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on Technology and Industrial Dynamics |
| By: | Ron Boschma; ; |
| Abstract: | There is an ongoing dialogue that explores how the Global Production Network and Evolutionary Economic Geography (EEG) literatures can make promising crossovers. This paper aims to contribute to this debate by outlining a theoretical-analytical approach to regional studies on Global Value Chains (GVCs). Building on the EEG literature on relatedness, economic complexity and regional diversification, this approach aims to develop a better understanding of the ability of regions to develop new and upgrade existing GVCs, and why regions may experience the loss or downgrading of existing GVCs. We present the features of this relatedness/complexity approach to GVCs, and discuss potential fields of applications. |
| Keywords: | Evolutionary Economic Geography, Global Value Chains, Global Production Networks, regional diversification, relatedness, economic complexity |
| JEL: | B52 F23 O19 O33 R10 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2402&r=tid |
| By: | Kapetaniou, Chrystalla; Pissarides, Christoforos Antoniou |
| Abstract: | In a model with robots, and automatable and non-automatable human tasks, we examine robot-labour substitutions and show how they are influenced by a country's 'innovation system'. Substitution depends on demand and production elasticities, and other factors influenced by the innovation system. Making use of World Economic Forum data we estimate the relationship for thirteen countries and find that countries with poor innovation capabilities substitute robots for workers much more than countries with richer innovation capabilities, which generally complement them. In transport equipment and non-manufacturing robots and workers are stronger substitutes than in other manufacturing. |
| Keywords: | robots-employment substitution; automatable tasks; complementary task creation; innovation environment; industrial allocations |
| JEL: | J23 L60 O33 O52 |
| Date: | 2023–03–15 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121320&r=tid |
| By: | Faia, Ester; Ottaviano, Gianmarco Ireo Paolo; Spinella, Saverio |
| Abstract: | Leveraging the geographic dimension of a large administrative panel on employer-employee contracts, we study the impact of robot adoption on wage inequality through changes in worker-firm assortativity. Using recently developed methods to correctly and robustly estimate worker and firm unobserved characteristics, we find that robot adoption increases wage inequality by fostering both horizontal and vertical task specialization across firms. In local economies where robot penetration has been more pronounced, workers performing similar tasks have disproportionately clustered in the same firms ('segregation'). Moreover, such clustering has been characterized by the concentration of higher earners performing more complex tasks in firms paying higher wages ('sorting'). These firms are more productive and poach more aggressively. We rationalize these findings through a simple extension of a well-established class of models with two-sided heterogeneity, on-the-job search, rent sharing and employee Bertrand poaching, where we allow robot adoption to strengthen the complementarities between firm and worker characteristics. |
| Keywords: | robot adoption; worker-firm sorting; wage inequality; technological change; finite mixture models; European Union’s Horizon 2020 research and innovation programme (grant agreement n 789049-MIMAT-ERC2017-ADG) |
| JEL: | J22 J23 J31 J62 E21 D31 |
| Date: | 2023–02–10 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121328&r=tid |
| By: | Yi Yiang; Richard S. J. Tol |
| Abstract: | In the era of sustainability, firms grapple with the decision of how much to invest in green innovation and how it influences their economic trajectory. This study employs the Crepon, Duguet, and Mairesse (CDM) framework to examine the conversion of R&D funds into patents and their impact on productivity, effectively addressing endogeneity by utilizing predicted dependent variables at each stage to exclude unobservable factors. Extending the classical CDM model, this study contrasts green and non-green innovations' economic effects. The results show non-green patents predominantly drive productivity gains, while green patents have a limited impact in non-heavy polluting firms. However, in high-pollution and manufacturing sectors, both innovation types equally enhance productivity. Using unconditional quantile regression, I found green innovation's productivity impact follows an inverse U-shape, unlike the U-shaped pattern of non-green innovation. Significantly, in the 50th to 80th productivity percentiles of manufacturing and high-pollution firms, green innovation not only contributes to environmental sustainability but also outperforms non-green innovation economically. |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2401.16030&r=tid |
| By: | Ribeiro, Beatriz Couto (Technical University of Berlin (TUB) and University of Campinas (UNICAMP)); Jamasb, Tooraj (Department of Economics, Copenhagen Business School) |
