|
on Information and Communication Technologies |
| By: | Mr. Giovanni Melina; Stefania Villa |
| Abstract: | This paper investigates the macroeconomic implications of the rising wave of investment in information and communication technology (ICT)—including AI-related hardware and software—in the U.S. economy. The analysis uses a structural macroeconomic model that treats ICT as a distinct type of capital and explores the degree to which ICT complements or substitutes for labor. The findings reveal three key insights. First, labor and ICT have historically been only moderately substitutable. Second, technological innovations that make it easier to turn ICT investment into productive capital act like demand shocks, boosting output and inflation. Third, given the uncertainty surrounding the interaction between AI-driven ICT capital and labor, the paper presents scenarios of possible trajectories for ICT investment under alternative assumptions. When ICT tends to complement labor, the economy experiences strong gains in output, but also inflationary pressure; the natural interest rate increases, requiring tighter monetary policy. Conversely, if ICT tends to replace labor, the same ICT investment path warrants a looser monetary policy stance. |
| Keywords: | Artificial Intelligence; Generative AI; ICT investment; Natural rate of interest; Monetary policy; DSGE modeling |
| Date: | 2025–10–31 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/224 |
| By: | Zhiwu Wei (University of Cambridge); Neil Lee (London School of Economics and Political Science); Yohan Iddawela (Asian Development Bank) |
| Abstract: | Mobile internet has become a fundamental component of modern infrastructure. In this paper, we consider the impact of mobile internet connectivity on household wealth in the Philippines. We construct a granular measure of local mobile internet connectivity using comprehensive information on approximately 0.27 million geocoded cell towers, and identify causal impact through a novel instrumental variable based on proximity to submarine cable landing points. Our results suggest that mobile internet connectivity significantly increases household wealth, with effects that persist across education levels and are more pronounced in urban areas compared to rural ones. Combining individual survey datasets with Points-of-Interest data, we investigate mechanisms and demonstrate that improved connectivity stimulates activities in several key economic sectors that create employment opportunities. Additionally, mobile internet connectivity enhances individual educational outcomes and promotes female labor force participation, though predominantly in occasional or seasonal roles. |
| Keywords: | mobile internet;cell tower;wealth inequality;Philippines |
| JEL: | F14 J24 J63 L86 O33 |
| Date: | 2025–11–07 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:021753 |
| By: | Elvis K. Ofori (Zhengzhou University, China); Simplice A. Asongu (Johannesburg, South Africa); Ernest B. Ali (Ekaterinburg, Russia); Bright A. Gyamfi (Istanbul, Turkey); Isaac Ahakwa (Hefei, China) |
| Abstract: | Since the industrial era, the selection of energy sources to facilitate economic advancement has been criticized because of the resulting ecological calamity. This has prompted the introduction of radical approaches such as ISO 14001, which tackles the drivers of pollution. Therefore, this study analyses the ISO 14001 - environment nexus from three distinct points of view BRICS, MINT, and G7 countries from 1999-2020. Also, our work fills an extant gap in assessing structural change and innovation's role in augmenting the relationship. The Driscoll and Kraay (DK) estimator is employed as an analytical tool for cross-sectional dependence and slope homogeneity, while the fixed effects approach provides sufficient robustness checks on the findings. While some outcomes vary per bloc, others are relatively similar across the three (3) blocs. That is: (1) ISO 14001 shows an abatement portfolio for only the G7 bloc, and the Full sample. (2) Structural change showed potential for abating carbon emissions in all blocs. (3) Technology led to an increase in Pollution in all blocs except for the MINT economy. (4) ICT in the form of mobile phones also help reduce carbon emissions in all three blocs except for their composite. (5) Renewable energy helps reduce carbon emission in all blocs except for G7. ISO 14001 shows the potential to encourage green growth. As a result, policymakers should work to enhance ISO 14001 certification, which might serve as a management tool to promote sustainable development. |
| Keywords: | ISO 14001, Sustainable development, Structural change, Technology, BRICSMINT, G7 |
| Date: | 2024–01 |
| URL: | https://d.repec.org/n?u=RePEc:dbm:wpaper:24/021 |
| By: | Bakker, Gerben |
| Abstract: | We identify a previously underappreciated data revolution starting in the 1960s, in which business information firms adopted ICT very early on to automate market data sales. Before this ‘terminal revolution’, securities firms could barely cope with the paperwork of growing trading volumes, forcing the NYSE to close on Wednesdays to allow them to catch up. The terminal revolution placed computer screens on every client’s desk, changed how data was accessed and acted on, and created virtual trading floors, foreshadowing almost all stages the internet would go through some three decades later. We focus on early entrant Reuters and late entrant Bloomberg, which came to dominate global market data provision, discussing other firms along the way. We find that theory on sunk costs and market structure (Sutton, 1998) can explain how the exploding market remained highly concentrated, despite many new entrants. We also find that financial and business news (subject to Arrow’s paradox) was a complement to data (not subject to Arrow’s paradox), and barely profitable by itself: only firms offering both financial news and data tended to survive. |
| Keywords: | news agencies; financial and business news; business information; Arrow's fundamental paradox of information; trading data terminals; exchange rates; stock prices; bond prices; commodity prices; precursors to internet; industrialisation of services; ICT productivity impact; Kenneth J. Arrow; business history |
