nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2022‒10‒31
nine papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Green Innovation and Economic Growth in a North-South Model By Witajewski-Baltvilks,Jan Ignacy; Fischer,Carolyn
  2. Collaborative knowledge exchange promotes innovation By Tomoya Mori; Jonathan Newton; Shosei Sakaguchi
  3. The Opportunity Driven Entrepreneurship in the Context of Innovation Systems in Europe in the Period 2010-2019 By Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio
  4. Raising EU productivity through innovation By Reinhilde Veugelers; Frederic Warzynski
  5. Evaluating Transformation – what can we learn from the literature? By Wise, Emily; Arnold, Erik
  6. Technical Change, Task Allocation, and Labor Unions By Marczak, Martyna; Beissinger, Thomas; Brall, Franziska
  7. Ecological Transition and Structural Change: A New-Developmentalist Analysis By Giulio Guarini; Jose Luis Oreiro
  8. Opening the Black Box: Task and Skill Mix and Productivity Dispersion By Blackwood, G.Jacob; Cunningham, Cindy; Dey, Matt; Foster, Lucia; Grim, Cheryl; Haltiwanger, John C.; Nesbit, Rachel; Pabilonia, Sabrina Wulff; Stewart, Jay; Tuttle, Cody; Wolf, Zoltan
  9. Automation and Polarization By Daron Acemoglu; Jonas Loebbing

  1. By: Witajewski-Baltvilks,Jan Ignacy; Fischer,Carolyn
    Abstract: If one region of the world switches its research effort from dirty to clean technologies, will other regions follow To investigate this question, this paper builds a North-South model that combines insights from directed technological change and quality-ladder endogenous growth models with business-stealing innovations. While North represents the region with climate ambitions, both regions have researchers choosing between clean and dirty applications, and the resulting technologies are traded. Three main results emerge: (i) In the long-run, if North's research and development (R&D) sector is large enough, researchers in South will follow the switch from dirty to clean R&D in North, motivated by the growing value of clean markets. (ii) If the two regions direct research effort toward different sectors and the outputs of the two sectors are gross substitutes, then the long-run growth rates in both regions are lower than if the global research effort were invested in one sector. (iii) If North's government induces its researchers to switch to clean R&D through clean technology subsidies, the welfare-maximizing choice for South is to ensure that all of its researchers switch too, unless the social discount rate is high. The last result is true even if South's R&D sector is large.
    Date: 2022–06–21
  2. By: Tomoya Mori; Jonathan Newton; Shosei Sakaguchi
    Abstract: Considering collaborative innovation in patent development, we provide micro-level evidence of knowledge spillovers. Knowledge embodied in a patent is proxied by word pairs appearing in its abstract, while novelty is measured by the frequency with which these word pairs have appeared in past patents. Inventors are assumed to possess the knowledge associated with patents in which they have previously participated. We find that collaboration by inventors with more mutually differentiated knowledge sets is likely to result in patents with higher novelty.
    Date: 2022–10
  3. By: Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio
    Abstract: In this article we have estimated the value of “Opportunity Driven Entrepreneurship” in Europe. We use data from European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, Pooled OLS, and Dynamic Panel. Our results show that “Opportunity Driven Entrepreneurship” is positively associated, among others, to “Innovation Friendly Environment” and “Turnover Share Large Enterprises”, while it is negatively associated, among others, to “Sales Impacts” and “R&D Expenditure Business Sectors”.
    Keywords: Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation
    JEL: O30 O31 O32 O33 O34
    Date: 2022–09–26
  4. By: Reinhilde Veugelers; Frederic Warzynski
    Abstract: A better overview of which firms are most likely to adopt digital technologies and to innovate, and to turn these investments into productivity growth
    Date: 2022–06
  5. By: Wise, Emily (CIRCLE, Lund University); Arnold, Erik (University of Manchester)
    Abstract: The last decade’s rise of the so-called “third frame” (or third generation) of Transformative Innovation Policies (TIP) has shifted focus of research and innovation investments from economic growth and competitiveness to also tackling societal challenges and generating broader environmental and societal impact. The evolution in rationale and aims for policy action also implies a need to adapt and evolve evaluative strategies and practices. As policymakers begin to develop new transformative innovation programmes, a key question arises as to how monitoring, evaluation and learning practices (currently framed around 1st and 2nd generation innovation policies) can be adapted in order to meet 3rd generation innovation policy needs? In shaping a response, one can learn from both theory and practice. This brief (produced within the GReaTr initiative ) aims to provide a synthesis of what recent academic research tells us about evaluating transformation, leveraging a set of 11 seminal articles (and other complementary literature) to answer four questions: For whom and why? What to evaluate? How to evaluate? What unit of analysis? The synthesis points to a relative consensus in the academic literature on the main purposes and uses, the recommended principles and approaches, as well as possibilities for delineating and dealing with multiple scopes and units of analysis in evaluating transformation – yet highlights different conceptual framings of system change. The summary provides inputs to planning an evaluative strategy for TIP and highlights the need to consider new questions related to approaches to reporting across funding agencies, and more active roles for funding and policymaking agencies in dialogues about strategic direction and prioritisation of investments.
