nep-ino New Economics Papers
on Innovation
Issue of 2019‒02‒25
twelve papers chosen by
Uwe Cantner
University of Jena

  1. Immigrant Entrepreneurs and Innovation in the U.S. High-Tech Sector By J. David Brown; John S. Earle; Mee Jung Kim; Kyung Min Lee
  2. Impact evaluation of innovation policy in Brazil By Rocha, C.
  3. The Internationalization of R&D By Ali-Yrkkö, Jyrki; Pajarinen, Mika
  4. Innovation, Automation, and Inequality: Policy Challenges in the Race against the Machine By Prettner, Klaus; Strulik, Holger
  5. The impact of the French policy mix on business R&D: How geography matters By Benjamin Montmartin; Marcos Herrera; Nadine Massard
  6. Valuing Product Innovation: Genetically Engineered Varieties in U.S. Corn and Soybeans By Ciliberto, Federico; Moschini, GianCarlo; Perry, Edward
  7. How fast is this novel technology going to be a hit? By Pezzoni, Michele; Veugelers, Reinhilde; Visentin, Fabiana
  8. Structural transformation in Africa: New technologies, resurgent entrepreneurship and the revival of manufacturing By Naude, Wim
  9. Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter? By Gries, Thomas; Naude, Wim
  10. Cooperation or non-cooperation in R&D: how should research be funded? By Marie-Laure Cabon-Dhersin; Romain Gibert
  11. A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda By Scheller, Fabian; Johanning, Simon; Bruckner, Thomas
  12. From "destructive creation" to "creative destruction": Rethinking Science, Technology and innovation in a global context By Soete, Luc

  1. By: J. David Brown; John S. Earle; Mee Jung Kim; Kyung Min Lee
    Abstract: We estimate differences in innovation behavior between foreign versus U.S.-born entrepreneurs in high-tech industries. Our data come from the Annual Survey of Entrepreneurs, a random sample of firms with detailed information on owner characteristics and innovation activities. We find uniformly higher rates of innovation in immigrant-owned firms for 15 of 16 different innovation measures; the only exception is for copyright/trademark. The immigrant advantage holds for older firms as well as for recent start-ups and for every level of the entrepreneur’s education. The size of the estimated immigrant-native differences in product and process innovation activities rises with detailed controls for demographic and human capital characteristics but falls for R&D and patenting. Controlling for finance, motivations, and industry reduces all coefficients, but for most measures and specifications immigrants are estimated to have a sizable advantage in innovation.
    JEL: F22 J15 J6 L26 O3 O31
    Date: 2019–02
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:25565&r=all
  2. By: Rocha, C.
    Abstract: This paper aims to assess the innovation policy in Brazil after the edition of the innovation law, in 2004, and the fiscal subsidies to innovation law, in 2005. We use data from the Brazilian Innovation Survey and from the Annual Industrial Survey to measure the effect of the use of policy instruments on private R&D disbursements and on productivity. The report finds a positive effect of the innovation policy on private R&D when all instruments are pooled together, that is, innovation policy resources may be viewed as complementary to private resources and may be viewed as successful in fostering innovative effort. When separate instruments are analyzed, we find that direct intervention instruments such as credit for R&D investments and economic grants work very well. The effect of fiscal subsidies is not straightforward, however. It seems to increase the probability to perform R&D disbursements but does not have effect on the intensity of these disbursements. Other instruments such as credit for the acquisition of equipment and machinery and credit for the enhancement of university-industry linkages do not perform well. Policy instruments had an overall positive impact on labor productivity. Most instruments have maintained a positive and significant impact on productivity over all equations, with the sole exception of risk capital.
