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on Technology and Industrial Dynamics |
| By: | Daniele Angelini (University of Konstanz) |
| Abstract: | Population aging affects the relative supply of inputs in the economy altering the in-centives to adopt different types of technology. Empirically, I document a hump-shaped relation between the age of the population and the adoption of new-technology proxied by the ICT capital share. To explain the non-monotonic relationship and identify the mech-anisms at play, I build a dynamic general equilibrium model with endogenous technology and R&D-driven technological progress. New-technology is defined as a labor-saving (capital-intensive) technology requiring skills to be used. An increase in the capital-to-labor ratio driven by population aging increases new-technology adoption while the increasing scarcity of young workers that have higher incentives to acquire the comple-mentary skills to new-technology reduces it. The model, calibrated to fit European data, shows that the demographic structure of the population is a major determinant of tech-nology adoption. Population aging explains almost half of the increase in new-technology adoption in the period 1995-2020 and it determines its reduction in the period 2020-2045. A decomposition exercise shows that population aging is a primary source of the increase in the skill premium explaining a larger share of its increase than technological progress. |
| Keywords: | Automation, Demographic change, Human capital, Inequality, R&D, OLG |
| JEL: | J11 J24 J26 J31 E25 H23 O31 O33 |
| Date: | 2023–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:knz:dpteco:2301&r=tid |
| By: | Anthony Krakah (Ghana Statistical Service); Gonzague Vannoorenberghe (UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES)) |
| Abstract: | We analyze how the spatial concentration of economic activity affects innovation among firms in Ghana. We use the 2014 census of all establishments to map economic activity at a precise geographic level and the responses to a detailed survey of more than 5000 firms to capture measures of innovation and firm-level characteristics. We find a strong positive effect of the overall density of economic activity on innovation (urbanization economies) but a negative effect of the density of employment in an establishment’s sector (localization economies). Several questions in the survey allow us to address the issue of endogeneity and shed some light on the mechanisms. We control for many firm characteristics and confirm our results on a subsample of establishments declaring that their location is that of their founder’s origin, i.e. firms with a plausibly exogenous geographic location. We find that firms in regions with denser economic activity report less problems to access funding and knowledge, while the presence of firms in the same sector is associated with more uncertainty about the gains from innovating. |
| Keywords: | innovation, development, localization, urbanization, externalities, Ghana |
| JEL: | R10 R11 R12 O14 O18 |
| Date: | 2023–02–13 |
| URL: | http://d.repec.org/n?u=RePEc:ctl:louvir:2023005&r=tid |
| By: | Lionel Fontagné; Ariell Reshef; Gianluca Santoni; Giulio Vannelli |
| 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. Our main contribution is to highlight the indirect effect of robotization on relative demand for labor via GVC integration. To do this, we develop a methodology to separately account for robots in the total capital stock. Increases in upstream, forward GVC participation directly reduce labor shares, mostly through reductions in fabrication, but also via management, marketing and R&D 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”. We also study novel channels through which rapid robotization in China shaped robotization in Europe and, therefore, GVC participation. This highlights an understudied way by which the global integration of China has affected relative demand for labor in its trading partners. |
| Keywords: | Labor Share;Functional Specialization;Global Value Chains;Upstreamness;Technological Change;Automation;Robots |
| JEL: | E25 F14 F16 |
| Date: | 2023–03 |
| URL: | http://d.repec.org/n?u=RePEc:cii:cepidt:2023-05&r=tid |
| By: | Lorenzo Cresti; Maria Enrica Virgillito |
