nep-ino New Economics Papers
on Innovation
Issue of 2019‒07‒22
ten papers chosen by
Uwe Cantner
University of Jena

  1. How are digital technologies changing innovation?: Evidence from agriculture, the automotive industry and retail By Caroline Paunov; Sandra Planes-Satorra
  2. Standing on the shoulders of science By Schnitzer, Monika; Watzinger, Martin
  3. A Toolkit of Policies to Promote Innovation By Nicholas Bloom; John Van Reenen; Heidi Williams
  4. The diffusion of public eServices in European cities By Alessandro Cepparulo; Antonello Zanfei
  5. Skill-biased technological change, endogenous labor supply, and the skill premium By Knoblach, Michael
  6. Youth Drain, Entrepreneurship and Innovation By Massimo Anelli; Gaetano Basso; Giuseppe Ippedico; Giovanni Peri
  7. Smart Specialisation from Concept to Practice: A Preliminary Assessment By Carlo Gianelle; Fabrizio Guzzo; Krzysztof Mieszkowski
  8. Will this time be different? A review of the literature on the Impact of Artificial Intelligence on Employment, Incomes and Growth By Bertin Martens; Songül Tolan
  9. Technology and employment in a vertically connected economy: a model and an empirical test By Giovanni Dosi; Mariacristina Piva; Maria Enrica Virgillito; Marco Vivarelli
  10. The role of distance and social networks in the geography of crowdfunding: evidence from France By Sylvain Dejean

  1. By: Caroline Paunov; Sandra Planes-Satorra
    Abstract: Digital technologies impact innovation in all sectors of the economy, including traditional ones such as agriculture, the automotive industry, and retail. Similar trends across sectors include that the Internet of Things and data are becoming key inputs for innovation, innovation cycles are accelerating, services innovation is gaining importance and collaborative innovation matters more. Sector-specific dynamics are driven by differences in opportunities such technologies offer for innovation in products, processes and business models, as well as differences in the types of data needed for innovation and the conditions for digital technology adoption. The analysis calls for revisiting innovation policy mixes to ensure these remain effective and address emerging challenges. A sectoral approach is needed when designing innovation policies in some domains, especially regarding data access and digital technology adoption policies. The current focus of innovation policies on boosting R&D to meet R&D intensity targets also requires scrutiny.
    Date: 2019–07–18
  2. By: Schnitzer, Monika; Watzinger, Martin
    Abstract: The goal of science is to advance knowledge, yet little is known about its value for marketplace inventions. While important breakthrough technologies could not have been developed without scientific background, skeptics argue that this is the exception rather than the rule, questioning the usefulness of basic research for private sector innovations and the effectiveness of the knowledge transfer from university to industry. We analyze the universe of U.S. patents to establish three new facts about the relationship between science and the value of inventions. First, we show that a patent that directly builds on science is on average 2.9 million U.S. dollars more valuable than a patent in the same technology that is unrelated to science. Based on the analysis of the patent text, we show second that the novelty of patents predicts their value, and third that science-intensive patents are more novel. This documents that science introduces new concepts that are valuable for marketplace inventions. Our study informs the debate on the merits of science for corporate innovation and the origins of breakthrough inventions.
    JEL: O30 O31 O33 O34
    Date: 2019–05
  3. By: Nicholas Bloom; John Van Reenen; Heidi Williams
    Abstract: Economic theory suggests that market economies are likely to under-provide innovation due to the public good nature of knowledge. Empirical evidence from the US and other advanced economies supports this idea. We summarize the pros and cons of different policy instruments for promoting innovation and provide a basic "toolkit" describing which policies are most effective, based on our reading of the evidence. In the short-run, R&D tax credits or direct public funding seem the most productive, but in the longer-run increasing the supply of human capital (e.g. relaxing immigration rules or expanding university STEM admissions) are likely more effective.