| Abstract: | With the rise of renewable and distributed energy sources, electricity distribution and transmission utilities are facing increasing demand by regulators to innovate and adopt new technologies and transit to smart grids. However, these regulated natural monopolies often lack economic incentives to develop and adopt new technologies. To overcome this barrier, some regulatory authorities have introduced the so-called "innovation-stimuli" regulations to foster experimentation, technological adoption, and innovative solutions. We analyze and compare the effectiveness of two different innovation-stimuli regulations, the cost-pass through and WACC approaches, in the UK and Italy, respectively. To assess the impact of these different regulations on innovation, we use synthetic control (SC) and synthetic difference-in-differences (SDID) methods, which constitute causal inference techniques for small-n case study design and, for the first time, are employed to assess the impact of regulations on innovation outputs. Our panel data encompasses 13 European countries covering 1995 to 2013 and used smart grid projects and patent applications as dependent variables. Differently from what one might expect, not every innovation-stimuli regulation effectively supports innovation outputs. Meanwhile, cost-pass-through significantly and positively affected patent applications in the UK. In Italy, WACC did not affect patent applications, and European Commission-funded projects mostly drove the increases in smart-grid projects. |
| Keywords: | Innovation; Electricity sector; Regulation |
| JEL: | K23 O31 Q48 |
| Date: | 2024–02–13 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:cbsnow:2024_007&r=tid |
| By: | Sanjit Dhami; Paolo Zeppini |
| Abstract: | We consider firms’ choices between a clean technology that benefits, and a dirty technology that harms, the environment. Green firms are more suited to the clean, and brown firms are more suited to the dirty technology. We use a model derived from complexity theory that takes account of true uncertainty and increasing returns to technology adoption. We examine theoretically, the properties of the long-run equilibrium, and provide simulated time paths of technology adoption, using plausible dynamics. The long-run outcome is an ‘emergent property’ of the system, and it unpredictable despite there being no external technological or preference shocks. We describe the role of taxes and subsidies in facilitating adoption of the clean technology; the conflict between optimal Pigouvian taxes and adoption of clean technologies; the optimal temporal profile of subsidies; and the desirability of an international fund to provide technology assistance to poorer countries. Finally, we extend our model to stochastic dynamics in which firms experiment with technological alternatives, and demonstrate the existence of punctuated equilibria. |
| Keywords: | technology choice, climate change, complexity, lock-in effects, increasing returns, green subsidies, public policy, Pigouvian taxes, stochastic dynamics |
| JEL: | D01 D21 D90 H32 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10900&r=tid |
| By: | Autor, David; Patterson, Christina; Van Reenen, John |
| Abstract: | National U.S. industrial concentration rose between 1992-2017. Simultaneously, the Herfindhahl Index of local (six-digit-NAICS by county) employment concentration fell. This divergence between national and local employment concentration is due to structural transformation. Both sales and employment concentration rose within industry-by-county cells. But activity shifted from concentrated Manufacturing towards relatively un-concentrated Services. A stronger between-sector shift in employment relative to sales explains the fall in local employment concentration. Had sectoral employment shares remained at their 1992 levels, average local employment concentration would have risen by 9% by 2017 rather than falling by 7%. |
| Keywords: | employment concentration; sales concentration; local labor markets; structural transformation; POID |
| JEL: | L11 L60 O31 O34 P33 R3 |
| Date: | 2023–04–19 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121333&r=tid |
| By: | Omer Majeed (Reserve Bank of Australia); Jonathan Hambur (Reserve Bank of Australia); Robert Breunig (Crawford School of Public Policy, Australian National University) |
| Abstract: | Recent papers have argued that monetary policy and economic conditions can influence the amount of innovative activity in the economy, and therefore productivity and living standards in the future. This paper examines whether this is the case for Australia, a small open economy that tends to import innovation from overseas. We find that contractionary (expansionary) monetary policy reduces (increases) aggregate research and development (R&D) spending, and that lower (higher) R&D spending reduces (increases) future productivity. However, using firm-level data and a broader survey measure of innovation that also captures adoption, we find heterogeneous responses across different firm types. Small firms decrease innovation in response to contractionary monetary policy shocks whereas large firms increase innovation. This heterogeneity appears to reflect differing exposure to the channels through which monetary policy affects innovation. These channels include affecting demand or affecting financial conditions and constraints. We also find that US monetary policy spills over and affects Australian firms' innovation. Overall, our results suggest that monetary policy and economic conditions have medium-run effects on productivity, though the effects are more heterogeneous than previously documented. While the effects may cancel out over a cycle, this finding highlights the importance of stabilisation policy in preventing medium-run economic scarring. |
