nep-ino New Economics Papers
on Innovation
Issue of 2022‒08‒08
seven papers chosen by
Uwe Cantner
University of Jena

  1. Research joint ventures: The role of financial constraints By Philipp Brunner; Igor Letina; Armin Schmutzler
  2. Flow of Ideas: Economic Societies and the Rise of Useful Knowledge By Francesco Cinnirella; Erik Hornung; Julius Koschnick
  3. Accounting for the slowdown in UK innovation and productivity By Peter Goodridge; Jonathan Haskel
  4. The Exports of Knowledge Intensive Services. A Complex Metric Approach By Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio
  5. Digitalisation, Institutions and Governance, and Diffusion: Mechanisms and Evidence By Baccianti, Claudio; Labhard, Vincent; Lehtimäki, Jonne
  6. Creative-entrepreneurs and new venture performance a study of the creative class at the firm-level. By Marcos Segantini; Lori A. Dickes
  7. Anatomy of Green Specialisation: Evidence from EU Production Data, 1995-2015 By Francesco Vona; Francesco Bontadini

  1. By: Philipp Brunner; Igor Letina; Armin Schmutzler
    Abstract: This paper provides a novel theory of research joint ventures for financially constrained firms. When firms choose R&D portfolios, an RJV can help to coordinate research efforts, reducing investments in duplicate projects. This can free up resources, increase the variety of pursued projects and thereby increase the probability of discovering the innovation. RJVs improve innovation outcomes when market competition is weak and external financing conditions are bad. An RJV may increase the innovation probability and nevertheless lower total R&D costs. RJVs that increase innovation tend to be profitable, but innovation-reducing RJVs also exist. Finally, we compare RJVs to innovation-enhancing mergers.
    Keywords: Innovation, research joint ventures, financial constraints, mergers, intensity of competition, licensing
    JEL: L13 L24 O31
    Date: 2022–07
  2. By: Francesco Cinnirella (University of Bergamo); Erik Hornung (University of Cologne); Julius Koschnick (London School of Economics)
    Abstract: Economic societies emerged during the late eighteenth-century. We argue that these institutions reduced the costs of accessing useful knowledge by adopting, producing, and diffusing new ideas. Combining location information for the universe of 3,300 members across active economic soci-eties in Germany with those of patent holders and World’s Fair exhibitors, we show that regions with more members were more innovative in the late nineteenth-century. This long-lasting effect of societies arguably arose through agglomeration economies and localized knowledge spillovers. To support this claim, we provide evidence suggesting an immediate increase in manufacturing, an earlier establishment of vocational schools, and a higher density of highly skilled mechanical workers by mid-nineteenth century in regions with more members. We also show that regions with members from the same society had higher similarity in patenting, suggesting that social networks facilitated spatial knowledge diffusion and, to some extent, shaped the geography of innovation.
    Keywords: Economic Societies, Useful Knowledge, Knowledge Diffusion, Innovation, Social Networks
    JEL: N33 O33 O31 O43
    Date: 2022–07
  3. By: Peter Goodridge (x The Productivity Institute, Alliance Manchester Business School); Jonathan Haskel (Bank of England; Imperial College Business School; CEPR and IZA)
    Keywords: productivity, growth, slowdown, innovation, knowledge, intangibles, investment, capital, TFP
    Date: 2022–06
  4. By: Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio
    Abstract: In the following article, the value of the "Knowledge Intensive Services Exports in Europe" in 36 European countries is estimated. The data were analyzed through a set of econometric models or: Poled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. The results show that “Knowledge Intensive Services Exports” is negatively associated, among others, with "Buyer Sophistication", "Government Procurement of Advanced Technology Products", and positively associated with the following variables i.e. "Innovation Index", "Sales Impacts" and "Total Entrepreneurial Activity". Then a clusterization with k-Means algorithm was made with the Elbow method. The results show the presence of 3 clusters. A network analysis was later built and 4 complex network structures and three structures with simplified networks were detected. To predict the future trend of the variable, a comparison was made with eight different machine learning algorithms. The results show that prediction with Augmented Data-AD is more efficient than prediction with Original Data-AD with a reduction of the mean of statistical errors equal to 55,94%.
    Keywords: Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation.
    JEL: O3 O30 O31 O32 O33 O34
    Date: 2022–06–11
  5. By: Baccianti, Claudio; Labhard, Vincent; Lehtimäki, Jonne
    Abstract: Digitalisation can be described as a sequence of technology and supply shocks which affect the economy through employment and labour markets, productivity and output, and competition and market structure. This paper focuses on how digitalisation - the process of diffusion of digital technologies - is affected by institutions and governance. It discusses a number of theoretical mechanisms and empirical evidence for different sets of European and other countries. The results indicate that a higher quality of institutions is usually associated with both a greater speed of diffusion and a greater spread of digital technologies. The results also suggest that there are large, policy-relevant differences in the diffusion process depending on the level of development as well as the state of technological change of a country. JEL Classification: E02, O11, O31, O33, O57
    Keywords: adoption, economy, estimates, panel, technology
    Date: 2022–07
  6. By: Marcos Segantini (Universidad ORT Uruguay. Facultad de Administración y Ciencias Sociales. Departmento de Economía); Lori A. Dickes (Clemson University)
    Abstract: Human capital has been a central topic since the beginning of entrepreneurship as a field of academic research. This paper analyzes the association of the human capital level of entrepreneurial teams on the performance of nascent projects by applying a relatively new theory of human capital. The creative class theory, widely used in the research of entrepreneurship at the regional level, is applied here for its first time at the firm level. This article's findings indicate similar results at the firm level to those found at the regional level. More creative-entrepreneur-owned startups are strongly associated with job creation, and to less extent, with projects' survival. As in regional studies, the results of this research also question the classic measures of human capital focused on entrepreneurs' formal education, but now at the firm level.
    Keywords: entrepreneurship, human capital, creative class.
    Date: 2020–12
  7. By: Francesco Vona (University of Milan, Department of Environmental Science and Policy, Fondazione Eni Enrico Mattei (FEEM) and OFCE Sciences-Po); Francesco Bontadini (OFCE Sciences-Po, LUISS Guido Carli University and SPRU – University of Sussex)
    Abstract: We study green specialisation across EU countries and detailed 4-digit industrial sectors over the period of 1995-2015 by harmonizing product-level data (PRODCOM). We propose a new list of green goods that refines lists proposed by international organizations by excluding goods with double usage. Our analysis reveals important structural characteristics of green specialisation in the manufacturing sector. First, green production is highly concentrated, with 13 out of 119 4-digit industries, which are high-tech and account for nearly 95% of the total. Second, green and polluting productions do not occur in the same sectors, and countries specialise in either green or brown sectors. Third, our econometric analysis identifies three key drivers of green specialisation: (i) first-mover advantage and high persistence of green specialisation, (ii) complementarity with non-green capabilities and (iii) the degree of diversification of green capabilities. Importantly, once we control for these drivers, environmental policies are not anymore positively associated with green specialisation.
    Keywords: Green goods, green specialisation, environmental policies, complementarity, path dependency
    JEL: Q55 L60 O44
    Date: 2022–06

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