nep-ino New Economics Papers
on Innovation
Issue of 2023‒06‒26
eight papers chosen by
Uwe Cantner
University of Jena

  1. “Trains of Thought: High-Speed Rail and Innovation in China” By Georgios Tsiachtsiras; Deyun Yin; Ernest Miguelez; Rosina Moreno
  2. Innovation Studies, Social Innovation, and Sustainability Transitions Research: From mutual ignorance towards an integrative perspective? By Attila Havas; Doris Schartinger; K. Matthias Weber
  3. Regional Eco-Innovation Trajectories By Hendrik Hansmeier; Sebastian Losacker;
  4. The Kaldor-Verdoorn Law at the Age of Robots and AI. By Andrea Borsato; Andre Lorentz
  5. A Crosswalk from the Business R&D and Innovation Survey (BRDIS) and the Survey of Industrial Research and Development (SIRD) to the Longitudinal Business Database (LBD) and the Standard Statistical Establishment List (SSEL) By Assa Cohen
  6. Innovation, localized externalities, and the British Industrial Revolution, 1700-1850 By Ugo M. Gragnolati; Alessandro Nuvolari
  7. The Impact of Sustainable Innovation Finance on Achieving Global Climate Goals By Schreiner, Lena; Madlener, Reinhard
  8. Innovation and the Labor Market: Theory, Evidence and Challenges By Corrocher, Nicoletta; Moschella, Daniele; Staccioli, Jacopo; Vivarelli, Marco

