nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2023‒06‒19
ten papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Innovation and the Labor Market: Theory, Evidence and Challenges By Corrocher, Nicoletta; Moschella, Daniele; Staccioli, Jacopo; Vivarelli, Marco
  2. Robots, Occupations, and Worker Age: A Production-Unit Analysis of Employment By Deng, Liuchun; Müller, Steffen; Plümpe, Verena; Stegmaier, Jens
  3. The Transfer of Federally Funded Technology: A Study of Small, Entrepreneurial, and Ambidextrous Firms By Guerrero, Maribel; Link, Albert; van Hasselt, Martijn
  4. Clean Innovation and Heterogeneous Financing Costs By Emanuele Campiglio; Alessandro Spiganti; Anthony Wiskich
  5. The past and future of work: how history can inform the age of automation By Schneider, Benjamin; Vipond, Hillary
  6. The characteristics and geographic distribution of robot hubs in U.S. manufacturing establishments By Brynjolfsson, Erik; Buffington, Catherine; Goldschlag, Nathan; Li, J. Frank; Miranda, Javier; Seamans, Robert
  7. Vertical integration and patterns of divergence in European industries: A long-term input-output analysis By Fabio Ascione; Maria Enrica Virgillito
  8. Productivity Spillovers among Knowledge Workers in Agglomerations: Evidence from GitHub By Lena Abou El-Komboz; Thomas Fackler
  9. The Returns to Government R&D: Evidence from U.S. Appropriations Shocks By Andrew J. Fieldhouse; Karel Mertens
  10. The green side of productivity: An international classification of green and brown occupations By Nathalie Scholl; Sébastien Turban; Peter N. Gal

  1. By: Corrocher, Nicoletta; Moschella, Daniele; Staccioli, Jacopo; Vivarelli, Marco
    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
  2. By: Deng, Liuchun (Yale-NUS College); Müller, Steffen (IWH Halle); Plümpe, Verena (IWH Halle); Stegmaier, Jens (Institute for Employment Research (IAB), Nuremberg)
    Abstract: We analyze the impact of robot adoption on employment composition using novel micro data on robot use of German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favorable employment effects for the least routine-task intensive occupations and for young workers, the latter being better at adapting to change. An event-study analysis for robot adoption confirms both predictions. We do not find decreasing employment for any occupational or age group but churning among low-skilled workers rises sharply. We conclude that the displacement effect of robots is occupation-biased but age neutral whereas the reinstatement effect is age-biased and benefits young workers most.
    Keywords: robots, jobs, occupation, worker age
    JEL: J23
    Date: 2023–05
  3. By: Guerrero, Maribel (Arizona State University); Link, Albert (University of North Carolina at Greensboro, Department of Economics); van Hasselt, Martijn (University of North Carolina at Greensboro, Department of Economics)
    Abstract: In this paper, we study the technology transfer mechanisms used to protect intellectual property by small, entrepreneurial firms that received Phase II research awards from the U.S Small Business Innovation Research (SBIR) program. The technology transfer mechanisms considered are patenting and publishing. Controlling for the agencies that funded the Phase II research (DOD and NIH), we find that the presence of a university as a research partner engenders greater patenting and publishing. We also find that minority-owned firms patent more intensely than do other firms. A portion of the firms patent and publish; we define these firms, based on our advanced review of the literature, to be ambidextrous. Ambidextrous firms are more likely to include a university as a research partner, to be male-owned and minority-owned, and to be relatively small. Our findings represent a new and important advancement to the literature.
    Keywords: SBIR program; technology transfer; patenting; publishing; intellectual property; ambidexterity; entrepreneurial firms; program evaluation;
    JEL: L21 L26 O34 O38
    Date: 2023–05–30
  4. By: Emanuele Campiglio; Alessandro Spiganti; Anthony Wiskich
    Abstract: Access to finance is a major barrier to clean innovation. We incorporate heterogeneous and endogenous financing costs in a directed technical change model and identify optimal climate mitigation policies. The presence of a financing experience effect induces more ambitious policies in the short-term, both to shift innovation and production towards clean sectors and to reduce the financing cost differential across technologies, which further facilitates the transition. The optimal climate policy mix between carbon taxes and clean research subsidies depends on whether experience is gained through clean production or research. In our benchmark scenario, where clean financing costs decline as cumulative clean output increases, we find an optimal carbon price premium of 47% in 2025, relative to a case with no financing costs.
    Keywords: carbon tax, directed technological change, endogenous growth, financing experience effect, innovation policy, low-carbon transition, optimal climate policy, sustainable finance
    JEL: H23 O31 O44 Q55 Q58
    Date: 2023–05
  5. By: Schneider, Benjamin; Vipond, Hillary
    Abstract: Debates about the future of work frequently reference past instances of transformative innovation to explain how automation and artificial intelligence could reshape society and the economy. However, historians have rarely engaged with these discussions, and most economists and technologists have limited knowledge of past experiences of technological change. In this paper we show that a deeper understanding of history can expand our understanding of possibilities and pitfalls for employment in the future. We open by demonstrating that evidence from historical events has been used to inform responses to present-day challenges. We argue that history provides the only way to analyze the long-term impacts of technological change, and that the scale of the First Industrial Revolution may make it the only precedent for emerging transformations. Next, we present an overview of the current debates around the potential effects of impending labour replacing innovation. We then summarize existing historical research on the causes and consequences of technological change and identify areas in which salient historical findings are overlooked. We close by proposing further research into past technological shocks that can enhance our vision of an automated future.
