nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2019‒10‒07
ten papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Structural Transformation of Innovation By Diego Comin; Danial Lashkari; Marti Mestieri
  2. Productivity and innovation at the industry level: What role for integration in global value chains? By Peter Gal; William Witheridge
  3. Global Innovation and Knowledge Diffusion By Nelson Lind; Natalia Ramondo
  4. Fostering innovation in South Asia: Evidence from FMOLS and Causality analysis By shah, Muhammad ibrahim
  5. Declining Dynamism, Increasing Markups and Missing Growth: The Role of the Labor Force By Michael Peters; Conor Walsh
  6. World Corporate Top R&D investors: Shaping the Future of Technologies and of AI By Helene Dernis; Petros Gkotsis; Nicola Grassano; Shohei Nakazato; Mariagrazia Squicciarini; Brigitte van Beuzekom; Antonio Vezzani
  7. Teaming up with Large R&D Investors: Good or Bad for Knowledge Production and Diffusion? By Sara Amoroso; Simone Vannuccini
  8. The effects of R&D subsidies and publicly performed R&D on business R&D: A survey By Ziesemer, Thomas
  9. Procurement in Big Science Centres: politics or technology? Evidence from CERN By Andrea, Bastianin; Chiara F., Del Bo
  10. Experimental Innovation Policy By Albert Bravo-Biosca

  1. By: Diego Comin (Dartmouth College); Danial Lashkari (Boston College); Marti Mestieri (Northwestern University)
    Abstract: We develop a multi-sector endogenous growth model in which the direc- tion of innovation across sectors is endogenous. The model provides a the- oretical general equilibrium framework for studying the classical demand- pull and technology-push drivers of innovation. A robust prediction is that the rate of growth innovation growth is asymptotically higher in more income-elastic sectors. We test this prediction using the universe of U.S. patents and firm R&D investments for the period 1976-2007. The analysis lends empirical support for the main predictions of the model.
    Date: 2019
  2. By: Peter Gal; William Witheridge
    Abstract: Productivity growth has declined in most advanced economies in the past two decades and there are signs that the pace of global value chain (GVC) integration has slowed in the post-crisis period. This paper explores the role of GVCs - international trade in intermediate inputs - for multi-factor productivity growth using a range of cross-country industry-level data sources. We find that greater participation in GVCs is associated with faster domestic productivity growth at the industry level. We estimate that if GVCs had continued to grow at their pre-crisis trend, productivity growth would have been around 1 percentage point faster over the subsequent five years in both manufacturing and services. We also find that the productivity-enhancing direction of trade differs between sectors. For manufacturing sectors, greater use of intermediate inputs from foreign sources (backward participation) is linked with faster productivity growth, reflecting the beneficial effects of having access to better quality or cheaper inputs. For services sectors, it is more the sales of intermediates (forward participation) that is associated with productivity gains, in line with the traditional role of services in foreign trade as providing inputs to other activities. Looking by partner country, GVC participation with higher productivity countries is particularly productivity enhancing. We also find that GVC integration spurs greater domestic innovation activity.
    Keywords: global value chains, innovation, productivity
    JEL: F14 D24 O30
    Date: 2019–10–04
  3. By: Nelson Lind (Emory University); Natalia Ramondo (UCSD)
    Abstract: This paper develops a model of economic growth and trade in which countries innovate ideas that diffuse across the globe. This model dynamically generates max-stable multivariate Frechet productivity distributions and implies a mixed-CES import demand system. This demand system allows for rich substitution patterns in trade flows that arise from spatial correlation in technology. In the special case of a pure innovation model where countries do not share ideas, productivities are independent across space, and the demand system is CES. As a consequence, departures from CES reflect how knowledge diffusion generates technological similarity. In the general case with diffusion, high innovation countries tend to have dissimilar technology and their goods are less substitutable. These theoretical results provide a direct connection between estimable substitution patterns and the underlying dynamics of innovation and knowledge diffusion.
    Date: 2019
  4. By: shah, Muhammad ibrahim
    Abstract: Innovation is at the core of fourth industrial revolution which is already under way. Both Sustainable growth and development depend on technological innovation. Traditional economic models/theories are now undermined because of new technologies like AI, automation,3D printing, robotics etc. Lack of innovation creates major socio-economic problems such as inequality, unemployment, poverty and many more. Therefore, in this competitive world, a country needs innovative people with innovative ideas to go forward. The aim of this study is to explain and critically examine the determinants of technological innovation across 5 South Asian countries using yearly data for 1980-2015 period. This paper employs several econometric techniques such as Cross sectional dependence to see if shocks that occur in one country affect another, Panel unit root test to check the stationary of the data and Panel Cointegration test to check long run relationship among the variables. This study also applies Fully Modified OLS to estimate long run coefficients and Dumitrescu and Hurlin panel causality test (2012) to see the causality between the variables. The findings suggest that democracy and human capital are negatively related to innovation, contrary to popular belief. The analysis also reveals that trade openness positively and significantly affects innovation and there exists a nonlinear, in particular an inverted U shaped relationship between innovation and financial development in South Asia. Findings from the Causality test reveals that there is bidirectional causality between total patent application and trade openness and also between financial development and human capital. This study, therefore, has several policy implications for South Asian countries.
