nep-ino New Economics Papers
on Innovation
Issue of 2021‒05‒10
seven papers chosen by
Uwe Cantner
University of Jena

  1. Institutions and the Productivity Challenge for European Regions By Ganau, Roberto; Rodríguez-Pose, Andrés
  2. Innovation and Trade Policy in a Globalized World By Akcigit, Ufuk; Ates, Sina T.; Impullitti, Giammario
  3. On Immigration and Native Entrepreneurship By Duleep, Harriet Orcutt; Jaeger, David A.; McHenry, Peter
  4. Exploring Synergies between EU Cohesion Policy and Horizon 2020 Funding across European Regions: An analysis of regional funding concentration on key enabling technologies and societal grand challenges By Julia Bachtroegler-Unger; Mathieu Doussineau
  5. The Smart Specialisation Policy Experience: Perspective of National and Regional Authorities By Fatime Barbara Hegyi; Fabrizio Guzzo; Inmaculada Perianez Forte; Carlo Gianelle
  6. Technological Advance, Social Fragmentation and Welfare By Bosworth, Steven; Snower, Dennis J.
  7. Repeated collaboration of inventors across European regions By Gergõ Tóth; Zoltán Elekes; Sándor Juhász; Balázs Lengyel

  1. By: Ganau, Roberto; Rodríguez-Pose, Andrés
    Abstract: Europe has witnessed a considerable labour productivity slowdown in recent decades. Many potential explanations have been proposed to address this productivity 'puzzle'. However, how the quality of local institutions influences labour productivity has been overlooked by the literature. This paper addresses this gap by evaluating how institutional quality affects labour productivity growth and, particularly, its determinants at the regional level during the period 2003-2015. The results indicate that institutional quality influences regions' labour productivity growth both directly -as improvements in institutional quality drive productivity growth- and indirectly -as the short- and long-run returns of human capital and innovation on labour productivity growth are affected by regional variations in institutional quality.
    Keywords: Europe; Human Capital; Innovation; institutional quality; labour productivity; Physical Capital; regions
    JEL: E24 J24 O47 R11
    Date: 2021–03
  2. By: Akcigit, Ufuk; Ates, Sina T.; Impullitti, Giammario
    Abstract: What is the role of innovation policy in open economy? We address this question employ- ing a new innovation-driven growth model with two large open economies at different stages of development. We examine the implications of the U.S. Research and Experimentation Tax Credit, introduced in 1981, and alternative protectionist policies. Key findings are: First, the tax credit generates substantial gains over medium and long horizons. Second, protectionist measures generate large dynamic losses by distorting the firms' innovation incentives. Third, the optimal R&D subsidy decreases in trade openness. Fourth, the optimal unilateral import tariff is zero for all policy horizons.
    Keywords: economic growth; innovation policy; Open economy; trade policy
    JEL: F13 F43 F60 O40
    Date: 2021–02
  3. By: Duleep, Harriet Orcutt; Jaeger, David A.; McHenry, Peter
    Abstract: We present a novel theory that immigrants facilitate innovation and entrepreneurship by being willing and able to invest in new skills. Immigrants whose human capital is not immediately transferable to the host country face lower opportunity costs of investing in new skills or methods and will be more flexible in their human capital investments than observationally equivalent natives. Areas with large numbers of immigrants may therefore lead to more entrepreneurship and innovation, even among natives. We provide empirical evidence from the United States that is consistent with the theory's predictions.
    Keywords: entrepreneurship; Human Capital; Immigration; Innovation
    JEL: J15 J24 J39 J61 L26
    Date: 2021–03
  4. By: Julia Bachtroegler-Unger (Österreichisches Institut für Wirtschaftsforschung (WIFO),Vienna, Austria); Mathieu Doussineau (European Commission - JRC)
    Abstract: Over the course of the 2014-2020 period, the European Union has invested more than €125bn into support to research and innovation through two main channels: the excellence-based Horizon 2020 programme and its cohesion policy implemented through the European Structural and investment funds (ESIF) and in particular the European Regional Development fund (ERDF). While projects funded by ESIF are selected in the context of place-based operational programmes and smart specialisation strategies (S3), Horizon 2020 grants are assigned based on the quality of the project proposals and consortia without any geographical criteria. A concentration of R&I funding from both funding schemes in the same technological or policy area could point to the creation of a synergy between EU funding as suggested by the concept of smart specialisation and encouraged by the European Commission. This report uses project data to analyse the regional distribution of Horizon 2020 and ESIF funding among key enabling technologies and societal grand challenges and to map potential synergies between different EU funding policies.
    Keywords: ERDF, ESIF, Cohesion policies, database, Horizon 2020
    JEL: O30 O38 O32
    Date: 2021–04
  5. By: Fatime Barbara Hegyi (European Commission - JRC); Fabrizio Guzzo (European Commission - JRC); Inmaculada Perianez Forte (European Commission - JRC); Carlo Gianelle (European Commission - JRC)