    Keywords: technological change; innovation; automation; future of work; technological unemployment; labour displacement
    JEL: J23 J64 J81 N31 N33 N71 N73 O31 O33
    Date: 2023–05
  6. By: Brynjolfsson, Erik; Buffington, Catherine; Goldschlag, Nathan; Li, J. Frank; Miranda, Javier; Seamans, Robert
    Abstract: We use data from the Annual Survey of Manufactures to study the characteristics and geography of investments in robots across U.S. manufacturing establishments. We find that robotics adoption and robot intensity (the number of robots per employee) is much more strongly related to establishment size than age. We find that establishments that report having robotics have higher capital expenditures, including higher information technology (IT) capital expenditures. Also, establishments are more likely to have robotics if other establishments in the same Core-Based Statistical Area (CBSA) and industry also report having robotics. The distribution of robots is highly skewed across establishments' locations. Some locations, which we call Robot Hubs, have far more robots than one would expect even after accounting for industry and manufacturing employment. We characterize these Robot Hubs along several industry, demographic, and institutional dimensions. The presence of robot integrators and higher levels of union membership are positively correlated with being a Robot Hub.
    Keywords: labor, manufacturing, robot, technology adoption
    JEL: L64 O34 O36 O4
    Date: 2023
  7. By: Fabio Ascione; Maria Enrica Virgillito
    Abstract: Against a theoretical background which recognizes the gains from trade liberalization, this paper asks whether, and if so to what extent, economic integration as directly measured through vertically integrated value-added has increased or reduced convergence among European industries and related countries. To answer this question, we draw upon new input-output tables and sectoral divergence measures for 14 European countries and 19 sectors since 1970. Our novel database provides consistent long-run measures of international input–output linkages and sectoral dispersion in labor productivity and wages. We use these measures to study the timing and mechanisms that govern the relationship between economic integration and sectoral gaps, taking a European perspective and focusing on the role of international production fragmentation via input-output linkages. According to our findings, higher vertical integration has fostered divergence rather than convergence within industries. Lock-in effects in laggard positions coupled with positive feedback loops and increasing returns for leading positions are potential mechanisms to explain why the fruits of rising vertical integration are shared unequally between poor-performing industries and frontier industries.
    Keywords: input-output analysis; divergence; economic integration; Europe; trade liberalization.
    Date: 2023–06–04
  8. By: Lena Abou El-Komboz (ifo Institute, LMU Munich); Thomas Fackler (ifo Institute, LMU Munich, CESifo, Laboratory for Innovation Science at Harvard)
    Abstract: Software engineering is a field with strong geographic concentration, with Silicon Valley as the epitome of a tech cluster. Yet, most studies on the productivity effects of agglomerations measure innovation with patent data, thus capturing only a fraction of the industry's activity. With data from the open source platform GitHub, our study contributes an alternative proxy for productivity, complementing the literature by covering a broad range of software engineering. With user activity data covering the years 2015 to 2021, we relate cluster size to an individual's productivity. Our findings suggest that physical proximity to a large number of other knowledge workers in the same field leads to spillovers, increasing productivity considerably. In further analyses, we confirm the causal relationship with an IV approach and study heterogeneities by cluster size, initial productivity and project characteristics.
    Keywords: agglomeration effects; knowledge spillovers; open source; online collaboration;
    JEL: D62 J24 O33 O36 R32
    Date: 2023–05–26
  9. By: Andrew J. Fieldhouse; Karel Mertens
    Abstract: We estimate the causal impact of government-funded R&D on business-sector productivity growth. Identification is based on a novel narrative classification of all significant postwar changes in appropriations for R&D funded by five major federal agencies. Using long-horizon local projections and the narrative measures, we find that an increase in appropriations for nondefense R&D leads to increases in various measures of innovative activity, and higher productivity in the long run. We structurally estimate the production function elasticity of nondefense government R&D capital using the SP-IV methodology of Lewis and Mertens (2023), and obtain implied returns of 150 to 300 percent over the postwar period. The estimates indicate that government-funded R&D accounts for about one quarter of business-sector TFP growth since WWII, and generally point to substantial underfunding of nondefense R&D.
    Keywords: government; R&D; productivity; growth; narrative analysis
    JEL: E62 O38 O47
    Date: 2023–05–18
  10. By: Nathalie Scholl; Sébastien Turban; Peter N. Gal
    Abstract: This paper describes the methodology used for crosswalking occupation-based measures of Green (“environmentally friendly”) and Brown (“polluting”) jobs from the Standard Occupational Classification (SOC) system to the International Standard Occupation Classification (ISCO) 08 at the most detailed (4-digit) level. The original, task-based Greenness scores by Vona et al. (2018) are provided at the 8-digit SOC level, and the industry-based Brownness measures are provided in 6-digit SOC. Crosswalking these measures requires several choices in terms of weighting and aggregating, which this paper describes in detail. The robustness of the resulting measures to the different weighting options and underlying assumption is tested using Linked Employer-Employee data from Portugal. An empirical application to the Productivity-Greenness link at the firm level shows the robustness of this link to different weighting choices, and confirms that all of the different measures derived are consistent in measuring the Greenness of jobs.
    Keywords: Brown occupations, Green occupations, Green skills, Green transition, , Occupation Classification, productivity
    JEL: J21 J24 L25
    Date: 2023–05–25

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