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on Technology and Industrial Dynamics |
| By: | Filimonovic, Dragan; Macher, Jeffrey T.; Rutzer, Christian; Weder, Rolf |
| Abstract: | We examine whether 'pioneer' regions - early leaders in generating new ideas in emerging scientific fields - develop and maintain an innovation advantage in the same fields over time. Our analysis covers 24 disruptive technologies (e.g. AI, cloud computing) in thousands of OECD regions over 20 years. The results show that pioneer regions gain a significant and growing innovation advantage over non-pioneer regions. This advantage is most pronounced in "super-cluster" regions, which are leaders in both science and related innovation. These findings highlight the importance of early scientific leadership for sustained regional innovation and suggest important policy implications. |
| Keywords: | Science, Innovation, Regional Advantage, Emerging Technology |
| JEL: | O30 O33 R11 |
| Date: | 2024–10–02 |
| URL: | https://d.repec.org/n?u=RePEc:bsl:wpaper:2024/11 |
| By: | Erik Engberg (Orebro University); Holger Gorg (Kiel Institute for the World Economy); Magnus Lodefalk (Örebro University); Farrukh Javed; Martin Langkvist; Natalia Monteiro; Hildegunn Nordas; Giuseppe Pulito (Rockwool Foundation Berlin); Sarah Schroeder (Aarhus University); Aili Tang (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 groupsof workers. |
| Keywords: | Artificial intelligence; Labour demand; Multi-country firm-level evidence |
| JEL: | E24 J23 J24 N34 O33 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:2414 |
| By: | Tom Broekel; Torben Klarl; ; ; |
| Abstract: | Innovations are widely accepted as fundamental drivers of economic growth by increasing productivity and creating new markets. However, empirical evidence on the long-term relationship between technological progress and economic growth remains scarce, with few studies considering shifts in technologies’ fundamental properties, such as their degree of complexity. Yet, higher levels of complexity are argued to increase technologies’ economic potential, and consequently, ignoring this dimension of technologies provides an incomplete picture of innovations’ growth effects. We address this research gap by exploring the relationship between economic growth and technological complexity over more than 170 years in the United States (US). Utilizing patent data, the concept of the complexity frontier, and partial wavelet analysis, we find that economic growth has not been driven by patented innovation and technological complexity for most of this period. However, since the beginning of the ICT revolution in the 1990s, it has significantly contributed to GDP growth. |
| Keywords: | Innovation, Economic Growth, Technological Complexity, USA, Complexity Frontier, Wavelt Analysis |
| JEL: | O30 O47 N10 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2427 |
| By: | James Bessen; Iain Cockburn; Jennifer Hunt |
| Abstract: | Using our own data on artificial intelligence publications merged with Burning Glass vacancy data for 2007-2019, we investigate whether online vacancies for jobs requiring AI skills grow more slowly in US locations farther from pre-2007 AI innovation hotspots. We find that a commuting zone which is an additional 200km (125 miles) from the closest AI hotspot has 17% lower growth in AI jobs' share of vacancies. This is driven by distance from AI papers rather than AI patents. Distance reduces growth in AI research jobs as well as in jobs adapting AI to new industries, as evidenced by strong effects for computer and mathematical researchers, developers of software applications, and the finance and insurance industry. 20% of the effect is explained by the presence of state borders between some commuting zones and their closest hotspot. This could reflect state borders impeding migration and thus flows of tacit knowledge. Distance does not capture difficulty of in-person or remote collaboration nor knowledge and personnel flows within multi-establishment firms hiring in computer occupations. |
| Keywords: | Technological change, Economic geography, Growth |
| Date: | 2024–10–01 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2038 |
| By: | Marco Cucculelli (Universita' Politecnica delle Marche, Dipartimento di Scienze economiche e sociali); Noemi Giampaoli (Polytechnic University of Marche, Department of Economics and Social Sciences,); Matteo Renghini (LUISS "Guido Carli" University, Department of Economics and Finance) |