| Keywords: | innovation; monetary policy; firm-level data |
| JEL: | E52 O30 |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:rba:rbardp:rdp2024-01&r=tid |
| By: | Almeida, Derick (University of Coimbra); Naudé, Wim (RWTH Aachen University); Sequeira, Tiago Neves (University of Coimbra) |
| Abstract: | Theory predicts that global economic growth will stagnate and even come to an end due to slower and eventually negative growth in population. It has been claimed, however, that Artificial Intelligence (AI) may counter this and even cause an economic growth explosion. In this paper, we critically analyse this claim. We clarify how AI affects the ideas production function (IPF) and propose three models relating innovation, AI and population: AI as a research-augmenting technology; AI as researcher scale enhancing technology; and AI as a facilitator of innovation. We show, performing model simulations calibrated on USA data, that AI on its own may not be sufficient to accelerate the growth rate of ideas production indefinitely. Overall, our simulations suggests that an economic growth explosion would only be possible under very specific and perhaps unlikely combinations of parameter values. Hence we conclude that it is not imminent. |
| Keywords: | automation, artificial intelligence, economic growth, innovation, ideas production function |
| JEL: | O31 O33 O40 J11 J24 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16766&r=tid |
| By: | Bachmann, Ronald; Gonschor, Myrielle; Milasi, Santo; Mitra, Alessio |
| Abstract: | We examine how technology is associated with self-employment dynamics using worker-level data from 31 European countries. We find that while employees exposed to labour-augmenting technologies are more likely to move from paid-employment to solo self-employment and viceversa, employees exposed to labour-saving technologies are less likely to become self-employed. We identify important differences with respect to workers' socio-demographic characteristics. The results suggest that while labour-augmenting technologies promote workers' mobility and reduce unemployment risks for high-skilled workers, they have the opposite effect for low-skilled workers. Furthermore, labour-saving technologies worsen labour market outcomes particularlyfor low-skilled and routine workers. |
| Abstract: | Unter Verwendung von Daten auf Arbeitnehmerebene aus 31 europäischen Ländern untersuchen wir, wie Technologie mit Arbeitsmarktübergängen in die Selbständigkeit zusammenhängt. Unsere Ergebnisse zeigen, dass Arbeitnehmer, die in ihrer Arbeit mit arbeitsunterstützenden Technologien konfrontiert sind, eher von abhängiger Beschäftigung in die Soloselbstständigkeit wechseln und umgekehrt, während Arbeitnehmer, die mit arbeitssparenden Technologien konfrontiert sind, seltener eine selbstständige Tätigkeit aufnehmen. Wir finden wichtige Unterschiede in den soziodemographischen Merkmalen der Arbeitnehmer. Die Ergebnisse deuten darauf hin, dass arbeitsunterstützende Technologien zwar die Mobilität von Arbeitnehmern fördern und das Arbeitslosigkeitsrisiko von hoch qualifizierten Arbeitnehmern verringern, dass sie aber bei gering qualifizierten Arbeitnehmern den gegenteiligen Effekt haben. Darüber hinaus verschlechtern arbeitssparende Technologien die Arbeitsmarktergebnisse, insbesondere für Geringqualifizierte und Routinearbeiter. |
| Keywords: | Solo self-employment, occupations, tasks, technology, Europe |
| JEL: | J62 J63 J31 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:rwirep:282007&r=tid |
| By: | Lionel Fontagné (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique); Ariell Reshef (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Gianluca Santoni (CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique); Giulio Vannelli (LEDa - Laboratoire d'Economie de Dauphine - IRD - Institut de Recherche pour le Développement - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | We study how technology adoption and changes in global value chain (GVC) integration jointly affect labor shares and business function specialization in a sample of 14 manufacturing industries in 14 European countries in 1999–2011. Increases in upstream, forward GVC integration directly reduce labor shares, mostly through reductions in fabrication, but also via other business functions. We do not find any direct effects of robot adoption; robotization affects labor only indirectly, by increasing upstream, forward GVC integration. In this sense robotization is "upstream-biased". Rapid robotization in China shaped robotization in Europe and, therefore, relative demand for labor there. |