  1. By: Georgios Tsiachtsiras (AQR-IREA University of Barcelona and University of Bath); Deyun Yin (School of Economics and Management, Harbin Institute of Technology); Ernest Miguelez (Univ. Bordeaux and AQR-IREA University of Barcelona); Rosina Moreno (AQR-IREA University of Barcelona)
    Abstract: This paper explores the effect of the High Speed Rail (HSR) network expansion on local innovation in China during the period 2008-2016. Using exogenous variation arising from a novel instrument - courier’s stations during the Ming dynasty, we find solid evidence that the opening of a HSR station increases cities’ innovation activity. We also explore the role of inter-city technology diffusion as being behind the surge of local innovation. To do it, we compute least-cost paths between city-pairs, over time, based on the opening and speed of each HSR line, and obtain that an increase in a city’s connectivity to other cities specialized in a specific technological field, through the HSR network, increases the probability for the city to specialize in that same technological field. We interpret it as evidence of knowledge diffusion.
    Keywords: High speed rail, Innovation, Technology Diffusion, Patents, Specialization. JEL classification: R40, O18, O30, O33.
    Date: 2022–11
  2. By: Attila Havas (Institute of Economics, Centre for Economic and Regional Studies, AIT Austrian Institute of Technology, Center for Innovation Systems and Policy); Doris Schartinger (AIT Austrian Institute of Technology, Center for Innovation Systems and Policy); K. Matthias Weber (AIT Austrian Institute of Technology, Center for Innovation Systems and Policy, Université Gustave Eiffel, LISIS)
    Abstract: Goal-oriented transformative change processes – that is, system-transforming processes that are guided by the ambition to resolve current or expected future societal challenges of various kinds – can only start once possible goals are considered by key stakeholders and the relevant actors are committed to act. Hence, there is a need for widening the scope of the current, partial conceptual models to consider the co-evolutionary interactions between technology, economy, and society to understand these changes. This claim is based on our review of Innovation Studies, Social Innovation research, and Sustainability Transitions research. The paper discusses the key conceptual elements of each strand; offers a definition of goal-oriented transformative change and building blocks for a new, integrative framework to analyse it; proposes directions for future research and draw tentative governance and policy implications.
    Keywords: Innovation studies; Social innovation research; Sustainability transitions research; Focussed literature review; Goal-oriented transformative change; A new, integrative analytical framework
    JEL: B52 H12 L31 O30 O31 O33 O35 O38 O44 P11 Q01 Q50 Q54 Q55 Q58
    Date: 2022–12
  3. By: Hendrik Hansmeier; Sebastian Losacker;
    Abstract: Given that eco-innovations and the associated renewal of economic structures are pivotal in addressing environmental problems, economic geography research is increasingly focusing on their spatio-temporal dynamics. While green technological and industrial path developments in specific regions have received considerable attention, little effort has been made to derive general patterns of environmental inventive activities across regions. Drawing on unique data capturing both green incumbent and green start-up activities in the 401 German NUTS-3 regions over the period 1997-2018, this article aims to trace and compare the long-term green regional development. For this purpose, we introduce social sequence analysis methods to economic geography that allow us to understand the constitution of regional eco-innovation trajectories. The findings suggest that regions mainly display distinct trajectories. Yet, structural similarities emerge in the sense that regions of the same type occur in spatial proximity to each other and show persistent specialization patterns. These range from the simultaneous presence or absence of green incumbents and green start-ups to the dominance of just one of the two groups of actors. Only some regions manage to establish an above-average eco-innovation specialization over time. Since this greening originates from either green incumbent or green start-up specialization, green regional trajectories can be assumed to unfold mainly in a path dependent and less radical manner. In summary, this study provides important empirical and methodological impulses for further in-depth analyses to disentangle spatio-temporal phenomena in economic geography.
    Keywords: eco-innovation, green regional development, path dependency, regional transitions, social sequence analysis
    Date: 2023–06
  4. By: Andrea Borsato; Andre Lorentz
    Abstract: This paper contributes to the literature around the Kaldor-Verdoorn law and analyses the impact of robotisation on the channel through which the law shapes labour-productivity growth. We start with a simple evolutionary interpretation of the law that combines Kaldorian and Post-Keynesian arguments with the neo-Schumpeterian theory of innovation and technological change. Then we apply a GMM estimator to a panel of 17 industries in 25 OECD capitalist economies for the period 1990-2018. After elaborating on the general evidence of the Kaldor-Verdoorn law in the sample, we investigate the effect of increasing robotisation. The estimates suggest that for industries with a higher-than-average robot density, the increasing adoption of robots weakens, at least, the meso-economic channel that relates productivity growth to mechanisation. Yet, the higher degree of robotisation strengthens the mechanism that links labour productivity growth at the industrial level to the macro-level dynamic increasing returns to scale that emerge from a general expansion of economic activities through the many interactions between sectors. Such results are in agreement with the empirical literature that suggests different impacts from robotisation on the basis of the level of economic activity considered.
    Keywords: Labour productivity, Kaldor-Verdoorn law, Robotisation, GMM.
    JEL: J23 O33 O47
    Date: 2023
  5. By: Assa Cohen
    Abstract: The Survey of Industrial Research and Development (SIRD) and the Business R&D and Innovation Survey (BRDIS) provide a rich description of R&D at the firm-level. Unfortunately, linking BRDIS and SIRD to other Census data is not straightforward. Standard Census identifiers are often missing, while the identifiers used in BRDIS-SIRD are different in format than those used in other data sets like Longitudinal Business Database (LBD) and the Standard Statistical Establishment List (SSEL). In this project we develop a new crosswalk to address the problem. The crosswalk assigns to each firm-year pairs in BRDIS-SIRD the identifiers of corresponding observations in LBD or SSEL. To generate the crosswalk, we: (i) Infer standard CES identifiers (FIRMID) from variables in SIRD. (ii) Map from BRDIS-SIRD to LBD, and from LBD to SSEL. (iii) Combine the results of multiple linkages, each using a different identifier. The crosswalk allows connecting BRDIS-SIRD with any Census collected data set that uses the identifiers applied in LBD and SSEL. Further, it allows creating links from BRDIS-SIRD to external data using names and addresses appearing in SSEL. In this context, it improves researchers’ ability to use tools that were developed by the Census to connect SSEL to patent data for assigning patents to firms in BRDIS-SIRD. That, in turn, facilitates further study of the relation between R&D activity, reported in BRDIS-SIRD, and innovation outputs, as they are reflected in patenting.
    Date: 2023–05
  6. By: Ugo M. Gragnolati; Alessandro Nuvolari
    Abstract: We study the determinants of the spatial distribution of patent inventors at the county level for Great Britain between 1700-1850. Our empirical analysis rests on the localization model by Bottazzi et al. (2007) and on the related estimation procedure by Bottazzi and Gragnolati (2015). Such an approach helps in particular to discriminate the role of localized externalities against other descriptors of county attractiveness. Our results show that, while the underlying geography of production remained a strong determinant of inventor location all throughout the industrial revolution, the effect of localized externalities among patent inventors went from being nearly absent in the early phases of industrialization to becoming a major driver of inventor location. In particular, local interactions among the ''mass'' of generic inventors turn out to be at least as important as interactions with ''elite'' inventors.
    Keywords: Inventor location; Patents; Localized externalities; Industrial Revolution.
    Date: 2023–06–05
  7. By: Schreiner, Lena (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN)); Madlener, Reinhard (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))
    Abstract: This paper investigates the impact of financial frictions on sustainable economic growth in the global economy. We present a model of endogenous directed technical change including a public and private financial sector, allowing for an endogenous financing decision in terms of internal and different external financing of technical change. Capturing the dynamics between the ‘global North’, i.e., the developed economies, and the ‘global South’, i.e., the developing economies, we allow for technological development to occur through innovation or imitation and, hence, capturing technology diffusion processes in the global economy. Our findings substantiate the way in which the presence of financing costs and frictions in the financial markets—which are elevated with regards to sustainable innovation and in the developing world—cause the global economy to converge towards a non-sustainable growth path in the absence of policy intervention. This development can be addressed partially, but not fully, by sustainable public investment. However, to steer the economy to a fully sustainable growth path, an additional regulation or incentivization of private investors is necessary. Alternatively, a sufficiently high carbon price can be set. However, other than in the current reality, this carbon price would have to cover a large share of global emissions.
    Keywords: Sustainable innovation; sustainable finance; innovation finance; green growth; financing frictions; directed technical change; endogenous innovation
    JEL: N70 O11 O16 O19 O31 O33 O44 Q43
    Date: 2023–04–01
  8. By: Corrocher, Nicoletta (Bocconi University); Moschella, Daniele (Sant'Anna School of Advanced Studies); Staccioli, Jacopo (Università Cattolica del Sacro Cuore); Vivarelli, Marco (Università Cattolica del Sacro Cuore)
    Abstract: This paper deals with the complex relationship between innovation and the labor market, analyzing the impact of new technological advancements on overall employment, skills and wages. After a critical review of the extant literature and the available empirical studies, novel evidence is presented on the distribution of labor-saving automation (namely robotics and AI), based on natural language processing of US patents. This mapping shows that both upstream high-tech providers and downstream users of new technologies—such as Boeing and Amazon—lead the underlying innovative effort.
    Keywords: innovation, technological change, skills, wages, technological unemployment
    JEL: O33
    Date: 2023–05

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