    Keywords: Innovation, R&D, intellectual property, tax, competition
    JEL: O31 O32
    Date: 2019–07
  4. By: Alessandro Cepparulo (Department of Economics, Society & Politics, Universit? di Urbino Carlo Bo); Antonello Zanfei (Department of Economics, Society & Politics, Universit? di Urbino Carlo Bo)
    Abstract: Using a novel dataset on the diffusion of public eServices at the city level in EU 15, this paper contributes to extant empirical literature in three ways. First, it extends the coverage of public eServices beyond eGovernment, investigating four service categories: Infomobility, eProcurement, eGovernment and eHealth. Second, it provides information for both a cross-country and cross-municipality comparison. Third, on the methodological side, it also extends the literature on composite indicators at a municipal level. Cities exhibiting the highest diffusion of public eServices are found to be medium-large, highly endowed with well-educated human capital, and characterised by a lively industrial atmosphere favoured by a reasonable number and variety of production and service activities. The relative performance of the European cities helps identify plausible directions to be taken for policies aimed at favoring the diffusion of public service innovation in Europe.
    Keywords: Innovation, eGovernment, Public eServices, Information Policy, ICT.
    JEL: O33 O38 L96 H83
    Date: 2019
  5. By: Knoblach, Michael
    Abstract: The evolution of the U.S. skill premium over the past century has been characterized by a U-shaped pattern. The previous literature has attributed this observation mainly to the existence of exogenous, unexpected technological shocks or changes in institutional factors. In contrast, this paper demonstrates that a U-shaped evolution of the skill premium can also be obtained using a simple two-sector growth model that comprises both variants of skill-biased technological change (SBTC): technological change (TC) that is favorable to high-skilled labor and capital-skill complementarity (CSC). Within this framework, we derive the conditions necessary to achieve a non-monotonic evolution of relative wages and analyze the dynamics of such a case. We show that in the short run for various parameter constellations an educational, a relative substitutability, and a factor intensity effect can induce a decrease in the skill premium despite moderate growth in the relative productivity of high-skilled labor. In the long run, as the difference in labor productivity increases, the skill premium also rises. To underpin our theoretical results, we conduct a comprehensive simulation study.
    Keywords: Skill-Augmenting Technological Change,Capital-Skill Complementarity,Skill Premium,Neoclassical Growth Model
    JEL: E24 J24 J31 O33 O41
    Date: 2019
  6. By: Massimo Anelli; Gaetano Basso; Giuseppe Ippedico; Giovanni Peri
    Abstract: Migration outflows, especially of young people, may deprive an economy of entrepreneurial energy and innovative ideas. We exploit exogenous variation in emigration from Italian local labor markets to show that between 2008 and 2015 larger emigration flows reduced firm creation. The decline affected firms owned by young people and innovative industries. We estimate that for every 1,000 emigrants, 10 fewer young-owned firms were created over the whole period. A simple accounting exercise shows that about 60 percent of the effect is generated simply by the loss of young people; the remaining 40 percent is due to a combination of selection of emigrants among highly entrepreneurial people, negative spillovers on the entrepreneurship rate of locals, and negative local firm multiplier effect.
    JEL: J61 M13 O3
    Date: 2019–07
  7. By: Carlo Gianelle (European Commission - JRC); Fabrizio Guzzo (European Commission - JRC); Krzysztof Mieszkowski (European Commission - JRC)
    Abstract: This study assesses how and to what extent the principles characterising the Smart Specialisation approach are actually translated in policy implementation, by examining three of its complementary aspects: the nature of the priority areas for policy intervention, the mechanisms for project selection, and the type of policy measures. The results shows that regions and countries tend to circumvent the selective approach of Smart Specialisation. Priority areas broadly defined, loose alignment of policy instruments with priorities and the scarce customisation of policy measures to the specific innovation needs of the identified priorities are the tangible signs of this circumvention process. We advance the hypothesis that this could be the result of lobbying activities, higher political return from widespread support measures, risk-aversion, and lack of adequate institutional and administrative capacity. An additional explanation may lie in the incentive structure established at European Union level which did not fully support the intervention logic of Smart Specialisation. To assess the effects of Smart Specialisation, we suggest focusing on interventions that (i) address priorities consistently defined, (ii) apply policy measures selectively to those priorities, (iii) design policy measures around the specificities of each priority.
