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on Technology and Industrial Dynamics |
| By: | Hyejin Park; Younghun Shim |
| Abstract: | This paper develops an occupation-level measure of Capital-Embodied Innovation (CEI) by matching patents with capital goods based on their text similarity. The impact of CEI on labor demand is heterogeneous, depending on the similarity between capital and occupational tasks. Specifically, CEI associated with task-similar capital reduces the relative labor demand, whereas CEI related to task-dissimilar capital raises it. Between 1980 and 2015, capital used by high-wage occupations experienced more innovations in task-dissimilar capital and fewer in task-similar capital. CEI can explain 51% of the relative wage growth in high-wage occupations and significantly contributes to routine- and abstract-biased labor market changes. |
| Keywords: | capital-embodied innovation, text analysis of patents, substitution between labor and capital |
| JEL: | J24 J31 O33 O47 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_11037&r=tid |
| By: | Pelin Ozgul; Marie-Christine Fregin; Michael Stops; Simon Janssen; Mark Levels |
| Abstract: | Artificial Intelligence (AI) will change human work by taking over specific job tasks, but there is a debate which tasks are susceptible to automation, and whether AI will augment or replace workers and affect wages. By combining data on job tasks with a measure of AI susceptibility, we show that more highly skilled workers are more susceptible to AI automation, and that analytical non-routine tasks are at risk to be impacted by AI. Moreover, we observe that wage growth premiums for the lowest and the highest required skill level appear unrelated to AI susceptibility and that workers in occupations with many routine tasks saw higher wage growth if their work was more strongly susceptible to AI. Our findings imply that AI has the potential to affect human workers differently than canonical economic theories about the impact of technology on work these theories predict. |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2404.06472&r=tid |
| By: | KOUAKOU, Dorgyles C.M.; SZEGO, Eva |
| Abstract: | This paper employs graph theory to assess the extent of integration of artificial intelligence (AI) technologies within defense activities and investigates how the performance of the national innovation system (NIS) influences this integration. The analysis utilizes data from 33 countries with defense industries, observed from 1990 to 2020. Empirical findings indicate that the United States (U.S.) leads globally, with a significant gap between the U.S. and other countries. NIS performance increases the level of integration of AI technologies in defense activities, suggesting that policies aimed at strengthening NIS performance should have positive externalities on defense activities in terms of integrating AI technologies. Technological diversification, knowledge localization, and originality are key dimensions of NIS performance that significantly enhance the integration of AI technologies within defense activities. They exhibit similar average marginal effects, suggesting comparable impacts. The cycle time of technologies has an inverted-U shaped relationship with the level of integration. |
| Keywords: | Integration of AI technologies; Defense activities; National innovation system |
| JEL: | L64 O31 O34 O38 |
| Date: | 2024–04–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120617&r=tid |
| By: | Matte Hartog; Andres Gomez-Lievano; Ricardo Hausmann; Frank Neffke |
| Abstract: | Between the mid-19th and mid-20th century, the US transformed from an agri- cultural economy to the frontier in science, technology and industry. We study how the US transitioned from traditional craftsmanship-based to today’s science-based innovation. To do so, we digitize half a million pages of patent yearbooks that describe inventors, organizations and technologies on over 1.6M patent and add demo- graphic information from US census records and information on corporate research activities from large-scale repeated surveys on industrial research labs. Starting in 1920, the 19th-century craftsmanship-based invention was, within just 20 years, overtaken by a rapidly emerging new system based on teamwork and a new specialist class of inventors, engineers. This new system relied on a social innovation: industrial research labs. These labs supported high-skill teamwork, replacing the collaborations within families with professional ties in firms and industrial research labs. This shift had wide-ranging consequences. It not only altered the division of labor in invention, but also reshaped the geography of innovation, reestablishing large cities as epicenters of technological progress and introduced new barriers to patenting for women and foreign-born inventors that have persisted into the 21st century. |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2408&r=tid |
| By: | Iñaki Aldasoro; Sebastian Doerr; Leonardo Gambacorta; Daniel Rees |
| Abstract: | This paper studies the effects of artificial intelligence (AI) on sectoral and aggregate employment, output and inflation in both the short and long run. We construct an index of industry exposure to AI to calibrate a macroeconomic multi-sector model. Building on studies that find significant increases in workers' output from AI, we model AI as a permanent increase in productivity that differs by sector. We find that AI significantly raises output, consumption and investment in the short and long run. The inflation response depends crucially on households' and firms' anticipation of the impact of AI. If they do not anticipate higher future productivity, AI adoption is initially disinflationary. Over time, general equilibrium forces lead to moderate inflation through demand effects. In contrast, when households and firms anticipate higher future productivity, inflation rises immediately. Inspecting individual sectors and performing counterfactual exercises we find that a sector's initial exposure to AI has little correlation with its long-term increase in output. However, output grows by twice as much for the same increase in aggregate productivity when AI affects sectors producing consumption rather than investment goods, thanks to second round effects through sectoral linkages. We discuss how public policy should foster AI adoption and implications for central banks. |
| Keywords: | artificial intelligence, generative AI, inflation, output, productivity, monetary policy |
