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on Technology and Industrial Dynamics |
| By: | Martin, Ralf; Verhoeven, Dennis Johannes Mathijs |
| Abstract: | Innovation policy faces a tradeoff between growth and climate objectives when the knowledge spillover externality from clean innovation is low compared to other sectors. To make such a comparison, we use patent data to estimate field-specific spillover returns generated by R&D support. Supporting Clean presents itself as a win-win opportunity, yielding global returns one-eighth higher than those of an untargeted policy. Nevertheless, only a modest portion of the returns stays within country borders, raising the question of whether national interests distort efficient allocation. Our policy simulations underscore the benefits of supranational coordination in clean innovation policy, potentially boosting returns by approximately 25% for the EU and over 60% globally. Moreover, the EU benefits strongly from US Clean innovation spillovers, impacting the debate on the Inflation Reduction Act. Overall, we identify no explicit innovation policy tradeoff in tackling the twin challenges of economic growth and climate change but emphasize the necessity for international cooperation. |
| Keywords: | innovation; knowledge spillovers; clean technology; innovation policy; green transition; net-zero; patent data |
| JEL: | O31 O33 O34 O38 Q55 Q58 |
| Date: | 2023–07–12 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121306&r=tid |
| By: | Yi Jiang; Richard S.J. Tol (Department of Economics, University of Sussex, BN1 9SL Falmer, United Kingdom) |
| 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 nongreen innovation economically. |
| Keywords: | Green innovation, Crowding-out effects, Productivity, CDM framework, Quantile regression, Recentered influence function |
| JEL: | D24 O31 Q55 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:sus:susewp:0124&r=tid |
| By: | Engberg, Erik (Örebro University); Görg, Holger (Kiel Institute for the World Economy); Lodefalk, Magnus (Örebro University); Javed, Farrukh (Örebro University); Längkvist, Martin (Örebro University); Monteiro, Natália Pimenta (University of Minho); Kyvik Nordås, Hildegunn (Council on Economic Policies); Schroeder, Sarah (Aarhus University); Tang, Aili (Örebro University) |
| Abstract: | We unbox developments in artificial intelligence (AI) to estimate how exposure to these developments affect firm-level labour demand, using detailed register data from Denmark, Portugal and Sweden over two decades. Based on data on AI capabilities and occupational work content, we develop and validate a time-variant measure for occupational exposure to AI across subdomains of AI, such as language modelling. According to the model, white collar occupations are most exposed to AI, and especially white collar work that entails relatively little social interaction. We illustrate its usefulness by applying it to near-universal data on firms and individuals from Sweden, Denmark, and Portugal, and estimating firm labour demand regressions. We find a positive (negative) association between AI exposure and labour demand for high-skilled white (blue) collar work. Overall, there is an up-skilling effect, with the share of white-collar to blue collar workers increasing with AI exposure. Exposure to AI within the subdomains of image and language are positively (negatively) linked to demand for high-skilled white collar (blue collar) work, whereas other AI-areas are heterogeneously linked to groups of workers. |
| Keywords: | artificial intelligence, labour demand, multi-country firm-level evidence |
| JEL: | E24 J23 J24 N34 O33 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16717&r=tid |
| By: | Bräuer, Richard |
| Abstract: | This paper proposes a model that explains both recently documented facts about the decline of disruptive innovation and the decline in productivity growth as the result of large firms trying to monopolize technologies by poaching inventors from disruptive activities. To come to this conclusion, the paper builds an endogenous growth model with inventor labor markets on which firms can interact strategically. To inform this model, I perform an event study of the effect of disruptive inventions on their technology fields using PATSTAT (1980-2010). I document that technology classes without disruption slowly trend towards incrementalism and that after a disruption, more patents get registered and research becomes less incremental. |
| Keywords: | disruptive innovation, general equilibrium, general purpose technology, innovation strategies, inventor labor markets, microeconometrics |
| JEL: | J24 J42 J44 O12 O33 O41 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iwhdps:281190&r=tid |
| By: | Bergeaud, Antonin; Guillouzouic, Arthur |
| Abstract: | Following Bergeaud et al. (2022), we construct a new measure of proximity between industrial sectors and public research laboratories. Using this measure, we explore the underlying network of knowledge linkages between scientific fields and industrial sectors in France. We show empirically that there exists a significant negative correlation between the geographical distance between firms and laboratories and their scientific proximity, suggesting strongly localized spillovers. Moreover, we uncover some important differences by field, stronger than when using standard patent-based measures of proximity. |
| Keywords: | knowledge spillovers; technological distance; public laboratories |
| JEL: | O32 O38 R12 |
| Date: | 2023–11–15 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121289&r=tid |
| By: | Bauluz, Luis; Bukowski, Pawel; Fransham, Mark; Lee, Annie Seong; López Forero, Margarita; Novokmet, Filip; Breau, Sébastien; Lee, Neil; Malgouyres, Clément; Schularick, Moritz; Verdugo, Gregory |