    Keywords: Economía, Finanzas, Innovación, Investigación socioeconómica,
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:dbl:dblwop:1339&r=all
  3. By: Ali-Yrkkö, Jyrki; Pajarinen, Mika
    Abstract: Abstract The aim of this paper is to broaden the knowledge concerning the development of Finnish firms’ innovation activities. The results show that during 2008–2017 the share of overseas R&D has risen. Currently, 14–25% of Finnish firms’ total R&D are conducted overseas. If Nokia is taken into account, the share of overseas R&D rises to 53–65%. Furthermore, the results suggest that Finnish firms invest approximately Eur 1.8 billion in innovation activities outside the traditional R&D definition.
    Keywords: Research, Development, R&D, Company, BERD, Internationalization, Globalisation
    JEL: O31 O32
    Date: 2019–02–15
    URL: http://d.repec.org/n?u=RePEc:rif:report:88&r=all
  4. By: Prettner, Klaus; Strulik, Holger
    Abstract: We analyze the effects of R&D-driven automation on economic growth, education, and inequality when high-skilled workers are complements to machines and low-skilled workers are substitutes for machines. The model predicts that innovation-driven growth leads to an increasing population share of college graduates, increasing income and wealth inequality, and a declining labor share. We use the model to analyze the effects of redistribution. We show that it is difficult to improve income of low-skilled individuals as long as both technology and education are endogenous. This is true irrespective of whether redistribution is financed by progressive wage taxation or by a robot tax. Only when higher education is stationary, redistribution unambiguously benefits the poor. We show that education subsidies affect the economy differently depending on their mode of funding and that they may actually reduce education. Finally, we extend the model by fair wage concerns and show how automation could induce involuntary low-skilled unemployment.
    Keywords: Automation,Innovation-Driven Growth,Inequality,Wealth Concentration,Unemployment,Policy Responses
    JEL: E23 E25 O31 O33 O40
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:zbw:glodps:320&r=all
  5. By: Benjamin Montmartin (Observatoire français des conjonctures économiques); Marcos Herrera (Universidad Nacional de Salta); Nadine Massard (Université Grenoble Alpes)
    Abstract: Based on a spatial extension of an R&D investment model, this paper measures the macroeconomic impact of the French R&D policy mix on business R&D using regional data. Our measure takes into account not only the direct effect of policies but also indirect effects generated by the existence of spatial interaction between regions. Using a unique database containing information on the levels of various R&D policy instruments received by firms in French NUTS3 regions over the period 2001–2011, our estimates of a spatial Durbin model with structural breaks and fixed effects reveal the existence of a negative spatial dependence among R&D investments in regions. In this context, while a-spatial estimates would conclude that all instruments have a crowding-in effect, we show that national subsidies are the only instrument that is able to generate significant crowding-in effects. On the contrary, it seems that the design, size and spatial allocation of funds from the other instruments (tax credits, local subsidies, European subsidies) lead them to act (in the French context) as beggar-thy-neighbor policies.
    Keywords: Policy mix evaluation; R&D investment; Spatial panel; French NUTS 3 regions
    JEL: H25 O31 O38 C23
    Date: 2018–12
    URL: http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/4ji8v7q9nt9q0rsm9mqn5dqrrp&r=all
  6. By: Ciliberto, Federico; Moschini, GianCarlo; Perry, Edward
    Abstract: We develop a discrete-choice model of differentiated products for U.S. corn and soybean seed demand to study the welfare impact of genetically engineered (GE) crop varieties. Using a unique dataset spanning the period 1996-2011, we find that the welfare impact of the GE innovation is significant. In the last five years of the period analyzed, our preferred counterfactual indicates that total surplus due to GE traits was $5.18 billion per year, with seed manufacturers appropriating 56% of this surplus. The seed industry obtained more surplus from GE corn, whereas farmers received more surplus from GE soybeans.
