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on Technology and Industrial Dynamics |
| By: | Koike Yasutaka-Mori; Toshitaka Maruyama; Koki Okumura |
| Abstract: | This paper develops an endogenous growth model that incorporates a frictional inventor market and examines the allocation of inventors across firms, knowledge diffusion, and its impact on growth. In our model, inventors play dual roles: they engage in in-house R&D and transfer knowledge from previous employers to new ones when changing jobs. Using an administrative panel dataset on German inventors matched to their employing establishments and patents, we find that, relative to general workers, inventors are more likely to transition to less productive establishments and suffer a higher wage growth via the transition. We also find that the knowledge base of establishments measured by patents grows faster when a significant proportion of their inventors originate from establishments possessing a larger knowledge base. We then calibrate the model to reflect these empirical findings and examine the effects of innovation policy. While subsidies to frontier firms discourage knowledge diffusion from these firms to technologically lagging firms, these subsidies also encourage innovation within frontier firms. The former negative effect dominates in the short term, but the latter positive effect dominates in the long run. |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1244&r= |
| By: | Carlo Altomonte; Nevine El-Mallakh; Tommaso Sonno |
| Abstract: | We build a novel worldwide database merging information on patent-citations of firms paired with information on firms' affiliation to Business Groups (BGs). We exploit these data to document how BGs appropriate knowledge through standalone firm acquisition. First, we confirm that innovative standalone firms have a higher probability of becoming part of a BG. Second, we document how BGs tend to acquire firms that are on an upward trend in patents and citations. We also show that innovating activity significantly deteriorates post-acquisition, particularly for firms with high-quality, cited patents. Third, we show that such a deterioration in innovation activity is driven by acquired firms patenting within the same technological classes of the acquiring BG, while the latter does not hold for acquired firms patenting in different technologies than the BG's. We also find that acquisitions occurring in environments characterized by higher market concentration and more mature leading firms are associated with a relatively more pronounced reduction in innovation. These results generalize the defensive acquisition narrative, suggesting that BGs leverage these transactions as a strategic manoeuvre to solidify their market position in the face of potential competition. |
| Keywords: | business groups, innovation |
| Date: | 2024–04–30 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1996&r= |
| By: | Bloom, David E. (Harvard School of Public Health); Prettner, Klaus (Vienna University of Economics and Business); Saadaoui, Jamel (Université de Strasbourg); Veruete, Mario (Quantum DataLab) |
| Abstract: | How will the emergence of ChatGPT and other forms of artificial intelligence (AI) affect the skill premium? To address this question, we propose a nested constant elasticity of substitution production function that distinguishes among three types of capital: traditional physical capital (machines, assembly lines), industrial robots, and AI. Following the literature, we assume that industrial robots predominantly substitute for low-skill workers, whereas AI mainly helps to perform the tasks of high-skill workers. We show that AI reduces the skill premium as long as it is more substitutable for high-skill workers than low-skill workers are for high-skill workers. |
| Keywords: | automation, artificial intelligence, ChatGPT, skill premium, wages, productivity |
| JEL: | J30 O14 O15 O33 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16972&r= |
| By: | Can Sever |
| Abstract: | Violent conflicts are typically associated with a long-lasting drag on economic output, yet establishing causality based on macro-data remains as a challenge. This study attempts to build causality in the conflict-growth nexus by exploiting within-country variation across industries’ technological intensity. It identifies a channel through which conflicts can impact growth, i.e., by hindering R&D activities. The analysis is based on industry-level data from two-digit manufacturing industries for a large sample of countries over the last four decades. The results show that conflicts lead to a decline in labor productivity growth, particularly in industries with higher technological intensity. The estimated magnitude of the differential effect of conflicts on labor productivity growth in high-tech industries is large. Moreover, the additional labor productivity loss in those industries in the years of conflicts does not seem to be offset in the post-conflict period neither. The findings offer insight into the observed patterns of durable declines in income in the aftermath of conflicts, considering the role of technological progress and innovation in long-term economic growth. |
| Keywords: | Conflict; war; R&D; innovation; high-tech; economic growth and development |
| Date: | 2024–05–10 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:2024/098&r= |
| By: | Egana-delSol, Pablo (Universidad Adolfo Ibañez); Micco, Alejandro (University of Chile) |