| JEL: | E31 J24 O33 O40 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:1179&r=tid |
| By: | Leogrande, Angelo |
| Abstract: | In the following article I analyze the determinants of regular internet users in the Italian regions. The data is analyzed both in terms of static analysis and also through the application of the k-Means algorithm optimized with the Elbow method. Subsequently, an econometric model is presented for estimating regular internet users in the Italian regions based on variables that reflect the state of technological innovation and digital culture. The results are analyzed and discussed in light of the implications that digitalisation has for triggering economic growth. |
| Keywords: | Innovation, Innovation and Invention, Management of Technological Innovation and R&D, Technological Change, Intellectual Property and Intellectual Capital |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2024–04–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120612&r=tid |
| By: | Traverso, Silvio; Vatiero, Massimiliano; Zaninotto, Enrico |
| Abstract: | This study examines the association between investments in automation technologies and employment outcomes at the firm level, utilizing a panel dataset of about 10, 450 Italian firms. Focusing on the proliferation of non-standard, flexible labor contracts introduced by labor market reforms in the 2000s, we identify a positive relationship between automation investments and the adoption of flexible labor arrangements. With the aid of a conceptual framework, we interpret these findings as evidence of complementarity between flexible capital, represented by automation technologies, and flexible labor, manifested through non-standard contractual arrangements. This complementarity is crucial for enhancing operational flexibility, a critical determinant of firm performance in the modern market environment. However, while this adaptability is beneficial for firms, it raises concerns about job security, the potential for lower wages among workers, and the reduction of workers' incentives to invest in human capital. In terms of policy implications, our analysis underscores the need for measures that safeguard workers' interests without compromising the efficiency gains from automation. |
| Keywords: | Automation, Labor Contracts, Flexible Capital, Flexible Labor |
| JEL: | D20 J30 J41 K31 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:1425&r=tid |
| By: | Abe C. Dunn; Lasanthi Fernando; Eli Liebman |
| Abstract: | While technological innovation is believed to be a key driver of spending growth, measuring this relationship is challenging. We address this challenge using a large database of cost-effectiveness studies, which we use to develop proxy measures of inno- vation for specific conditions. We connect to data on spending growth at the condition level from the Bureau of Economic Analysis (BEA) Health Care Satellite Account (HCSA). We find our proxy for innovation is significantly related to spending growth, even after accounting for a number of factors. We estimate that about 18 percent of real spending growth per capita is explained by our proxy for innovation, which we argue is likely a lower bound for the actual contribution of technology on spending growth. |
| JEL: | E01 I10 O3 |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:bea:papers:0121&r=tid |
| By: | Richhild Moessner |
| Abstract: | This paper provides ex-post empirical evidence on the effects of green technology support policies, in comparison with other climate policies, on carbon dioxide emissions at the aggregate national level. The paper uses cross-country dynamic panel estimation for a sample of 38 countries over the period from 1990 to 2015, controlling for macroeconomic determinants such as economic development, GDP growth, urbanisation and the energy mix. It uses a new index which measures the strength of green technology support policies, including separate sub-indices for the public support of expenditure on research and development of low-carbon energy technologies, and for the support of the adoption of wind energy and of solar energy. We find that an increase by one index point of the green technology support policy index leads to a significant reduction of around 0.9% in CO2 emissions per capita in the short run, and of around 3.7% in the long run. An increase by one index point of the green R&D expenditure support policy index leads to a significant reduction of around 0.4% in CO2 emissions per capita in the short run, and of around 1.7% in the long run. An increase by one index point of the wind energy support policy index leads to a significant reduction of around 0.5% in CO2 emissions per capita in the short run, and of around 2.1% in the long run. |
| Keywords: | green technology support policies, solar energy, wind energy, climate policigreen technology support policies, solar energy, wind energy, climate policies, carbon tax, carbon dioxide, climate changees, carbon tax, carbon dioxide, climate change, emissions |
| JEL: | Q00 Q48 Q58 Q55 Q40 Q50 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_11047&r=tid |
| By: | Giovanni Dosi; Marcelo C. Pereira; Andrea Roventini; Maria Enrica Virgillito |
| Abstract: | This chapter presents an application of the multi-sector labour augmented K+S agent-based model to two contemporary challenges in political economy, namely declining unionization and rising inequality, with reference to mid-term evidence in the US. What has been the effect of declining unionization? We focus, as an example, upon the introduction of legislations such as Right- to-Work (RTW) laws, disfavouring union firms and the way they affected the dynamics of the labour market. The model proves to be a solid and rich tool in order to confront different scenarios emerging out of the interaction of an endogenous dynamic competition between union and non union firms, the latter arriving at a specific time, mimicking the exogenous introduction of RTW laws. The arrival of non union firms induces direct first-order effects, as rising inequality at the workplace and macro level, but also, indirect, second order effects, as lower rates of employment absorption and consumption patterns skewed toward wealthy, luxury consumption goods. In that, complexity economics proves to be a promising avenue to incorporate and confront the grand challenges of contemporary capitalism. |
| Keywords: | Complexity, Capitalism, Socio-economic structure, Macro-evolutionary agent-based models |
| Date: | 2024–04–24 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2024/13&r=tid |