| Abstract: | Focusing on labour requirements incorporated into GVCs, in the following, we develop a novel, non conventional measure of learning capabilities, represented by knowledge embodied along the division of labour within global production networks. In order to capture the division of labour, and the ensuing division of embodied knowledge, we move from monetary flows of production, or value-added embodied, to labour embodied in the I-O linkages. We focus on mature economies as offshoring has been particularly in place there. After constructing a new indicator of Bilateral Net Labour Dependence, we estimate its relationship with a measure of performance of industries, namely, labour productivity, seeking to challenge the established findings generally reporting a positive effect of GVCs participation for sector-level productivity. Our conjecture is that being in a weak position in terms of (net) labour provision results in an overall weakening of the capabilities of the loosing productive structure. We corroborate the conjecture with a panel analysis of OECD countries and industries for the time period 2000-2014. |
| Keywords: | Input-output; global value chains; international division of labour; dependency theory. |
| Date: | 2023–02–24 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2023/10&r=tid |
| By: | Martin Ho; Henry CW Price; Tim S Evans; Eoin O'Sullivan |
| Abstract: | Is calendar time the true clock of innovation? By combining complexity science with innovation economics and using vaccine datasets containing over three million citations and eight regulatory authorisations, we discover that calendar time and network order describe innovation progress at varying accuracy. First, we present a method to establish a mathematical link between technological evolution and complex networks. The result is a path of events that narrates innovation bottlenecks. Next, we quantify the position and proximity of documents to these innovation paths and find that research, by and large, proceed from basic research, applied research, development, to commercialisation. By extension, we are able to causally quantify the participation of innovation funders. When it comes to vaccine innovation, diffusion-oriented entities are preoccupied with basic, later-stage research; biopharmaceuticals tend to participate in applied development activities and clinical trials at the later-stage; while mission-oriented entities tend to initiate early-stage research. Future innovation programs and funding allocations would benefit from better understanding innovation orders. |
| Date: | 2023–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2302.13076&r=tid |
| By: | Arnab Bhattacharjee; Ornella Maietta; Fernanda Mazzotta |
| Abstract: | Innovativeness of a firm improves not only its own survival chances but can also generate externalities on its neighboring firms. We empirically examine the role of agglomeration economies in how innovativeness affects firm survival in Southern Italy, using spatial weights to model spillovers. Spatial Durbin probit model estimates confirm that innovation is a determinant of firm survival not only for firms that are themselves innovative but also ones located close to other innovative firms. Definition of spatial scale and weight plays an important role. Spillover benefits are enhanced by agglomeration economies, but only at a very local scale. |
| Keywords: | Firm survival, Spatial models, Innovation, Spillovers, Southern Italian SMEs |
| JEL: | L20 O3 D22 C21 C41 |
| Date: | 2023–02 |
| URL: | http://d.repec.org/n?u=RePEc:nsr:niesrd:546&r=tid |
| By: | Andrés Mauricio Gomez-Sanchez (Universidad del Cauca, Colombia.); Juan A. Máñez Castillejo (Universidad de Valencia and ERICES, Valencia, España.); Juan Alberto Sanchis-Llopis (Universidad de Valencia and ERICES, Valencia, España.) |
| Abstract: | The objective of this work is to explore the impact of ICT (using several indicators) on the firm’s export decision for Colombian manufacturing. To study this decision, we specify a model that accounts for sunk costs, firm previous experience in exporting and the impact of importing on exporting, and we estimate a dynamic (panel data) discrete model for the decision to export. To undertake this study, we merge three data bases at the firm level for Colombia: the Annual Manufacturing Survey (EAM), the Technological Development and Innovation Survey (EDIT) and the Annual ICT Manufacturing Survey (EAM-TIC), for the period 2013-2016. The results we obtain, show that ICT has a significant and positive impact on firm’s propensity to export, regardless the ICT category examined. Our work also confirms the existence of persistence on firm’s exports, self-selection, and depreciation of export experience. This evidence contributes to the scarce empirical literature on this topic for emerging economies, such as Colombia. |
| Keywords: | ICT, Exports, Self-Selection, Panel Data, Emerging Economies. |
| JEL: | L16 L96 F14 C23 D22 |
| Date: | 2023–03 |
| URL: | http://d.repec.org/n?u=RePEc:eec:wpaper:2303&r=tid |
| By: | Andrew Green; Lucas Lamby |