    Keywords: Regional innovation policy; Smart Specialisation; Selective intervention logic; policy priorities
    JEL: O25 O30 R12 R58
    Date: 2019–07
  8. By: Bertin Martens (European Commission – JRC - IPTS); Songül Tolan (European Commission – JRC)
    Abstract: There is a long-standing economic research literature on the impact of technological innovation and automation in general on employment and economic growth. Traditional economic models trade off a negative displacement or substitution effect against a positive complementarity effect on employment. Economic history since the industrial revolution as strongly supports the view that the net effect on employment and incomes is positive though recent evidence points to a declining labour share in total income. There are concerns that with artificial intelligence (AI) "this time may be different". The state-of-the-art task-based model creates an environment where humans and machines compete for the completion of tasks. It emphasizes the labour substitution effects of automation. This has been tested on robots data, with mixed results. However, the economic characteristics of rival robots are not comparable with non-rival and scalable AI algorithms that may constitute a general purpose technology and may accelerate the pace of innovation in itself. These characteristics give a hint that this time might indeed be different. However, there is as yet very little empirical evidence that relates AI or Machine Learning (ML) to employment and incomes. General growth models can only present a wide range of highly diverging and hypothetical scenarios, from growth implosion to an optimistic future with growth acceleration. Even extreme scenarios of displacement of men by machines offer hope for an overall wealthier economic future. The literature is clearer on the negative implications that automation may have for income equality. Redistributive policies to counteract this trend will have to incorporate behavioural responses to such policies. We conclude that that there are some elements that suggest that the nature of AI/ML is different from previous technological change but there is no empirical evidence yet to underpin this view.
    Keywords: labour markets, employment, technological change, task-based model, artificial intelligence, income distribution,
    JEL: J62 O33
    Date: 2018–08
  9. By: Giovanni Dosi (Institute of Economics, Scuola Superiore Sant’Anna, Pisa); Mariacristina Piva (DISCE, Università Cattolica); Maria Enrica Virgillito (DISCE, Università Cattolica); Marco Vivarelli (DISCE, Università Cattolica - UNU-MERIT, Maastricht, The Netherlands and IZA, Bonn, Germany)
    Abstract: This paper addresses, both theoretically and empirically, the sectoral patterns of job creation and job destruction in order to distinguish the alternative effects of embodied vs disembodied technological change operating into a vertically connected economy. Disembodied technological change turns out to positively affect employment dynamics in the “upstream’’ sectors, while expansionary investment does so in the “downstream’’ industries. Conversely, the replacement of obsolete capital vintages tends to exert a negative impact on labour demand, although this effect turns out to be statistically less robust.
    Keywords: Innovation, disembodied and capital-embodied technological change, employment, job-creation, job-destruction, sectoral interdependencies
    JEL: O14 O31 O33
    Date: 2019–06
  10. By: Sylvain Dejean (CE.RE.GE - CEntre de REcherche en GEstion - ULR - Université de La Rochelle - IAE Poitiers - Institut d'Administration des Entreprises (IAE) - Poitiers - Université de Poitiers - Université de Poitiers)
    Abstract: This article aims to estimate the cost of distance in the geographical flow of crowdfunding, and to show how social ties between the 94 French metropolitan regions shape the geography of funding. Our analysis draws upon a unique database provided by the French leader in rewards-based crowdfunding. The main result is that the elasticity of distance remains important (around 0.5), and that social ties between regions determine the flow of funding. Doubling the number of immigrants in a region increases the number of investments by 24% and reduces the impact of distance.
    Keywords: Crowdfunding,economic geography,social networks,gravity
    Date: 2019–06–19

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