| Abstract: | The employment to output elasticity has risen from 0.65 during the 1960s and 1970s to 1.25 in the last two decades. We study the role of recent technological change in the evolution of this elasticity along the business cycle. Using the Covid-19-induced shock and an instrumental variable approach as sources of identification, we find that recent technologies augment the employment to output elasticity. We find that employment in sectors characterized with occupations with a high risk of automation are the most affected and that this effect is larger in sectors that have undergone a technology-capital deepening process in the last decades. |
| Keywords: | technological change, automation, employment to output elasticity, labor markets |
| JEL: | O33 E32 J23 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp17003&r= |
| By: | Yibo Qiao; Nicola Cortinovis; Andrea Morrison; |
| Abstract: | This article investigates how MNEs influence the export behavior of domestic firms in the context of China. We conceptually disentangle different MNE spillovers related to local export dynamics, linking in a unique framework specific spillover mechanisms, channels, activation conditions and type of knowledge conveyed. Empirically, our analysis relies on a panel dataset containing all Chinese manufacturing firms in the period 2000-2007. The results show that relatedness linkages matter in the context of export quantity, while forward-backward linkages matter for the sophistication of export. These findings suggest that relatedness linkages convey mainly marketing-related knowledge spillovers, while forward-backward linkages are diffusing mainly product-related knowledge spillovers. |
| Keywords: | Relatedness, forward-backward linkages, multinational enterprises, export, innovation, China |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2415&r= |
| By: | Daron Acemoglu |
| Abstract: | This paper evaluates claims about large macroeconomic implications of new advances in AI. It starts from a task-based model of AI’s effects, working through automation and task complementarities. So long as AI’s microeconomic effects are driven by cost savings/productivity improvements at the task level, its macroeconomic consequences will be given by a version of Hulten’s theorem: GDP and aggregate productivity gains can be estimated by what fraction of tasks are impacted and average task-level cost savings. Using existing estimates on exposure to AI and productivity improvements at the task level, these macroeconomic effects appear nontrivial but modest—no more than a 0.66% increase in total factor productivity (TFP) over 10 years. The paper then argues that even these estimates could be exaggerated, because early evidence is from easy-to-learn tasks, whereas some of the future effects will come from hard-to-learn tasks, where there are many context-dependent factors affecting decision-making and no objective outcome measures from which to learn successful performance. Consequently, predicted TFP gains over the next 10 years are even more modest and are predicted to be less than 0.53%. I also explore AI’s wage and inequality effects. I show theoretically that even when AI improves the productivity of low-skill workers in certain tasks (without creating new tasks for them), this may increase rather than reduce inequality. Empirically, I find that AI advances are unlikely to increase inequality as much as previous automation technologies because their impact is more equally distributed across demographic groups, but there is also no evidence that AI will reduce labor income inequality. Instead, AI is predicted to widen the gap between capital and labor income. Finally, some of the new tasks created by AI may have negative social value (such as design of algorithms for online manipulation), and I discuss how to incorporate the macroeconomic effects of new tasks that may have negative social value. |
| JEL: | E24 J24 O30 O33 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32487&r= |
| By: | Sara Calligaris; Chiara Criscuolo; Luca Marcolin |
| Abstract: | Relying on a novel dataset which combines balance sheet data on firms, patents, and industry-level proxies of technology for 25 countries in the period 2001-2014, we document an increase in mark-ups over time, mainly driven by firms in the top half of the mark-up distribution, and a significant and increasing "mark-up gap" between firms in digital intensive and less digital intensive industries. Second, we show that the intangible components of the digital transformation, matter above all others for firm mark-up, and that this is not explained by the industry's fixed-cost structure, concentration, openness to trade and product market regulation. |
| Keywords: | mark-ups, market power, digitalisation, intangible assets |
| Date: | 2024–04–29 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1994&r= |
| By: | Kässi, Otto |
| Abstract: | Abstract We examine the effects of generative artificial intelligence (GenAI) on the labor market, specifically focusing on the impact of ChatGPT on job demand. Using micro-level data from one of the largest online labor platforms, we classify new job postings into three categories: substitutable, augmenting, and unaffected. We apply a difference-in-differences method to explore how ChatGPT’s deployment has altered labor demand within these categories. Our findings show a slight decrease in openings for substitutable jobs, where GenAI can fully perform tasks without loss of quality. However, there is an increase in demand for augmenting and unaffected jobs, which either benefit from faster task completion due to GenAI assistance or remain unchanged by it. The data indicates that ChatGPT’s introduction has not uniformly decreased labor demand but rather redistributed it, leading to growth in some sectors and declines in others. |