| Abstract: | This report provides representative, cross-country estimates of the artificial intelligence (AI) workforce across OECD countries. The AI workforce is defined as the subset of workers with skills in statistics, computer science and machine learning who could actively develop and maintain AI systems. For countries that wish to be at the forefront of AI development, understanding the AI workforce is crucial to building and nurturing a talent pipeline, and ensuring that those who create AI reflect the diversity of society. This report uses data from online job vacancies to measure the within-occupation intensity of AI skill demand. The within-occupation AI intensity is then weighted to employment by occupation in labour force surveys to provide estimates of the size and growth of the AI workforce over time. |
| Keywords: | Artificial Intelligence |
| JEL: | J21 J23 J24 J31 J44 |
| Date: | 2023–02–23 |
| URL: | http://d.repec.org/n?u=RePEc:oec:elsaab:287-en&r=tid |
| By: | Billington, Stephen D.; Lane, Joe |
| Abstract: | Did the outbreak of the French Revolutionary and Napoleonic Wars influence technical change during the Industrial Revolution? We address this question by investigating an instance of state intervention into the market for inventions from 1793-1820: the introduction of a new proviso into British patents compelling inventors to supply the military, and also attracting military inventions from outside the patent system. We present new patent data alongside previously unused archival evidence to argue that the state's intervention helped direct technical change in Britain. Our evidence provides additional support for the military-demand-induced hypothesis as a credible explanation for Britain's ongoing industrialisation. |
| Keywords: | Industrial Revolution, Institutions, Invention, Patents |
| JEL: | N43 N73 O31 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:qucehw:202305&r=tid |
| By: | Borrás, Susana (Copenhagen Business School); Haakonsson, Stine (Copenhagen Business School); Taudal Poulsen, René (Copenhagen Business School); Pallesen, Trine (Copenhagen Business School); Hendriksen, Christian (Copenhagen Business School); Somavilla, Lucas (University College London); Kugelberg, Susanna (Copenhagen Business School); Larsen, Henrik (Copenhagen Business School); Gerli, Francesco (Copenhagen Business School) |
| Abstract: | Although public sector organizations (such as municipalities, executive agencies, and publicly controlled utilities), are pivotal in sustainability transitions, a conceptualization of their transformative capacity is underdeveloped. Several strands of literature have started to pay attention to the concept of ‘capacity’, but these remain disjointed. Conducting a literature review, the present paper identifies variations and understudied aspects of the concept. It proposes a holistic conceptual framework based on three elements: their organizational roles, resources, and skills. Hence, the transformative capacity of a public sector organization is defined by the interaction between its purposeful enactment of various roles when exercising change agency, and by the deployment and development of its dynamic skills, when mobilizing the internal and external resources at its disposal. The framework offers the opportunity for a granular understanding of what specific combinations of those elements are at play in the implementation of highly diverse sustainability actions. This has important theoretical and empirical implications, as well as practical implications for more targeted transformative capacity-building efforts. |
| Keywords: | sustainability transitions; eco-innovation; transformative innovation; socio-technical systems; climate; capacity; dynamic capabilities; climate; governance |
| JEL: | O31 O33 O38 Q01 Q28 Q58 Z18 |
| Date: | 2023–02–22 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:lucirc:2023_002&r=tid |
| By: | Fabio Manca |
| Abstract: | This study responds to six key questions about the impact that the demand for Artificial Intelligence (AI) skills is having on labour markets. What are the occupations where AI skills are most relevant? How do different AI-relevant skills combine in job requirements? How quickly is the demand for AI-related skills diffusing across labour markets and what is the relationship between AI skill demands and the demand for cognitive skills across jobs? Finally, are AI skills leading to a wage premium and how different are the wage returns associated with AI and routine skills? To shed light on these aspects, this study leverages Natural Language Processing (NLP) algorithms to analyse the information contained in millions of job postings collected from the internet. |
| Keywords: | artificial intelligence, education, labour market, skills, technology |
| JEL: | I26 J01 O14 O33 |
| Date: | 2023–02–23 |
| URL: | http://d.repec.org/n?u=RePEc:oec:elsaab:286-en&r=tid |