downstream industries). In addition, technology diffusion can be the result of both short- and long-term spillover effects. The results of the empirical analyses highlight the presence of short- and long-term horizontal spillover effects, both of which negatively affect the total factor productivity performance of domestic manufacturers. Moreover, we find an inverse relationship between the growth of FDI and total factor productivity in upstream industries in the short term; however, this changes to a positive relationship in the long term. Furthermore, the results show no evidence of FDI spillover effects to downstream sectors.
    Keywords: Technology diffusion; Foreign direct investment; Total factor productivity; Backward spillover effect; Manufacturing industries; Unit-Level data
    JEL: C81 F21 O53
    Date: 2020–03
  7. By: Farasat A.S. Bokhari (Centre for Competition Policy and School of Economics, University of East Anglia); Franco Mariuzzo (Centre for Competition Policy and School of Economics, University of East Anglia); Anna Rita Bennato (Centre for Competition Policy, University of East Anglia and Loughborough University)
    Abstract: New drug introductions are a key to growth for pharmaceutical firms. However not all innovations are the same and they may have differential effects that vary by firm size. We use quarterly sales data on UK pharmaceuticals in a dynamic panel model to estimate the impact of product (new drugs) and marketing (additional pack varieties) innovations within a therapeutic class on a firm's business unit growth. We find that product innovations lead to substantial growth in both the short and long run, whereas a new pack variety only produces short-term effects. The strategies are substitutes but the marginal effects are larger for product innovations relative to additional packs, and the effects are larger for smaller business units. Nonetheless, pack introductions offer a viable short-term growth strategy, especially for small and medium sized businesses.
    Keywords: Growth; Innovation; Size; Pharmaceuticals; Business unit
    JEL: L25 L65 O31 O32
    Date: 2019–10–01
  8. By: Mario Benassi (Department of Economics, Management, and Quantitative Methods, University of Milan); Elena Grinza (Department of Management and Production Engineering, Politecnico di Torino); Francesco Rentocchini (Department of Economics, Management, and Quantitative Methods, University of Milan); Laura Rondi (Department of Management and Production Engineering, Politecnico di Torino)
    Abstract: Drawing on the knowledge-based view of the firm, we investigate whether firm performance is related to the accumulated stock of technological knowledge associated with the Fourth Industrial Revolution (4IR), and what contextual factors affect this relationship. We test our research questions on a longitudinal matched patent-firm data set on large firms filing 4IR patents at the European Patent Office (EPO). Our results, which control for a large number of patent- and firmlevel variables as well as firm fixed unobserved heterogeneity, show a significant and economically relevant positive association between the development of 4IR technologies and firm productivity. However, no significant relationship with firm profitability is detected, thereby suggesting that the returns from 4IR technological developments are slow to cash in. We also find that late innovators benefit more from the development of 4IR technological capabilities than early innovators and experience a substantial “boost effect”. We provide empirical support to an explanation of these findings in terms of the ability of late innovators to (i) manage the inherent complexity of the bundle of technologies comprising the 4IR and (ii) exploit profitable downstream applications of the 4IR.
    Keywords: Fourth Industrial Revolution (4IR); patenting; technology development; firm performance; longitudinal matched patent-firm data
    JEL: O33 D24 J24
    Date: 2020–06
  9. By: Timothy DeStefano (OECD); Filipe Silva (OECD); Sho Haneda (Nihon University); Hyeog Ug Kwon (Nihon University)
    Abstract: This paper examines the determinants of structural adjustment in Japan and identifies several factors that explain the use of certain employment types. Its findings are based on a novel plant-level dataset that provides considerable detail on the types of employees used by Japanese manufacturers between 2001 and 2014. Analysis of this dataset shows that growth in the diffusion of robotics is linked to fewer non-regular employees, which seems to be partially driven by the positive association between robot adoption and the dismissal of certain types of non-regular workers. It also finds that offshoring from Japan to other countries contributes to the use of both regular and non-regular workers, while higher plant productivity is related to the use of more regular workers. Finally, establishments that experienced job dismissals appear to substitute non-regular workers for regular workers.
    Keywords: Employment composition, Layoffs, Structural adjustment
    JEL: J21 J23
    Date: 2020–08–20
  10. By: Jonas Heiberg; Christian Binz; Bernhard Truffer
    Abstract: Research in economic geography has recently been challenged to adopt more institutional and multi-scalar perspectives on industrial path development. This paper contributes to this debate by integrating insights from (evolutionary) economic geography, as well as transition and innovation studies into a conceptual framework of how path creation in emerging industries depends on the availability of both knowledge and legitimacy. Unlike the extant literature, we argue here, that not only the former but also the latter may substantially depend on non-local sources, which hithero have largely been overseen. Conceptually, we distinguish between multi-scalar export, attraction and absorption of legitimacy. Coupled with conventional knowledge indicators, this approach enables us to reconstruct how not only external knowledge sourcing but also multi-scalar institutional dynamics contribute to countries’ ability to leverage the potential of different path creation constellations in an emerging industry. Methodologically, we develop legitimation indicators from a global media database, which was built around the case of modular water technologies. Cross-comparing the evidence from six key countries (India, Israel, Singapore, South Africa, UK, USA) with differing path creation constellations allows us to hypothesize how multi-scalar legitimation influences a country’s prospects for creating a radically new industrial path.