| JEL: | L82 L86 N20 N72 N74 N82 N84 O33 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:129938 |
| By: | Liu, Yan; Huang, Jingyun; Wang, He |
| Abstract: | Nearly three years after ChatGPT’s launch, the generative artificial intelligence landscape remains in rapid flux. Using high-frequency website traffic data from Semrush, this paper tracks global adoption patterns for the 60 most-visited consumer-facing generative artificial intelligence tools through mid-2025. Five key findings emerge. First, fierce competition drives continuous innovation: two of 2025’s top five tools—DeepSeek and Grok—are new entrants, and development is rapidly diversifying into multi-modal capabilities, reasoning, and specialized applications. Second, ChatGPT maintains dominance despite competition, accounting for 77 percent of traffic to the top 60 tools in April 2025. Third, usage of generative artificial intelligence has exploded since mid-2024: ChatGPT traffic grew 113 percent year-over-year, driven by 42 percent user growth and 50 percent increased visits per user, with session duration doubling. Fourth, high-income countries are pulling decisively ahead, creating stark global divides. While 24 percent of internet users in high-income countries use ChatGPT, penetration drops to 5.8 percent in upper-middle-income countries, 4.7 percent in lower-middle-income countries, and just 0.7 percent in low-income countries. Regression analysis confirms that gross domestic product per capita strongly predicts adoption growth. Fifth, localization shapes competitive advantage: non-U.S. tools concentrate heavily in home markets, with Le Chat drawing 69 percent of traffic from Europe and several Chinese tools exceeding 90 percent domestic usage. These patterns reveal an artificial intelligence landscape characterized by intense innovation, persistent market leadership, accelerating growth, and deepening global inequality, underscoring the need for inclusive policies as generative artificial intelligence becomes central to economic participation. |
| Date: | 2025–10–15 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wbrwps:11231 |
| By: | Lewandowski, Piotr (Institute for Structural Research (IBS)); Madoń, Karol (Institute for Structural Research (IBS)); Park, Albert (Hong Kong University of Science & Technology) |
| Abstract: | This paper develops a task-adjusted, country-specific measure of workers’ exposure to Artificial Intelligence (AI) across 108 countries. Building on Felten et al. (2021), we adapt the Artificial Intelligence Occupational Exposure (AIOE) index to worker-level PIAAC data and extend it globally using comparable surveys and regression-based predictions, covering about 89% of global employment. Accounting for country-specific task structures reveals substantial cross-country heterogeneity: workers in low-income countries exhibit AI exposure levels roughly 0.8 U.S. standard deviations below those in high-income countries, largely due to differences in within-occupation task content. Regression decompositions attribute most cross-country variation to ICT intensity and human capital. High-income countries employ the majority of workers in highly AI-exposed occupations, while low-income countries concentrate in less exposed ones. Using two PIAAC cycles, we document rising AI exposure in high-income countries, driven by shifts in within-occupation tasks rather than employment structure. |
| Keywords: | AI, occupations, job tasks, technology, skills |
| JEL: | J21 J23 J24 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18235 |
| By: | Lei Chen; Chaoyue Gao; Alvin Leung; Xiaoning Wang |
| Abstract: | Generative artificial intelligence (GenAI) like Large Language Model (LLM) is increasingly integrated into digital platforms to enhance information access, deliver personalized experiences, and improve matching efficiency. However, these algorithmic advancements rely heavily on large-scale user data, creating a fundamental tension between information assurance-the protection, integrity, and responsible use of privacy data-and artificial intelligence-the learning capacity and predictive accuracy of models. We examine this assurance-intelligence trade-off in the context of LinkedIn, leveraging a regulatory intervention that suspended the use of user data for model training in Hong Kong. Using large-scale employment and job posting data from Revelio Labs and a Difference-in-Differences design, we show that restricting data use significantly reduced GenAI efficiency, leading to lower matching rates, higher employee turnover, and heightened labor market frictions. These effects were especially pronounced for small and fast-growing firms that rely heavily on AI for talent acquisition. Our findings reveal the unintended efficiency costs of well-intentioned data governance and highlight that information assurance, while essential for trust, can undermine intelligence-driven efficiency when misaligned with AI system design. This study contributes to emerging research on AI governance and digital platform by theorizing data assurance as an institutional complement-and potential constraint-to GenAI efficacy in data-intensive environments. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.01923 |
| By: | Brüll, Eduard (ZEW); Mäurer, Samuel (University of Mannheim); Rostam-Afschar, Davud (University of Mannheim) |
| Abstract: | We provide experimental evidence on how employers adjust expectations to automation risk in high-skill, white-collar work. Using a randomized information intervention among tax advisors in Germany, we show that firms systematically underestimate automatability. Information provision raises risk perceptions, especially for routine-intensive roles. Yet, it leaves short-run hiring plans unchanged. Instead, updated beliefs increase productivity and financial expectations with minor wage adjustments, implying within-firm inequality like limited rent-sharing. Employers also anticipate new tasks in legal tech, compliance, and AI interaction, and report higher training and adoption intentions. |
| Keywords: | belief updating, firm expectations, technology adoption, innovation, technological change, automation, artificial intelligence, expertise, labor demand, white collar jobs, training |
| JEL: | J23 J24 D22 D84 O33 C93 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18225 |