| Abstract: | Assessing the presence and distribution of strategic and net-zero technologies in companies is crucial for European competitiveness. However, due to the complexity and evolving nature of these technology areas, this is a challenging task. This paper presents a process for identifying and mapping strategic and net-zero technologies (as described in the Strategic Technologies for Europe Platform (STEP) and the Net-Zero Industry Act (NZIA)) in European companies. STEP and NZIA technologies are identified using text mining techniques based on the titles and abstracts of patents filed with the EPO and retrieved in PATSTAT for the years 2002 to 2022. The paper describes the classification process of STEP and NZIA technologies based on IPC codes of file patents. The IPC codes were then matched with the patent portfolio of almost 100, 000 European companies to determine the company's technological profile and the distribution of these technologies by sector, geographic area, and company characteristics in the European panorama. |
| Keywords: | PATSTAT, Orbis, Patents, Text mining, Innovation, STEP, NZIA, Unconventional data |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:anc:wmofir:188 |
| By: | Elodie Andrieu; John Morrow |
| Abstract: | How do firms diffuse resources and do they spillover outside headquarter intensive areas? We show R&D subsidies induce French firms to hire new workers, often in new establishments and commuting zones. Using subsidy induced labor demand shocks and past employment patterns, we estimate a within industry spillover elasticity of .26 to non-subsidy firms, rising to .35 for openings outside of headquarter areas. Spillovers are also significant across firm branches and for firms. While subsidies are nominally awarded to headquarters, firms expand to distribute spillovers more broadly. |
| Keywords: | multi-establishment firms, subsidies, directed growth, spillovers |
| Date: | 2024–09–24 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2035 |
| By: | Christophe André; Peter Gal |
| Abstract: | This review takes stock of the large body of evidence on aggregate productivity growth, its structural drivers, and the role of a wide range of policies. It aims to synthesise evidence on how public policies can promote productivity through their impacts on both the incentives and the capabilities of businesses and workers, taking account of different specificities of firms at the frontier and below, and integrating complementarities across policy areas. It also identifies gaps in knowledge, thus offering potential directions for future work. |
| Keywords: | Economic policy, Efficiency frontier, Entrepreneurship, Firm Performance, Intangible capital, Investment, Productivity, Technological diffusion |
| JEL: | D24 E22 E24 E6 J24 L25 L26 L5 O31 O32 O33 O38 O47 |
| Date: | 2024–10–07 |
| URL: | https://d.repec.org/n?u=RePEc:oec:ecoaaa:1822-en |
| By: | Fitzgerald, Jack |
| Abstract: | Moscona & Sastry (2023, Quarterly Journal of Economics) - henceforth MS23 - find that cropland values are significantly less damaged by extreme heat exposure (EHE) when crops are more exposed to technological innovation. However, MS23's 'innovation exposure' variable does not measure innovation, instead proxying innovation using a measure of crops' national heat exposure. A re-examination of MS23's replication data - which permits a close but inexact reproduction of MS23's published findings - shows that this proxy moderates EHE impacts for reasons unrelated to innovation. The proxy is practically identical to local EHE, so MS23's models examining interaction effects between their proxy and local EHE effectively interact local EHE with itself. I document extensive evidence that MS23's findings on 'innovation exposure' are simply artefacts of nonlinear impacts in local EHE, and uncover robustness issues for other key findings. I then construct direct measures of innovation exposure from MS23's crop variety and patenting data. Replacing MS23's proxy with these direct innovation measures decreases MS23's moderating effect estimates by at least 99.8% in standardized units; none of these new estimates are statistically significantly different from zero. Similar results arise from an instrumental variables strategy that instruments my direct innovation measures with MS23's heat proxy. These results cast doubt on the general capacity for market innovations to mitigate agricultural damage from climate change. |
| JEL: | O31 Q10 Q54 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:i4rdps:158 |
| By: | Giuseppe Berlingieri; Filippo Boeri; Danial Lashkari; Jonathan Vogel |