| Keywords: | labor share, functional specialization, global value chains, upstreamness, technological change, automation, robots |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-04346960&r=tid |
| By: | Klauser, Roman; Tamm, Marcus |
| Abstract: | Do returns to training differ if training is accompanied by technological innovations at the workplace? We analyze this potential heterogeneity of returns based on panel data from Germany that provide a unique measure for individuals' adoption of new technology at the workplace. In the preferred analysis we run fixed effects estimations. As a robustness test we also allow for individual time trends. The findings indicate positive wage effects and more job stability for training participants in general but no effects on wages and job mobility for new technology adoption. Furthermore, the combined occurrence of new technology adoption and of training participation does not make individuals better off in terms of wages or job stability compared with individuals experiencing neither training nor new technology adoption. |
| Abstract: | Unterscheiden sich Weiterbildungserträge, wenn Weiterbildung von technologischen Innovationen am Arbeitsplatz begleitet wird? Wir analysieren die potenzielle Heterogenität der Erträge anhand von Paneldaten aus Deutschland, die ein einzigartiges, individuelles Maß für die Adoption neuer Technologien am Arbeitsplatz bieten. In unserer Hauptanalyse verwenden wir sogenannte Fixed-Effects-Regressionen, die in Robustheitstests durch individuelle "time trends" ergänzt werden. Die Ergebnisse zeigen positive Lohneffekte und eine größere Arbeitsplatzstabilität für Personen, die an Weiterbildungsmaßnahmen teilgenommen haben, aber keine dieser Effekte für Personen, die über eine neue Technologien am Arbeitsplatz berichten. Darüber hinaus führt das gemeinsame Auftreten von neuen Technologien und Weiterbildungsteilnahme nicht dazu, dass Personen in Bezug auf Löhne oder Arbeitsplatzstabilität besser abschneiden als Personen, die weder Weiterbildung noch die Einführung neuer Technologien erfahren. |
| Keywords: | Returns to education, training, technology |
| JEL: | I26 J24 J62 M53 O33 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:rwirep:282011&r=tid |
| By: | Vahidin Jeleskovic; Steffen Loeber |
| Abstract: | In this paper, we employ spatial econometric methods to analyze panel data from German NUTS 3 regions. Our goal is to gain a deeper understanding of the significance and interdependence of industry clusters in shaping the dynamics of GDP. To achieve a more nuanced spatial differentiation, we introduce indicator matrices for each industry sector which allows for extending the spatial Durbin model to a new version of it. This approach is essential due to both the economic importance of these sectors and the potential issue of omitted variables. Failing to account for industry sectors can lead to omitted variable bias and estimation problems. To assess the effects of the major industry sectors, we incorporate eight distinct branches of industry into our analysis. According to prevailing economic theory, these clusters should have a positive impact on the regions they are associated with. Our findings indeed reveal highly significant impacts, which can be either positive or negative, of specific sectors on local GDP growth. Spatially, we observe that direct and indirect effects can exhibit opposite signs, indicative of heightened competitiveness within and between industry sectors. Therefore, we recommend that industry sectors should be taken into consideration when conducting spatial analysis of GDP. Doing so allows for a more comprehensive understanding of the economic dynamics at play. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2401.10261&r=tid |
| By: | Joachim Wagner (Leuphana Universität Lüneburg, Institut für Volkswirtschaftslehre and Kiel Centre for Globalization) |
| Abstract: | The use of cloud computing by firms can be expected to go hand in hand with higher productivity, more innovations, and lower costs, and, therefore, should be positively related to export activities. Empirical evidence on the link between cloud computing and exports, however, is missing. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union taken from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate this link. Applying standard parametric econometric models and a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), we find that firms which use cloud computing do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated cloud computing premium for extensive margins of exports is statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of this premium can be considered to be large. Extensive margins of exports and the use of cloud computing are positively related. |
| Keywords: | Cloud computing, exports, firm level data, Flash Eurobarometer 486, kernel-regularized least squares (KRLS) |
| JEL: | D22 F14 |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:lue:wpaper:427&r=tid |