| Abstract: | The rise of economic inequalities in advanced economies has been often linked with the growth of spatial inequalities within countries, yet there is limited comparative research that studies the relationship between national and subnational economic inequality. This paper presents the first systematic attempt to create internationally comparable evidence showing how different countries perform in terms of geographic wage inequalities. We create cross-country comparable measures of spatial wage disparities between and within similarly-defined local labour market areas (LLMAs) for Canada, France, (West) Germany, the UK and the US since the 1970s, and assess their contribution to national inequality. By the end of the 2010s, spatial inequalities in LLMA mean wages are similar in Canada, France, Germany and the UK; the US exhibits the highest degree of spatial inequality. Over the study period, spatial inequalities have nearly doubled in all countries, except for France where spatial inequalities have fallen back to 1970s levels. Due to a concomitant increase in within-place inequality, the contribution of places in explaining national wage inequality has remained fairly constant over the 40-year study period, except in the UK where we document a significant increase. Whilst common global social, economic and technological shocks are important drivers of spatial inequality, this variation in levels and trends of spatial inequality opens the way to comparative research exploring the role of national institutions in mediating how global shocks translate into economic disparities between places. |
| Keywords: | regional inequality; wage inequality; local labour markets; ES/V013548/1; EXC 2126/1– 390838866 |
| JEL: | J3 R1 R23 |
| Date: | 2023–08–16 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121290&r=tid |
| By: | Dolores Añon Higón (Department of Applied Economics II and ERI-CES, Faculty of Economics, Universitat de València, Avda. Tarongers, s/n, 46022 Valencia (Spain)); Ionnanis Bournakis (SKEMA Business School. Avenue Willy Brandt. 59777 Euralille, France) |
| Abstract: | We examine the relationship between firms’ participation in global value chains (GVCs) and price markups. We use data from 14, 316 firms in six European countries obtained from AMADEUS data linked to the EFIGE project. There is substantial heterogeneity between countries and industries in terms of firm-specific time variant markups. After controlling for sample selection bias using coarsened exact matching (CEM), we find that firms involved in exporting produced-to-order goods and importing service and material inputs have between a three and four percent markup premium relative to nontrading firms. Our results remain robust to alternative definitions of GVC participation, different data matching techniques (Propensity Score Matching) and different markup estimates. Our findings contribute to the scarce but increasingly significant literature on markup heterogeneity and provide ample opportunities for designing industrial policies. |
| Keywords: | FDI, migration, elasticity of substitution, gender, discrimination |
| JEL: | F21 F22 F23 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:eec:wpaper:2403&r=tid |
| By: | Hémous, David; Lepot, Simon; Sampson, Thomas; Schärer, Julian |
| Abstract: | This paper provides a first comprehensive quantitative analysis of optimal patent policy in the global economy. We introduce a new framework, which combines trade and growth theory into a tractable tool for quantitative research. Our application delivers three main results. First, the potential gains from international cooperation over patent policies are large. Second, only a small share of these gains has been realized so far. And third, the WTO's TRIPS agreement has been counterproductive, slightly reducing welfare in the Global South and for the world. Overall, there is substantial scope for policy reform. |
| Keywords: | trade policy; innovation; growth; patents; TRIPS |
| JEL: | F13 F43 O34 |
| Date: | 2023–11–13 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121295&r=tid |
| By: | L. Serafini; E. Marrocu; R. Paci |
| Abstract: | This paper focuses on the impact of the Smart Specialisation Strategy (S3) and Industry 4.0 (I4) initiatives during the 2014-2020 programming period on firms' performance in Italy. By analysing European Regional Development Fund (ERDF)-funded projects under these frameworks, we use OpenCoesione data and a Difference-in-Differences approach to assess the effectiveness of S3 and I4 initiatives. Our results reveal that projects integrating I4 technologies within the S3 framework (S3I4 projects) significantly enhance firms' performance. This is particularly evident when compared to projects funded under other ERDF initiatives. The study highlights the importance of aligning S3 and I4 strategies with regional economic profiles and innovation capacities to maximise their impact. Our analysis underscores the role of these initiatives in driving innovation and economic growth. The results offer key insights for policymakers, suggesting that focused and strategic investment in S3 and I4 can lead to more effective regional innovation and development. |
| Keywords: | Industry 4.0;Innovation and firm Performance;Cohesion Policy;Counterfactual Impact Analysis;Smart Specialisation Strategy |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:cns:cnscwp:202403&r=tid |
| By: | Kauma, Bridget; Mion, Giordano |
| Abstract: | We propose a new data resource that attempts to overcome limitations of standard firm-level datasets for the UK (like the ARD/ABS) by building on administrative data covering the population of UK firms with at least one employee. We also construct a similar dataset for France and use both datasets to: 1) Provide some highlights of the data and an overall picture of the evolution of aggregate UK and French productivity and markups: 2) Analyse the spatial distribution of productivity in both countries at a fine level of detail - 228 Travel to Work Areas (TTWAs) for the UK and 297 Zones da'emploi (ZEs) for France - while focusing on the role of economic density. Our findings suggest that differences in firm productivity across regions are magnified in the aggregate by an increasing productivity return of density along the productivity distribution. |