    Date: 2019–02
    URL: http://d.repec.org/n?u=RePEc:cpr:ceprdp:13525&r=all
  7. By: Pezzoni, Michele; Veugelers, Reinhilde; Visentin, Fabiana
    Abstract: Despite the high interest of scholars in identifying successful inventions, little attention has been devoted to investigate how (fast) the novel ideas embodied in original inventions are re-used in follow-on inventions. We overcome this limitation by empirically mapping and characterizing the trajectory of novel technologies' re-use in follow-on inventions. Specifically, we consider the factors affecting the time needed for a novel technology to be legitimated as well as to reach its full technological impact. We analyze how these diffusion dynamics are affected by the antecedent characteristics of the novel technology. We characterize novel technologies as those that make new combinations with existing technological components and trace these new combinations in follow-on inventions. We find that novel technologies combining for the first time technological components which are similar and which are familiar to the inventors' community require a short time to be legitimated but show a low technological impact. In contrast, combining for the first time technological components with a science-based nature generates technologies with a long legitimation time but also high technological impact.
    Keywords: combinatorial components; Diffusion; patent data; technological novelty
    JEL: O33
    Date: 2019–01
    URL: http://d.repec.org/n?u=RePEc:cpr:ceprdp:13447&r=all
  8. By: Naude, Wim (UNU-MERIT, and Maastricht University)
    Abstract: In this paper I argue that manufacturing is still important for structural transformation in Africa. Despite failing to industrialize in the past, there may be a new window of opportunity. This is due to the convergence of new technologies of the Fourth Industrial Revolution (4IR) and a resurgence of start-up entrepreneurship. In this light I (i) show why manufacturing is vital for African economies, (ii) critically analyze the nature and impact, both in terms of opportunities and risks, of the new technologies associated with the 4IR for Africa; (iii) describe the resurgence of tech start-up entrepreneurship in Africa and (iv) call for policy support in the form of complimentary investments and regulations to allow entrepreneurs to utilize opportunities and to minimize threats. The paper show that a new narrative for African structural transformation is possible.
    Keywords: Technology, industry 4.0, entrepreneurship, development, Africa
    JEL: O33 O14 O55 L52 L26
    Date: 2018–11–30
    URL: http://d.repec.org/n?u=RePEc:unm:unumer:2018045&r=all
  9. By: Gries, Thomas (Universitat Paderborn); Naude, Wim (UNU-MERIT, and Maastricht University, RWTH Aachen University, IZA Institute of Labor Economics, Bonn.)
    Abstract: Rapid technological progress in artificial intelligence (AI) has been predicted to lead to mass unemployment, rising inequality, and higher productivity growth through automation. In this paper we critically re-assess these predictions by (i) surveying the recent literature and (ii) incorporating AI-facilitated automation into a product variety-model, frequently used in endogenous growth theory, but modified to allow for demand-side constraints. This is a novel approach, given that endogenous growth models, and including most recent work on AI in economic growth, are largely supply-driven. Our contribution is motivated by two reasons. One is that there are still only very few theoretical models of economic growth that incorporate AI, and moreover an absence of growth models with AI that takes into consideration growth constraints due to insuficient aggregate demand. A second is that the predictions of AI causing massive job losses and faster growth in productivity and GDP are at odds with reality so far: if anything, unemployment in many advanced economies is historically low. However, wage growth and productivity is stagnating and inequality is rising. Our paper provides a theoretical explanation of this in the context of rapid progress in AI.
    Keywords: Technology, artificial intelligence, productivity, labour demand, innovation, growth theory
    JEL: O47 O33 J24 E21 E25
    Date: 2018–12–12
    URL: http://d.repec.org/n?u=RePEc:unm:unumer:2018047&r=all
  10. By: Marie-Laure Cabon-Dhersin (CREAM - Centre de Recherche en Economie Appliquée à la Mondialisation - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université - IRIHS - Institut de Recherche Interdisciplinaire Homme et Société - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université); Romain Gibert (CREAM - Centre de Recherche en Economie Appliquée à la Mondialisation - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université - IRIHS - Institut de Recherche Interdisciplinaire Homme et Société - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université)
    Abstract: This article investigates two research funding policies in a cooperative and a non-cooperative R&D setting: subsidising private research (Spr) and subsidising public research (Spu). We show that R&D cooperation with subsidies (either Spr or Spu) always performs better than R&D cooperation with no subsidy. Furthermore, the Spr policy leads to better performance than the Spu approach does in terms of overall net surplus whether the rms cooperate or not in R&D. Nevertheless, comparing the two research funding policies for the same level of public spending shows that the Spu policy with R&D cooperation is in some cases more eective than the Spr policy, the latter becoming too costly for the government when spillovers are high.