| Abstract: | We study capital-skill complementarity in a multi-sector framework featuring firm-specific, multi-factor production functions and allowing for firm-specific factor-price wedges. We characterize the elasticity of the skill premium to the price of capital equipment in terms of firm-level elasticities of substitution across factors, elasticities of substitution across firms and sectors, and factor intensities. Using French data, we provide credible identification of these firm-level elasticities. Combining these elements we offer the first identification of aggregate capital-skill complementarity that allows for arbitrary trends in the unobservable skill-bias of productivity at the firm, industry, and aggregate levels. We find an economically and statistically significant degree of aggregate capital-skill complementarity, but this force alone is insufficient to generate the full increase in the relative demand for high-skilled workers observed in the data. There is a substantial role for skill-augmenting technical change not embodied in capital equipment. |
| JEL: | E10 E23 E25 J30 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33000 |
| By: | Grimaud, André; Gray, Elie |
| Abstract: | We formalize inter-sectoral knowledge diffusion in a standard fully endogenous Schumpeterian growth model. Each sector is simultaneously sending and receiving knowledge; thereby, to produce new knowledge, the research and development activity of each sector draws from a pool of knowledge which stems from this diffusion. This enables us to revisit the scale effects issue by revealing how this property (inconsistent with empirical evidence) relates with knowledge diffusion (the importance of which is empirically highlighted). We show that suppressing knowledge diffusion across sectors is a sufficient but not necessary condition for obtaining scale-invariancy. Then, we identify several sets of assumptions which enable us to obtain models which are reasonably consistent with empirical evidence both on scale effects and how knowledge diffuses in the economy. Specifically, these models do not exhibit scale effects (or at least not significant ones) while considering various scope of knowledge diffusion (including possible occurrence of general-purpose technologies). |
| Keywords: | Schumpeterian growth theory, Scale effects, Knowledge diffusion, Knowledge; spillovers, Non rivalry, echnological distance |
| JEL: | O30 O31 O33 O40 O41 |
| Date: | 2024–09–20 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:129742 |
| By: | Sanduku Mulumba; Lawrence Edwards; David Fadiran |
| Abstract: | In this paper, we use the new economic geography (NEG) framework to estimate the extent to which spatial wage disparities in the South African manufacturing sector are an outcome of economic forces such as market access. To test the relationship, we use the anonymized tax data on employers and employees made available by the South African Revenue Service and National Treasury in collaboration with UNU-WIDER. We first document the key stylized facts that characterize the spatial distribution of wages across regions in South Africa using exploratory spatial data analysis (ESDA) techniques. |
| Keywords: | Wage differentials, Spatial econometrics, Regional economics, Income distribution, Manufacturing industries, Wages, Spatial inequality, Manufacturing firms, Estimation theory |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:unu:wpaper:wp-2024-52 |
| By: | Ciarli, Tommaso; Madariaga Espinoza, Andrés; Foster-McGregor, Neil |
| Abstract: | This report documents global shifts in of industrial policy objectives and the rationales behind public intervention to address them. Drawing from a selected sample of policy documents from international organizations and countries with literature on innovation and technical change, this report presents a classification of objectives and rationales. This classification is used to code systematically the academic literature on industrial policy to analyse changes in objectives and rationales in publications on countries of different income groups. The findings show increased attention to social challenges with respect to economic objectives, especially in lower-income countries, while in high-income countries the shift is towards strategic objectives. There has, however, been limited change in rationales. There is also greater coherence between objectives and rationales for policy intervention in the discussion on specific instruments. Based on this evidence, it is suggested that more careful analysis of the rationales for public intervention is needed within existing frameworks and strategic thinking on industrial policies with a view to designing industrial strategies that are time consistent and systematically take into account the synergies and tensions between objectives. |
| Date: | 2024–09–10 |
| URL: | https://d.repec.org/n?u=RePEc:ecr:col022:80651 |