| Keywords: | Generative artificial intelligence, Technological change, Labour demand, Labour markets |
| JEL: | J23 J24 O33 |
| Date: | 2024–06–06 |
| URL: | https://d.repec.org/n?u=RePEc:rif:briefs:136&r= |
| By: | Humlum, Anders (University of Chicago Booth School of Business); Vestergaard, Emilie (University of Copenhagen) |
| Abstract: | We study the adoption of ChatGPT, the icon of Generative AI, using a large-scale survey experiment linked to comprehensive register data in Denmark. Surveying 100, 000 workers from 11 exposed occupations, we document ChatGPT is pervasive: half of workers have used it, with younger, less experienced, higher-achieving, and especially male workers leading the curve. Why have some workers adopted ChatGPT, and others not? Workers see a substantial productivity potential in ChatGPT but are often hindered by employer restrictions and required training. Informing workers about expert assessments of ChatGPT shifts workers' beliefs and intentions but has limited impacts on actual adoption. |
| Keywords: | technology adoption, labor productivity |
| JEL: | J24 O33 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16992&r= |
| By: | Peretto, Pietro; Valente, Simone |
| Abstract: | We fully characterize the transition to sustained growth of resource-constrained economies using a model of industrialization that reproduces key stylized facts of resource use and prices. Natural scarcity, endogenous demography and innovations generate different growth regimes: knowledge-based innovations can potentially feed productivity growth in the long run, but exhaustible primary inputs and population pressure may halt economic development at earlier stages. Our model reproduces two well-documented empirical regularities -- a U-shaped path of resource prices and a hump-shaped path of resource extraction -- as secular trends that arise across growth regimes. Resource use and prices reach their respective turning points at different stages of development, and we may observe a peak in extraction followed by a long period where both resource use and its market price fall. The decoupling of price and quantity dynamics hinges on general-equilibrium interactions between demography and three sources of endogenous technological change, namely, increases in the mass of intermediate firms, vertical innovations within each intermediate firm, and endogenous extraction costs affected by learning-by-doing in the primary sector. |
| Keywords: | Endogenous Growth, Population, Natural Resources, Sustainability. |
| JEL: | E10 L16 O31 O40 |
| Date: | 2024–04–29 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120828&r= |
| By: | Sandor Juhasz; Zoltan Elekes; Virag Ilyes; Frank Neffke |
| Abstract: | Strong local clusters help firms compete on global markets. One explanation for this is that firms benefit from locating close to their suppliers and customers. However, the emergence of global supply chains shows that physical proximity is not necessarily a prerequisite to successfully manage customer-supplier relations anymore. This raises the question when firms need to colocate in value chains and when they can coordinate over longer distances. We hypothesize that one important aspect is the extent to which supply chain partners exchange not just goods but also know-how. To test this, we build on an expanding literature that studies the drivers of industrial coagglomeration to analyze when supply chain connections lead firms to colocation. We exploit detailed micro-data for the Hungarian economy between 2015 and 2017, linking firm registries, employer-employee matched data and firm-to-firm transaction data from value-added tax records. This allows us to observe colocation, labor flows and value chain connec- tions at the level of firms, as well as construct aggregated coagglomeration patterns, skill relatedness and input-output connections between pairs of industries. We show that supply chains are more likely to support coagglomeration when the industries in- volved are also skill related. That is, input-output and labor market channels reinforce each other, but supplier connections only matter for colocation when industries have similar labor requirements, suggesting that they employ similar types of know-how. We corroborate this finding by analyzing the interactions between firms, showing that supplier relations are more geographically constrained between companies that operate in skill related industries. |
| Keywords: | coagglomeration, labor flow network, skill relatedness, supply chain |
| JEL: | R12 J24 O14 D57 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2416&r= |
| By: | Chu, Angus C.; Peretto, Pietro; Wang, Xilin |