    Keywords: Innovation policy; Evaluation; System evaluation; Transformation; Socio-technical transitions
    JEL: O32 O38
    Date: 2022–10–04
  6. By: Marczak, Martyna; Beissinger, Thomas; Brall, Franziska
    Abstract: We propose a novel framework that integrates the "task approach" for a more precise production modeling into the search-and-matching model with low- and high-skilled workers, and wage setting by labor unions. We establish the relationship between task reallocation and changes in wage pressure, and examine how skill- biased technical change (SBTC) affects the task composition, wages of both skill groups, and unemployment. In contrast to the canonical model with a fixed task allocation, low-skilled workers may be harmed in terms of either lower wages or higher unemployment depending on the relative task-related productivity profile of both worker types. We calibrate the model to the US and German data for the periods 1995-2005 and 2010-2017. The simulated effects of SBTC on low-skilled unemployment are largely consistent with observed developments. For example, US low-skilled unemployment increases due to SBTC in the earlier period and decreases after 2010.
    Keywords: task approach,search and matching,labor unions,skill-biased technical change,labor demand,wage setting
    JEL: J64 J51 E23 E24 O33
    Date: 2022
  7. By: Giulio Guarini; Jose Luis Oreiro
    Abstract: The article aims to analyze the ecological transition and the structural change by considering the role of Medium-Income Trap (MIT) with respect to exchange rate overvaluation and (re)industrialization, according to the structuralist-New Developmentalist Approach. The ecological challenges can be faced by an ecological transition based on Ecological Technological Progress and Ecological Structural Change (ESC). The ESC can be represented by the increase of the share of green activities in output for increasing the environmental efficiency of the economy. The theoretical core of the new developmentalism is the tendency of overvaluation of real exchange rate for middle income countries whose sources are the Dutch disease (and the growth with external saving strategy). This fact generates the MIT concerning the negative impact of overvaluation real exchange rate on the industrial development. Thus, we analyze how the ESC interact with the drivers of overvaluation exchange rate by carrying out a post-Keynesian model based the Structuralist-New Developmentalist features. In this perspective, we integrate the issue of the achievement of the environmental targets as indicated by the Climate International Conferences and by the UN initiative of the Sustainable Developments Goals, to the structural change necessary for the economic catching-up of the middle income (and/or developing) countries.
    Keywords: Ecological Transition, Structural Change, Dutch-Disease, New-Developmentalism
    JEL: O11 O14 Q56 Q57
    Date: 2022–10
  8. By: Blackwood, G.Jacob (Amherst College); Cunningham, Cindy (U.S. Bureau of Labor Statistics); Dey, Matt (US Bureau of Labor Statistics); Foster, Lucia (U.S. Census Bureau); Grim, Cheryl (U.S. Census Bureau); Haltiwanger, John C. (University of Maryland); Nesbit, Rachel (University of Maryland); Pabilonia, Sabrina Wulff (U.S. Bureau of Labor Statistics); Stewart, Jay (U.S. Bureau of Labor Statistics); Tuttle, Cody (University of Texas at Austin); Wolf, Zoltan (U.S. Census Bureau)
    Abstract: An important gap in most empirical studies of establishment-level productivity is the limited information about workers' characteristics and their tasks. Skill-adjusted labor input measures have been shown to be important for aggregate productivity measurement. Moreover, the theoretical literature on differences in production technologies across businesses increasingly emphasizes the task content of production. Our ultimate objective is to open this black box of tasks and skills at the establishment-level by combining establishment-level data on occupations from the Bureau of Labor Statistics (BLS) with a restricted-access establishment-level productivity dataset created by the BLS-Census Bureau Collaborative Micro-productivity Project. We take a first step toward this objective by exploring the conceptual, specification, and measurement issues to be confronted. We provide suggestive empirical analysis of the relationship between within-industry dispersion in productivity and tasks and skills. We find that within-industry productivity dispersion is strongly positively related to within-industry task/skill dispersion.
    Keywords: productivity, skills, tasks, manufacturing
    JEL: D24 J24 J31 L60
    Date: 2022–09
  9. By: Daron Acemoglu; Jonas Loebbing
    Abstract: We develop an assignment model of automation. Each of a continuum of tasks of variable complexity is assigned to either capital or one of a continuum of labor skills. We characterize conditions for interior automation, whereby tasks of intermediate complexity are assigned to capital. Interior automation arises when the most skilled workers have a comparative advantage in the most complex tasks relative to capital, and because the wages of the least skilled workers are sufficiently low relative to their productivity and the effective cost of capital in low-complexity tasks. Minimum wages and other sources of higher wages at the bottom make interior automation less likely. Starting with interior automation, a reduction in the cost of capital (or an increase in capital productivity) causes employment and wage polarization. Specifically, further automation pushes workers into tasks at the lower and upper ends of the task distribution. It also monotonically increases the skill premium above a skill threshold and reduces the skill premium below this threshold. Moreover, automation tends to reduce the real wage of workers with comparative advantage profiles close to that of capital. We show that large enough increases in capital productivity ultimately induce a transition to low-skill automation and qualitatively alter the effects of automation - thereafter inducing monotone increases in skill premia rather than wage polarization.
    JEL: J23 J31 O33
    Date: 2022–09

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