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on Information and Communication Technologies |
| By: | Mathilde Maurel (Centre d'Economie de la Sorbonne, CNRS); Thomas Pernet (Centre d'Economie de la Sorbonne, Université Paris 1 Panthéon-Sorbonne) |
| Abstract: | This paper examines how using the internet and social networks as information souces affects individuals' understanding of democracy. Using data from the sixth round of the Afrobarometer survey (2014), which includes both open- and closed-ended questions on democracy, the study analyzes how online information influences political perceptions across African countries. Open-ended responses are structured using ChatGPT. The identification strategy exploits the interaction between lightning activity and 3G coverage, where lightning causes random internet disruptions, providing an exogenous source of variation. Findings reveal that reliance on Internet-based information negatively biases individuals' understanding of democracy, freedom of expression and institutional corruption, while positively biasing perceptions of electoral fairness. Given the strong link between democratic understanding and preferences for democracy, these biases may shape political attitudes. As internet use grows in Africa, its role in influencing political perspective becomes increasingly significant |
| Keywords: | Internet news; Democracy; Misunderstanding of Democracy; Africa |
| JEL: | G2 G32 L25 L6 Q53 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:mse:cesdoc:25005 |
| By: | Mahdi Ghodsi (The Vienna Institute for International Economic Studies, wiiw); Sandra M. Leitner (The Vienna Institute for International Economic Studies, wiiw); Maryna Tverdostup (The Vienna Institute for International Economic Studies, wiiw) |
| Abstract: | Labour shortages in Europe have led firms to adopt two key strategies automation and the employment of migrants. This study empirically examines the relationship between robot adoption and immigrant labour (differentiated by region of origin and education level) in Austrian firms using a novel dataset linking firm-level survey data on robotics adoption from Austria’s Information and Communication Technologies (IKTU ) surveys (waves 2018, 2020 and 2022) with registry-based employment records. Employing Poisson pseudo-maximum likelihood (PPML) estimations, we analyse firm-level employment decisions while controlling for firm characteristics, industry and region. Our findings show that firms adopting robots tend to employ more workers overall, particularly those with low and medium education levels. Notably, robot-adopting firms employ a higher share of low-educated migrants who are not from the European Economic Area (EEA), suggesting complementarity rather than substitution. However, automation appears to reduce the employment of highly educated migrant workers relative to natives. Distinguishing between industrial and service robots, we find that service robots have a stronger association with employment growth than industrial robots. The impact of robot adoption also differs by sector and is most pronounced in manufacturing, whereas its effects vary in the private service sectors. Our findings suggest that while automation can alleviate labour shortages, it may reinforce labour market segmentation. For EU policy makers, targeted interventions are needed to support the transition of migrant workers into higher-skilled occupations and to ensure that the benefits of automation are equitably distributed. Given the EU-wide relevance of automation and migration dynamics, these results provide insights that are also applicable beyond Austria. |
| Keywords: | Migration, automation, employment, firm- and worker-level analysis |
| JEL: | D22 J23 J24 J61 O33 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:wii:wpaper:262 |
| By: | Fontanelli, Luca; Guerini, Mattia; Miniaci, Raffaele; Secchi, Angelo |
| Abstract: | While artificial intelligence (AI) adoption holds the potential to enhance business operations through improved forecasting and automation, its relation with average productivity growth remain highly heterogeneous across firms. This paper shifts the focus and investigates the impact of predictive artificial intelligence (AI) on the volatility of firms’ productivity growth rates. Using firm-level data from the 2019 French ICT survey, we provide robust evidence that AI use is associated with increased volatility. This relationship persists across multiple robustness checks, including analyses addressing causality concerns. To propose a possible mechanisms underlying this effect, we compare firms that purchase AI from external providers (“AI buyers”) and those that develop AI in-house (“AI developers”). Our results show that heightened volatility is concentrated among AI buyers, whereas firms that develop AI internally experience no such effect. Finally, we find that AI-induced volatility among “AI buyers” is mitigated in firms with a higher share of ICT engineers and technicians, suggesting that AI’s successful integration requires complementary human capital. |
| Keywords: | Dairy Farming, Production Economics, Research and Development/Tech Change/Emerging Technologies, Resource/Energy Economics and Policy |
| Date: | 2025–04–07 |
