nep-ino New Economics Papers
on Innovation
Issue of 2022‒02‒28
five papers chosen by
Uwe Cantner
University of Jena

  1. Agglomeration and Technological Specialization By Basheer Kalash
  2. Enterprises Providing ICT Training in Europe By Laureti, Lucio; Costantiello, Alberto; Matarrese, Marco Maria; Leogrande, Angelo
  3. Return of the Solow-paradox in AI? AI-adoption and firm productivity By Bäck, Asta; Hajikhani, Arash; Jäger, Angela; Schubert, Torben; Suominen, Arho
  4. Geography, Growth and Inequalities: Market Failures and Public Policy Implications By Benjamin Montmartin
  5. Conceptualizing market formation for transformative policy By Wouter P.C. Boon; Jakob Edler; Douglas K. R. Robinson

  1. By: Basheer Kalash (Université Côte d'Azur; GREDEG CNRS; Sciences Po, OFCE, France)
    Abstract: Notable attention has been given to the relationship between agglomeration and innovation. However, there is a lack of evidence of how agglomeration affects the type of innovation produced. This study aims to causally assess the impact of a change in agglomeration economies, via transportation improvements, on regional technological specialization. It investigates this relationship using the inauguration of the Öresund Bridge between Sweden and Denmark in 2000 as a quasi-experiment for a difference-in-difference approach. It considers the Öresund area, which consists of Copenhagen and the Swedish Skåne, as the treated regions and the other regions in Denmark and Sweden as a control group. The International Patent Classification (IPC) codes of European Patent Office (EPO) applications are employed to define technology classes for 30 NUTS-3 regions in Sweden and Denmark from 1988 to 2011. The results show that the opening of the Öresund bridge led to an increase in Skåne's highly cited patent technology classes, but no significant change in the specialization of Copenhagen. The results suggest that changes in regions' specializations are not only dependent on the quality of patent technology classes but are also region-specific.
    Keywords: Agglomeration, technological specialization, Öresund, transportation infrastructure, innovation
    JEL: O31 O33 R11
    Date: 2022–01
  2. By: Laureti, Lucio; Costantiello, Alberto; Matarrese, Marco Maria; Leogrande, Angelo
    Abstract: The determinants of enterprises providing ICT training in Europe are analyzed in this article. Data are collected from the European Innovation Scoreboard-EIS of the European Commission for 36 European countries in the period 2000-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. Results show that the number of enterprises providing ICT training in Europe is positively associate with “Innovation Index”, “Innovators”, “New Doctorate Graduates”, “Tertiary Education” and negatively associated with “Government Procurement of Advanced Technology Products”, “Human Resources”, and “Marketing or Organisational Innovators”. In adjunct a cluster analysis is performed by using k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of four clusters. Finally, we use eight different machine learning algorithms to predict the value of the enterprises providing ICT training in Europe. We found that the Simple Tree Regression is the best predictor and that the number of enterprises providing ICT training in Europe is expected to growth of the 5,02%.
    Keywords: Innovation and Invention: Processes and Incentives; Management of Technological Innovation; Technological Change: Choices and Consequences; Intellectual Property and Intellectual Capital.
    JEL: O30 O31 O32 O33 O34
    Date: 2022–01–29
  3. By: Bäck, Asta (VTT); Hajikhani, Arash (VTT); Jäger, Angela (Fraunhofer Institute for Systems and Innovation Research ISI); Schubert, Torben (CIRCLE, Lund University); Suominen, Arho (VTT)
    Abstract: AI-related technologies have become ubiquitous in many business contexts. However, to date empirical accounts of the productivity effects of AI-adoption by firms are scarce. Using Finnish data on job advertisements between 2013 and 2019, we identify job advertisements referring to AI-related skills. Matching this data to productivity data from ORBIS, we estimate the productivity effects of AI related activities in our sample. Our results indicate that AI-adoption increases productivity, with three important qualifications. Firstly, effects are only observable for large firms with more than 499 employees. Secondly, there is evidence that early adopters did not experience productivity increases. This may be interpreted as technological immaturity.Thirdly, we find evidence of delays of least three years between the adoption of AI and ensuing productivity effects (investment delay effect). We argue that our findings on the technological immaturity and the investment delay effect may help explain the so-called AI-related return of the Solow-paradox: I.e. that AI is everywhere except in the productivity statistics.
    Keywords: Recruiting personnel; AI related jobs; Artificial Intelligence; Job Market; Text Mining; Firm performance; Productivity
    JEL: D22 D24 O31 O32
    Date: 2022–02–15
  4. By: Benjamin Montmartin (SKEMA Business School; Université Côte d'Azur; OFCE Sciences.Po; GREDEG CNRS)
    Abstract: We propose a unique market and social planner solution for a generalized new economic geography and growth model that highlights the importance of taking into account the existence of agglomeration externalities in the analysis of market failures and public policies. Our model disentangles the underinvestment in R&D and the suboptimal growth link present in the previous endogenous growth model. Consequently, our framework allows the market economy to reach various steady-state situations. By evaluating the effects of two strategic policies implemented in the European Union, namely, an innovation and a cohesion policy, we highlight that the complementarity or substitutability of these policies to bring the economy closer to its optimum is directly related to the hypothesis made on the link between agglomeration and growth.
    Keywords: Agglomeration, growth, spatial income inequality, innovation and cohesion policies
    JEL: F43 H50 R12
    Date: 2022–01
  5. By: Wouter P.C. Boon (Utrecht University [Utrecht]); Jakob Edler (Fraunhofer ISI - Fraunhofer Institute for Systems and Innovation Research - Fraunhofer-Gesellschaft - Fraunhofer, University of Manchester [Manchester]); Douglas K. R. Robinson (LISIS - Laboratoire Interdisciplinaire Sciences, Innovations, Sociétés - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Université Gustave Eiffel, UCL - University College of London [London])
    Abstract: Transitions are hardly conceivable without understanding how new markets are formed. However, there is still an incipient conceptualization of market formation in the context of transformation and transformative policy. Drawing on existing perspectives of market formation in economics of innovation, sociology of markets and marketing studies literature, this paper develops a framework for characterizing, differentiating and analyzing new market formation processes. We use three case studies to demonstrate how the framework is able to capture the dynamic and interconnected nature of market formation. The market formation framework serves to diagnose potential misalignments, bottlenecks and failures, to identify entry points for policy to intervene in market formation and support transformative innovation.
    Date: 2022

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