| Abstract: | The goal of this study is to contribute to the debate on the role of government spending in shaping the growth process. We take the analysis in three new directions. First, we investigate the role of government spending in a scale-invariant Schumpeterian model of endogenous innovation. Second, we allow public spending to be the catalyst that precipitates the takeoff of the economy. Third, we postulate a production structure that violates the conventional condition for endogenous growth, namely, that the economy's reduced-form production function must be linear in the accumulated factor. With non-distortionary taxation, increasing productive government spending causes an earlier industrial takeoff and faster economic growth. With distortionary labor-income tax under elastic labor supply, instead, increasing productive government spending has a U-shaped effect on the timing of the industrial takeoff and an inverted-U effect on economic growth. Using cross-country panel data, we document an inverted-U relationship between productive government spending and economic growth. Calibrating the model to US data, we find that raising productive government spending from its historical value to to its growth-maximizing value causes an earlier industrial takeoff by over six decades and an increase in the long-run level of output by 129%. We also explore the robustness of our results under consumption tax and corporate income tax. |
| Keywords: | Government spending; taxation; industrialization; innovation; economic growth |
| JEL: | E6 O3 O4 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120797&r= |
| By: | Tobias Koenig; Thomas Brenner; ; |
| Abstract: | The evolution of industrial clusters has received much attention in the recent literature on evolutionary economic geography (EEG) and regional science. However, scientific results on the influence of different factors on the decline or renewal of mature industrial clusters are scarce. Therefore, this study identifies different factors: preconditions, triggering events and self-augmenting processes, and examines their influence on declining or renewing industrial clusters. In order to obtain transferable results, this meta-analysis is based on 69 individual empirical case studies from different countries and industries. The empirical results show, firstly, that the decline and renewal of industrial clusters is driven by different preconditions, triggering events and self-augmenting processes. Secondly, these factors change over time and may have both positive and negative dimensions. Finally, the decline of industrial clusters is more often associated with unfavorable preconditions and triggering events, while self- augmenting processes are more often found in the context of cluster renewal. |
| Keywords: | Cluster; Evolution; Decline; Renewal; Meta-analysis |
| JEL: | O33 R10 R11 |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2418&r= |
| By: | Kuosmanen, Natalia; Pajarinen, Mika; Heshmati, Almas |
| Abstract: | Abstract The service sector is undergoing rapid changes attributed to digitalization. This study examines the relationship between digitalization and the performance of the Finnish private service firms from 2015 to 2021 using linked employer-employee data, financial data and an IT usage survey. Our descriptive and regression analyses reveal significant variability in the level and areas of digital adoption across service industries. Information and communication, and professional activities are found highly digitalized, while accommodation and food service activities, and transportation and storage lag in digitalization intensity. Additionally, we find a strong positive correlation between firms’ digitalization and revenues, particularly for firms with higher digital intensity. This correlation persisted throughout the COVID-19 pandemic. We also observe a positive correlation between digitalization and productivity in the early years, but more recent data suggest a weakening of this association, possibly due to increased digital adoption among less productive firms during the pandemic. Finally, our analysis indicates that larger firms, or those with a larger market share or international activities, tend to have higher levels of digitalization. Thus, investment in digitalization is recommended to enhance service sectors performance. |
| Keywords: | Digitalization, Firm performance, Productivity, Private service industry, Finland |
| JEL: | L25 L80 L86 O14 O33 |
| Date: | 2024–06–11 |
| URL: | https://d.repec.org/n?u=RePEc:rif:wpaper:117&r= |
| By: | Bathelt, Harald; Buchholz, Maximilian; Storper, Michael |
| Abstract: | Social scientists and policymakers alike have become increasingly concerned with understanding the nature, causes, and consequences of inter-regional inequality in economic living conditions. Contemporary spatial inequality is multi-faceted—it varies depending on how we define inequality, the scale at which it is measured, and which groups in the labor force are considered. Increasing economic inequality has important implications for broader social and political issues. Notably, it is difficult to account for the rise of far-right populism in industrialized countries without considering the context of growing inter-regional inequality. Important explanations for the rise in inter-regional inequality include changing patterns of worker and firm sorting processes across space, major transitions like the reorientation of the economy from manufacturing to digital technologies, and increasing global economic integration, as well as policy. Different causal explanations in turn imply a different role for place-based policy. This article introduces the context of the special issue on the nature, causes, and consequences of inter-regional inequality, focusing specifically on inequality in North America and Western Europe, and aims to identify challenges for, and spark further research on, inter-regional inequality. |
| Keywords: | global economic integration; inter-regional connectivity; inter-regional inequality; place-based policies; political polarization; sorting across space |
| JEL: | D63 D72 D83 F21 O18 R11 |
| Date: | 2024–04–02 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:123014&r= |