    Abstract: This publication presents the results of a survey, launched in 2020 as part of a research project performed by the Smart Specialisation platform to gain new insights on the Smart Specialisation (S3) policy experience across the European Union (EU). The survey aimed at gathering the views and reflections of S3 implementing authorities on their policy experience. The questionnaire addressed the main tenets of the Smart Specialisation policy concept and consisted of four sections: implementation, governance, Entrepreneurial Discovery Process (EDP) and monitoring and evaluation. Survey results provides evidence on the state of implementation, challenges and critical aspects as well as some of the results achieved by this policy experiment in view of the new Cohesion Policy 2021-2027. Overall, we can observe that most strategies are implemented according to the original plans. Nevertheless, the situation varies considerably across categories of territories, with less developed regions exhibiting a poorer implementation performance. Smart Specialisation has supported the adoption and diffusion of more inclusive forms of governance in innovation policy across the EU. Despite the general increase in pressure for coordination and the changes introduced by this policy experiment, the effectiveness of inter-government coordination mechanisms is still considered weak by many national and regional authorities. Clearly, there is room for further improvements in this area. More efforts are also needed in relation to the skills and resources to perform the policy functions of the management body. Overall, the quality of the contribution of different stakeholders to the entrepreneurial discovery process is considered adequate by the public authorities responsible for the management of the strategy. Relevant partners are considered to have high technical/specialist skills, while their capacities to participate in policy decision-making processes are generally lower. In person meetings are the preferred options to engage stakeholders. This is not surprising, given the potential these meetings offer for deeper interaction. Online platforms appear less popular. However, considered the accelerated learning on virtual forms of engagement that is taking place with the COVID-19 pandemic, the perception on the use of online platforms is likely to change. Finally, survey results show that most of the strategies have a system of result indicators in place. However, the capacity of these indicators to monitor strategy progress is often inadequate. Lack of adequate and timely data is another major critical issue of the S3 monitoring systems, while the integration of the findings of the monitoring and evaluation systems into the next programming period is present in just over 40% of the cases.
    Keywords: Smart Specialisation, monitoring, evaluation, assessment, policy implementation, policy evaluation, governance, entrepreneurial discovery process, leadership
    Date: 2021–04
  6. By: Bosworth, Steven; Snower, Dennis J.
    Abstract: This paper models the welfare consequences of social fragmentation arising from technological advance. We start from the premise that technological progress falls primarily on market-traded commodities rather than prosocial relationships, since the latter intrinsically require the expenditure of time and thus are less amenable to productivity increases. Since prosocial relationships require individuals to identify with others in their social group whereas marketable commodities are commonly the objects of social status comparisons, a tradeoff arises between in-group affliation and inter-group status comparisons. People consequently narrow the bounds of their social groups, reducing their prosocial relationships and extending their status-seeking activities. As prosocial relationships generate positive externalities whereas status-seeking activities generate negative preference externalities, technological advance may lead to a particular type of "decoupling" of social welfare from material prosperity. Once the share of status goods in total production exceeds a crucial threshold, technological advance is shown to be welfare-reducing.
    Keywords: Bowling Alone; Conspicuous consumption; decoupling; growth; social fragmentation
    JEL: D63 D69 D71 E71 I39 O33 Z10
    Date: 2021–01
  7. By: Gergõ Tóth (Agglomeration and Social Networks Lendület Research Group, Centre for Economic-and Regional Studies, Budapest, Hungary and Spatial Dynamics Lab, University College Dublin, Dublin, Ireland); Zoltán Elekes (Agglomeration and Social Networks Research Group, Centre for Economic and Regional Studiesand Centre for Regional Science at Umea University (CERUM), Umea University, 90187 Umea, Sweden); Sándor Juhász (NETI Lab, Corvinus Institute for Advanced Studies, Budapest Corvinus University, Budapest, Hungary); Balázs Lengyel (Agglomeration and Social Networks Lendület Research Group, Centre for Economic-and Regional Studies, Budapest, Hungary;International Business School Budapest, Budapest, Hungaryand NETI Lab, Corvinus Institute for Advanced Studies, Budapest Corvinus University, Budapest, Hungary)
    Abstract: This paper explores the spatial patterns and underlying determinants of repeated inventor collaboration across European NUTS 3 regions. It is found that only a small fraction of co-inventor linkages across regions are repeated, while community detection reveals that these collaborations are clustered in geographical space more intensively compared with collaboration in general. Additional results from gravity modelling indicate that links in the inter-regional co-patenting network emerge mainly through the triadic collaboration of regions, while geographical proximity becomes the most influential factor for repeating co-inventor ties. In addition to that, the combination of technological similarity and shared third partner regions offer a premium for the likelihood of repeating collaboration, but only when geographical proximity is present as an enabler.
    Keywords: collaborative knowledge production; inter-regional collaboration; co-inventor network; repeated collaboration; European Research Area; gravity model
    JEL: D85 O31 O43 O52 R11 R58
    Date: 2021–03

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