| URL: | https://d.repec.org/n?u=RePEc:ags:feemwp:355806 |
| By: | Sanja Samirana Pattnayak |
| Abstract: | This study contributes to the literature on digitalisation in developing countries by examining its role in export intensity and firm productivity in Indian manufacturing from 2000 to 2021. Using fixed effects and the system generalised method of moments (GMM) model, the analysis draws on firm-level data from the Prowess database, encompassing approximately 11, 000 manufacturing firms. The findings reveal that digitalisation amongst India’s manufacturing firms is positively associated with both export intensity and productivity, after accounting for firm characteristics and heterogeneity. Specifically, a 1% increase in digital intensity corresponds to a 0.16% increase in exports. This effect is further enhanced when expenditure on internet services and software development is included, raising the export impact to 0.21% per 1% increase in digital intensity. Additionally, the results indicate that a 1% increase in digitalisation intensity leads to a 0.8% growth in total factor productivity. These findings have significant policy implications, particularly as digitalisation increasingly shapes the global and Indian economies. They underscore the need for strategies to promote digital adoption in manufacturing to enhance competitiveness and productivity. |
| Keywords: | digitalisation; productivity; exports; servicification; manufacturing; India |
| JEL: | C33 D24 F14 J24 L60 O33 |
| Date: | 2025–03–19 |
| URL: | https://d.repec.org/n?u=RePEc:era:wpaper:dp-2024-39 |
| By: | Tao Chen; Shuwen Pi; Qing Sophie Wang (University of Canterbury) |
| Abstract: | This study examines the impact of artificial intelligence (AI) on corporate investment efficiency. Our analysis of recruitment data from Chinese listed companies reveals a positive correlation between AI and investment efficiency, primarily driven by a reduction in over-investment. Specifically, a one-standard-deviation increase in AI hiring is associated with a 3.1% improvement in investment efficiency. This improvement results from better investment decisions (e.g., greater responsiveness to growth opportunities and fewer value-destroying mergers and acquisitions), and more effective internal capital allocation (e.g., improvements in innovation and operational efficiency). The positive impact of AI is stronger in firms with less government intervention, flatter organizational structures, technically experienced boards, poorer information environments, and traditional and lowly competitive industries. Overall, our findings highlight the importance of AI skills in shaping corporate investment decisions. |
| Keywords: | Artificial intelligence, AI hiring, investment efficiency |
| JEL: | O14 O33 G31 G34 |
| Date: | 2025–04–01 |
| URL: | https://d.repec.org/n?u=RePEc:cbt:econwp:25/05 |
| By: | Botsari, Antonia; Lang, Frank |
| Abstract: | Based on responses from 226 European private equity fund managers, the 2024 EIF PE Mid-Market Survey (the largest of its kind in Europe; conducted during July-August 2024) provides insights on the latest trends and developments in the European PE market. Key findings: Despite a still challenging market environment, the developments of the past two years reflect a normalisation away from the crisis mode seen in 2022, when PE Mid-Market fund managers' key concerns had been geopolitical uncertainty and market volatility. Fundraising and geopolitical uncertainty remain the two biggest challenges for the PE Mid-Market business, followed by portfolio company performance and the exit environment. General difficulties in finding potential buyers and a thin M&A market are mentioned as key challenges for exits. Approximately 2 in 5 PE Mid-Market fund managers state that the scale-up financing conditions have worsened in the last year. Recruiting high-quality professionals, the costs of production and labour and geopolitical uncertainty (and related consequences) have remained the three most important challenges for PE Mid-Market portfolio companies. PE Mid-Market fund managers report, on balance, a higher number of incoming investment proposals as well as of new investments undertaken. Respondents see promising investment opportunities in several sectors, particularly in the areas of Healthcare, ICT and the transition to greener and more efficient energy sources. With regard to respondents' expectations for future developments, for many market sentiment indicators the level of optimism expressed for the next 12 months has almost recovered to or even surpassed that observed in 2021- which was a record year for the PE/VC markets in Europe. Background: The EIF Equity Survey (combined EIF VC Survey and EIF Private Equity Mid-Market Survey) is the largest regular survey among General Partners across Europe, with a total of 624 respondents (398 VC, 226 PE). It feeds into our flagship publications delivering unique market insights on an annual basis. This publication is based on the results of the EIF PE Mid-Market Survey 2024. The study focuses on market sentiment and looks at the current situation, developments in the recent past as well as fund managers' expectations for the future |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:eifwps:313621 |