| Keywords: | firm-level dataset; merging; BSD; FAME; VAT; FICUS; FARE; productivity; markups; UK; France; regional disparities; density |
| JEL: | R12 D24 |
| Date: | 2023–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121301&r=tid |
| By: | Merouani, Youssouf (Department of Economic History, Lund University); Perrin, Faustine (Department of Economic History, Lund University) |
| Abstract: | The gender patenting gap is well-established and is wide. Despite important progress made over the past decades, the gap remains. Why are women underrepresented in patenting activities? What are the roots of the gender patenting gap? How did the gap evolve since the ‘modern’ patenting system was established? Our knowledge of women’s contribution to innovative activities in the past is extremely scarce. We build an original dataset covering the entirety of French patents to investigate the extent to which women patented relative to men in France during the long nineteenth century and explores the factors behind the historical gender patenting gap. We find that despite the absence of scientific and technical education opportunities for women and the presence of institutional barriers, women, including those who were married, took an active part in the innovation process. The empirical analysis conducted in the paper suggests that explanations of the origins and persistence of the gender patenting gap have to be found outside of the patent system itself. |
| Keywords: | Patent; Innovation; Gender; Women; Nineteenth Century; France |
| JEL: | J16 N33 O30 |
| Date: | 2024–01–17 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:luekhi:0255&r=tid |
| By: | Joachim Wagner (Leuphana Universität Lüneburg, Institut für Volkswirtschaftslehre and Kiel Centre for Globalization) |
| Abstract: | The use of robots by firms can be expected to go hand in hand with higher productivity, higher product quality and more product innovation, which should be positively related to export activities. This paper uses firm level data from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate the link between the use of robots and export activities in manufacturing enterprises from the 27 member countries of the European Union. Applying standard parametric econometric models and a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), we find that firms which use robots do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated robots 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 robots are positively related. |
| Keywords: | Robots, exports, firm level data, Flash Eurobarometer 486, kernel-regularized least squares (KRLS) |
| JEL: | D22 F14 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:lue:wpaper:426&r=tid |
| By: | J.J. Harrigan; Ariell Reshef (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique, PJSE - Paris Jourdan Sciences Economiques - 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); Farid Toubal (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique, CEPR - Center for Economic Policy Research - CEPR, 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 the impact of techies—engineers and other technically trained workers—on firm-level productivity. We first report new facts on the role of techies in the firm by using French administrative data and unique surveys. Techies are STEM-skill intensive and are associated with innovation, as well as with technology adoption, management, and diffusion within firms. Using structural econometric methods, we estimate the causal effect of techies on firm-level Hicks-neutral productivity in both manufacturing and non-manufacturing industries. We find that techies raise firm-level productivity, and this effect goes beyond the employment of R&D workers, extending to ICT and other techies. In non-manufacturing firms, the impact of techies on productivity operates mostly through ICT and other techies, not R&D workers. Engineers have a greater effect on productivity than technicians. |
| Keywords: | productivity, R&D, ICT, techies, STEM skills. |
| Date: | 2024–01–31 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:hal-04429434&r=tid |
| By: | Mr. Andrew Berg; Mr. Edward F Buffie; Mariarosaria Comunale; Mr. Chris Papageorgiou; Luis-Felipe Zanna |
| Abstract: | The current wave of technological revolution is changing the way policies work. This paper examines the growth and distributional implications of three policies when “robot'' capital (a broad definition of robots, Artificial Intelligence, computers, big data, digitalization, networks, sensors and servos) is introduced in a neoclassical growth model. 1) cuts to the corporate tax rate; 2) increases in education spending; and 3) increases in infrastructure investment. We find that incorporating “robot'' capital into the model does make a big difference to policy outcomes: the trickle-down effects of corporate tax cuts on unskilled wages are attenuated, and the advantages of investment in infrastructure, and especially in education, are bigger. Based on our calibrations grounded on new empirical estimates, infrastructure investment and corporate tax cuts dominate investment in education in a "traditional" economy. However, in an economy with “robots” the infrastructure investment dominates corporate tax cuts, while investment in education tends to produce the highest welfare gains of all. The specific results, of course, may depend on the exact modeling of the technological change, but our main results remain valid and can provide more accurate welfare rankings. |
| Keywords: | Technological change; Artificial Intelligence; robots; growth; income distribution; fiscal policy; public investment; education |
| Date: | 2024–01–12 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:2024/003&r=tid |