    Keywords: Innovation; South Asia; Cross sectional dependence; FMOLS; Causality
    JEL: C01 C23 O31 O53 R11
    Date: 2019–08–19
  5. By: Michael Peters (Yale University); Conor Walsh (Yale University)
    Abstract: A growing body of empirical research highlights substantial changes in the US economy during the last three decades. Business dynamism – namely job reallocation, firm entry and creative destruction – is declining. Market power, as measured by markups and industry concentration, seems to be on the rise. Aggregate productivity growth is sluggish. We show that declines in the rate of growth of the labor force can qualitatively account for all of these features in a standard model of firm-dynamics. Despite its richness we can characterize the link between population growth and dynamism, markups and growth analytically. When we calibrate the model to the universe of U.S. Census data, the labor force channel can explain a large fraction of the aggregate trends.
    Date: 2019
  6. By: Helene Dernis (OECD); Petros Gkotsis (European Commission - JRC); Nicola Grassano (European Commission - JRC); Shohei Nakazato (OECD); Mariagrazia Squicciarini (OECD); Brigitte van Beuzekom (OECD); Antonio Vezzani
    Abstract: This report brings together data on patents, scientific publications, trademarks and designs of the world’s top corporate R&D investors to shed some light on the role they play in shaping the future of technologies and AI. As for the two previous editions, the present report is the product of a collaborative effort of the JRC of the European Commission and the OECD, two organisations committed to provide high quality open data and up-to-date indicators and analysis. The audience this report wants to reach is quite diverse: from the scientific community to the industry representatives, from practitioners to policy makers. Its scope is to be a useful source of analysis and data for all those interested in getting an understanding of the scientific and technological activities of key industrial players, particularly in the field of AI. The data underlying the analysis presented are publicly available for all those who want to use them for further analysis.
    Keywords: R&D investment, Artificial Intelligence, Intellectual Property, Patents, Trademarks,Scientific publications
    Date: 2019–09
  7. By: Sara Amoroso (Joint Research Centre, European Commission); Simone Vannuccini (Science Policy Research Unit (SPRU), University of Sussex Business School, University of Sussex)
    Abstract: The participation of top R&D players to publicly funded research collaborations is a common yet unexplored phenomenon.If,on the one hand,including top R&D firms creates opportunities for knowledge spillovers and increases the chance for a project to be funded, on the other hand, the uneven nature of such partnerships and the asymmetry in knowledge appropriation capabilities could hinder the overall performance of such collaborations. In this paper, we study the role of top R&D investors in the performance of publicly funded R&D consortia (in terms of number of patents and publications). Using a unique data set that matches informationon R&D collaborative projects and proposals with data on international top R&D firms, we find that indeed teaming up with leading R&D firms increases the probability to obtain funds. However,the participation of such R&D leaders hinders the innovative performance of the funded projects, both in terms of patents and publications. In light of this evidence, the benefits of mobilizing top R&D players should be carefully leveraged in the evaluation and design of innovation policies aimed at R&D collaboration and technology diffusion.
    Keywords: Collaboration; publicfunding; innovationperformance; appropriability; top R&D investor
    JEL: L24 L25 O33
    Date: 2019–09
  8. By: Ziesemer, Thomas (UNU-MERIT, and SBE, Maastricht University)
    Abstract: This literature review shows that a majority of studies finds complementarity of R&D subsidies and tax credits with private R&D expenditures. A non-negligible minority finds incomplete crowding out. Full crowding out is found only for small parts of the respective samples or small sub-sectors of the economy under consideration. Education R&D and publicly performed R&D stimulate private R&D according to a small literature. We focus on the exceptions from these dominant results. The controversies concern firm size, interaction of policy instruments, and effectiveness of parts of publicly performed R&D. There are important suggestions for future research derived from our literature review: (i) use of dynamic models with adequate time lags, (ii) explaining effects of country and firm heterogeneity.
    Keywords: Research & development, business R&D, subsidies, public R&D
    JEL: H25 O38
    Date: 2019–09–24
  9. By: Andrea, Bastianin; Chiara F., Del Bo
    Abstract: Procurement from Big Science Centers (BSC) yields a variety of spillover effects that can ultimately have growth enhancing consequences for their partner countries. We study the determinants of procurement for the biggest research infrastructure ever built: the Large Hadron Collider (LHC) at CERN. Using a unique cross-section database of firms that have registered to become industrial partners of the LHC program, we estimate the determinants for potential suppliers of receiving an order from CERN. We compare the relative weight of firms’ technological features and CERN’s procurement rules aimed at securing a juste retour for its Member States. Our results point to a strong impact of technological factors, while also highlighting the importance of political constraints related with CERN’s procurement rules as well as the presence of a home bias. Since the constraints related with the achievement of a juste retour affect–directly or indirectly–the procurement policy of many European BSCs, our results have policy implications that go beyond the CERN case study.
    Keywords: big science; procurement; innovation; hi-tech; CERN.
    JEL: C21 C25 H57 O32 O38
    Date: 2019–05–21
  10. By: Albert Bravo-Biosca
    Abstract: Experimental approaches are increasingly being adopted across many policy fields, but innovation policy has been lagging. This paper reviews the case for policy experimentation in this field, describes the different types of experiments that can be undertaken, discusses some of the unique challenges to the use of experimental approaches in innovation policy, and summarizes some of the emerging lessons, with a focus on randomized trials. The paper concludes describing how at the Innovation Growth Lab we have been working with governments across the OECD to help them overcome the barriers to policy experimentation in order to make their policies more impactful.
    JEL: C93 L26 O25 O38
    Date: 2019–09

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