    Keywords: R&D Cooperation,R&D spillovers,Knowledge public externalities,Subsidies,Public policy,H2,H4,L3,L5,03,C7
    Date: 2018–11–15
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-02006515&r=all
  11. By: Scheller, Fabian; Johanning, Simon; Bruckner, Thomas
    Abstract: Modeling the diffusion of innovations is a very challenging task, as there are various influencing factors to consider. At the same time, insights into the diffusion process can help decision makers to detect weak points of potential business models. In the literature, various models and methodologies that might tackle this problem are presented. Between these, empirically grounded agent-based modeling turned out to be one of the most promising approaches. However, the current culture is dominated by papers that fail to document critical methodological details. Thus, existing agent-based models for real-world analysis differ extensively in their design and grounding and therefore also in their predictions and conclusions. Additionally, the selection of modeling aspects seems too often be ad hoc without any defendable rationale. Concerning this matter, to draw on experiences could guide the researcher. This research paper seeks to synthesize relevant publications at the interface of empirical grounding, agent-based modeling and innovation diffusion to provide an overview of the existing body of knowledge. The major aim is to assess existing approaches regarding development procedure, entity and dynamics consideration and theoretical grounding to suggest a future research agenda. This might lead to the development of more robust models. According to the findings of this review, future work needs to focus on generic design, model coupling, research consistency, modular testing, actor involvement, behavior modeling, network foundation, and data transparency. In a subsequent step and based on the findings, a novel model approach needs to be designed and implemented.
    Keywords: Innovation diffusion models,Agent-based models,Empirically grounded models,Data driven models,Literature review
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:zbw:iirmco:012019&r=all
  12. By: Soete, Luc (UNU-MERIT)
    Abstract: There is general agreement amongst economists today that Science, Technology and Innovation (STI) have dramatically contributed to individual countries' economic growth and welfare. Another, 21st Century way of looking at the old Solow residual discussion is to observe that STI has been the core factor behind the intrinsic characteristic of capitalism to accumulate indefinitely. Doing so STI has also created the seeds of the current pattern of unsustainable global development. Once the major driving forces of countries' international, technological competitiveness are taken into account, "smart", innovation-led growth and "sustainable", green growth appear in contradiction with each other. The paper makes the case for "smart" no longer be leading in STI policy but rather "sustainability". Four priority "directions" are suggested: radical improvements in eco-productivity reducing the energy and emissions intensity of production, distribution and consumption; biomimicry as sustainable product innovation guiding principle; the use of AI and big data as "sustainable purpose technologies" assisting and complementing growth in eco-productivity and green product development and design; and finally regulatory and taxing policies addressing over-consumption, including advertising. In so far as sustainability and inclusiveness are also in contradiction with each other, there is also need for specific proactive, integrated "eco-social" STI policies. Global sustainable development will only be successful if it supported by all classes in society. While for high income classes priority can be given to increased taxation, for low income classes there is a need for a more comprehensive green new deal that should include house retrofitting and social energy tariffs making the energy transition cheap. Finally the research community itself should put full priority to exploit fully the digital substitution advantages of research networking, rather than air travel.
    Keywords: Science, Technology and Innovation, Smart Growth, Sustainable Development, Inclusiveness.
    JEL: M48 O30 O33 O38 P48
    Date: 2019–01–10
    URL: http://d.repec.org/n?u=RePEc:unm:unumer:2019001&r=all

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