nep-ino New Economics Papers
on Innovation
Issue of 2023‒10‒30
eight papers chosen by
Uwe Cantner, University of Jena

  1. The Productivity Effects of Regional Anchors on Local Firms in Swedish Regions between 2007 and 2019 – Evidence from an Expert-informed Machine-Learning Approach By Nilsson, Magnus; Schubert, Torben; Miörner, Johan
  2. Enhancing the Knowledge Economy: A Cross-Country Study of Knowledge Creation By Moid, Md Zubab Ibne; Buaka, Emefa; Link, Albert
  3. Bringing Technology to Market: National Heart, Lung, and Blood Institute SBIR Phase IIB Projects By Nienow, Sara; Leonchuk, Olena; O'Connor, Alan; Link, Albert
  4. Economic stimulus effects of product innovation under demand stagnation By Daisuke Matsuzaki; Yoshiyasu Ono
  5. Innovation During Challenging Times By Cascaldi-Garcia, Danilo; Vukoti, Marija; Zubairy, Sarah
  6. The Impact of R&D tax incentives: Results from the OECD microBeRD+ project By OECD
  7. Measuring governments’ R&D funding response to COVID-19: An application of the OECD Fundstat infrastructure to the analysis of R&D directionality By OECD
  8. Technological externalities and wages: new evidence from Italian provinces By Andrea Ricci; Claudia Vittori; Francesco Quartaro; Stefano Dughera