    Keywords: Evolutionary economic geography, path creation, legitimation, institutional dynamics, multi-scalarity, modular water technologies
    JEL: O33 O31 D85 L95
    Date: 2020–08
  11. By: Davide Dottori (Bank of Italy, Ancona regional branch)
    Abstract: Increased robot diffusion has raised concerns for its possible negative impact on employment. Following an empirical approach in line with those applied to the US and Germany with contrasting results, this paper provides evidence about the effect of robots on employment outcomes in Italy (second European economy for robot stock) from the early 1990s up to 2016, both at the local labour market (LLM) level and at the worker level. In order to purge from demand and other confounding shocks, the identification relies on an instrumental variables strategy based on robots’ sectoral growth in other European countries. No harmful impact on total employment emerges from the LLM analysis; the estimated effect is negative when limited to manufacturing employment, but its statistical significance is weak or absent once concurrent trends relating to trade and ICT are controlled for. Results at the worker level show that incumbent workers in manufacturing were not damaged on average, with an overall positive (though not large) employment effect, driven by longer working relationships with the original firm; conditional on them remaining at the original firm, the impact is also positive on wages. On the other hand, robot diffusion turns out to have contributed to reshaping the sectoral distribution of the new labour force inflows towards less robot intensive industries.
    Keywords: robot, automation, employment, local labour markets, wages
    JEL: J23 J31 L11 L60 O33 R11
    Date: 2020–07
  12. By: E. Marrocu; R. Paci; D. Rigby; S. Usai
    Abstract: The smart specialization strategy (S3) has been at the core of European Cohesion Policy supporting regions to identify the technologies and economic sectors that might comprise sustainable growth paths. Most regions have included S3 in their development policies and devoted a share of available EU resources to their Regional Operational Programmes for the period 2014-2020. This paper provides one of the first attempts in the literature to assess empirically whether the choices made by European regions in selecting their S3 sectors are consistent, directly and indirectly, with their current specialisation patterns. The latter refer to the regional economy as a whole and not just to the manufacturing sector. Previous contributions that have focused on patent data may be biased because of the concentration of patenting within manufacturing. Analysis of S3 strategies draws from the EC official S3 website, where all regions were compelled to disclose their industrial and technological targets. Results show that regional strategies are heterogeneous. There are a few regions that have chosen a new S3 path rooted both in current sectors within which they enjoy comparative advantage and on related activities. However, overall, regions have not selected sectors highly associated with their current specialization or closely related to it, indicating a limited potential for S3 to activate successful growth trajectories that leverage existing capabilities.
    Keywords: Smart Specialization Strategy;regional development;capabilities;revealed comparative advantage;relatedness
    Date: 2020
  13. By: Crescenzi, Riccardo; Iammarino, Simona; Ioramashvili, Carolin; Rodríguez-Pose, Andrés; Storper, Michael
    Abstract: Through successive industrial revolutions, the geography of innovation around the globe has changed radically, and with it the geography of wealth creation and prosperity. Since the Third Industrial Revolution, high incomes are increasingly metropolitan, leading to a renewal of inter-regional divergence within countries. These metropolitan areas are also hotbeds of innovation. At the same time, global networks for the production and delivery of goods and services have expanded greatly in recent decades. The globalization of production is mirrored in the globalization of innovation. The paper argues that the emerging geography of innovation can be characterised as a globalized hub-to-hub system, rather than a geography of overall spread of innovation and illustrates these trends using patent data. Although much attention has been given to explaining the rise and growth of innovation clusters, there is as yet no unified framework for the micro-foundations of the agglomeration and dispersion of innovation. In addition, there appear to be strong links between growing geographical inequality of innovation and prosperity, particularly within countries. This is particularly relevant in the context of declining overall research productivity, which could be driving growing geographical concentration. All in all, there is a rich agenda for continuing to investigate the relationship between the geography of innovation, economic development and income distribution.
    Keywords: geography of innovation; clusters; networks; inequality
    JEL: O33 R12
    Date: 2020–06
  14. By: Muraközy, Balázs (University of Liverpool); Telegdy, Álmos (Corvinus University of Budapest)
    Abstract: This paper investigates the effects of non-repayable enterprise grants financed from the European Union's Structural and Cohesion Funds on firm outcomes in Hungary using firm- and worker-level information on all rejected and successful grant applications between 2004-2014. In our model, after paying the fixed cost of applying, firms can purchase capital at a reduced marginal cost and they share the rent generated from the grant with their workers. In line with the model's predictions, larger than average, more productive and faster growing firms are more likely to apply for a grant. We combine panel regression methods with matching techniques to estimate the effect of grants by comparing successful and unsuccessful applicants' outcomes. Subsidized firms increase their employment, sales, capital-to-labor ratio and labor productivity, but not total factor productivity. The skill composition of workers is not affected by the grant but wages grow, especially for skilled workers. Firms winning multiple grans benefit more already from the first grant and successive grants have even larger effects. According to our simple calculations, each year's subsidy program created jobs in grant winning firms equivalent to 0.3-0.5 percent of total SME employment and contributed by 0.3-0.7 percentage points to aggregate SME productivity growth – with an annual cost often in excess of 1 percent of total SME value added. These results suggest that these grants promote firm growth, but do not lead firms to introduce new forms of production or upgrade technology.
    Keywords: enterprise grants, EU grants, worker effects, matched employer-employee data, Hungary
    JEL: H25 D22 O16 J21
    Date: 2020–06

This nep-tid issue is ©2020 by Fulvio Castellacci. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.