  1. By: Nilsson, Magnus (CIRCLE, Lund University); Schubert, Torben (CIRCLE, Lund University); Miörner, Johan (CIRCLE, Lund University)
    Abstract: This paper analyses the impact of regional anchors on local firms in Swedish regions. Departing from previous idiographic research, we adopt a nomothetic research design relying on a stepwise expert-informed supervised machine learning approach to identify the population of anchor firms in the Swedish economy between 2007 and 2019. We find support for positive anchor effects on the productivity of other firms in the region. These effects are moderated by regional and anchor conditions. We find that the effects are greater when there are multiple anchors within the same industry and that the effects are larger in economically weaker regions.
    Keywords: anchor-tenant; productivity; machine learning; anchor firms; Sweden
    JEL: D24 O30 R11 R12
    Date: 2023–10–10
  2. By: Moid, Md Zubab Ibne (University of North Carolina at Greensboro, Department of Economics); Buaka, Emefa (University of North Carolina at Greensboro, Department of Economics); Link, Albert (University of North Carolina at Greensboro, Department of Economics)
    Abstract: We identify quantitatively, using cross-country data from the Global Innovation Index, a path through which R&D (research and development) operates to affect economic growth and development. The path we consider is one that relates to enhancing the knowledge economy. Specifically, we contribute to the literature through the quantification of the antecedents and consequences of newly created knowledge: R&D creation of new knowledge economic growth and development. And, we show statistically that the R&D creation of new knowledge relationship is enhanced when businesses collaborate with universities. Not only is this collaborative indirect relationship new to the knowledge creation literature, but also it is based on the estimation of a model specification that has not previously been considered.
    Keywords: Global Innovation Index; knowledge economy; R&D; business-university collaboration;
    JEL: O33 O47 O50
    Date: 2023–10–18
  3. By: Nienow, Sara (RTI International); Leonchuk, Olena (RTI International); O'Connor, Alan (RTI International); Link, Albert (University of North Carolina at Greensboro, Department of Economics)
    Abstract: The National Heart, Lung, and Blood Institute (NHLBI) is the fourth largest institute in the U.S. National Institutes of Health (NIH). Surprisingly, there is a conspicuous void of policy studies related to the research activities of NHLBI in comparison to NIH or to the National Cancer Institute. This paper investigates the likelihood that a business funded through NHLBI’s Small Business Innovation Research (SBIR) program will commercialize from its Phase IIB translational support. Commercialization is one performance metric that quantifies a policy dimension of the success of the funded SBIR project. Based on an empirical analysis of 61 Phase IIB projects, we find that the most significant covariate with the likelihood of commercialization is the growth in human capital within the business since the Phase IIB award.
    Keywords: NHLBI; Phase IIB projects; SBIR program; technology commercialization;
    JEL: H11 H51 O38
    Date: 2023–10–06
  4. By: Daisuke Matsuzaki; Yoshiyasu Ono
    Abstract: When confronting economic stagnation, innovation (product innovation in particular) is often cited as an effective stimulus because it is assumed to encourage household consumption and lead to higher demand. Using a secular stagnation model with wealth preference, we examine the effects of product innovation on employment and consumption. This study examines three types of product innovation, including quantity-augmenting-like innovation, addictive innovation, and variety expansion. The first works as if a larger quantity were consumed although the actual quantity remains the same, the second reduces the elasticity of the marginal utility of consumption, and the third increases the variety of consumption commodities. We find that the first and third reduce both consumption and employment, whereas the second expands them. It suggests that policy makers should carefully choose the type of product innovation to promote as an economic stimulus: addictive innovation stimulates business activity whereas quantity-augmenting-like innovation and variety expansion worsen stagnation.
    Date: 2023–03
  5. By: Cascaldi-Garcia, Danilo (Federal Reserve Board); Vukoti, Marija (University of Warwick); Zubairy, Sarah (Texas A&M University and NBER)
    Abstract: When is receiving positive news regarding future technological advancements most impactful on the economy: during recessions or economic booms? A recession might represent an opportune time for investing in relatively cheaper, productivityenhancing activities. However, tighter financial constraints during recessions might hinder the ability to secure funds for these activities. We explore this dichotomy by exploiting patent-based innovation shocks, which are constructed using changes in stock market valuations of firms that obtain patent grants. We find that aggregate patent-based innovation shocks have a greater impact on the economy during recessions, leading to a more significant increase in private investment. Additionally, our exploration of firm-level data uncovers supporting evidence that firms tend to boost their capital investment and R&D expenditures in response to these innovation shocks, particularly during recessions. The financial constraints of firms play a crucial role, with capital investments by firms with low default risk driving the larger impact observed during recessions.
    Keywords: Innovation shocks ; Patent-Based Innovation Index ; Financial Frictions ; Firms heterogeneity ; State dependency
    Date: 2023
  6. By: OECD
    Abstract: This document reports on the final output of the OECD microBeRD+ project. Drawing on the outcomes of previous work, this study presents new evidence on the impact of business R&D support policies – tax incentives and direct forms of support – on business R&D investment (R&D input additionality) and the innovation and economic performance of firms (R&D output additionality). The report also provides an exploratory analysis of R&D spillovers.
    JEL: H25 O38 L25
    Date: 2023–10–09
  7. By: OECD
    Abstract: This paper presents new evidence on the size and direction of governments’ R&D funding response to the COVID-19 pandemic through the exploration of a novel data infrastructure, the OECD Fundstat initiative for the analysis of government-funded R&D projects. The document reports on the exploratory development and application of automatic classification tools to detect relevant COVID-19 R&D funding, map salient topics and classify and allocate project funding according to priorities in the WHO COVID-19 R&D Blueprint, as well as comparing results with similar analysis of scientific publication output data. The results provide new insights on which areas of enquiry were prioritised by governmental R&D funding bodies.
    Keywords: classification, COVID-19, directionality, Government funding, large language models, R&D, Research and Development, topic modelling
    JEL: C38 C45 O32 O38
    Date: 2023–10–16
  8. By: Andrea Ricci; Claudia Vittori; Francesco Quartaro; Stefano Dughera
    Abstract: In this paper, we investigate the relationship between local wages and the internal structure of the regional knowledge base. The purpose is to assess if the workers’ compensations are related to the peculiarities of the technological space where they supply their labor services. To test this hypothesis, we apply the concepts of related and unrelated variety to the firms’ patenting activity as to assess if wages grow more in a framework of ‘knowledge deepening’ (generated by firms innovating in related technological domains) or in one of ‘knowledge widening’ (generated by firms innovating in unrelated technological domains).
    Date: 2022–03–31

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