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on Information and Communication Technologies |
| By: | Rawane Yasser (Agence Française de Développement.); Irene Selwaness (Cairo University, Egypt); Cecilia Poggi (Agence Française de Développement) |
| Abstract: | The dynamic intersection between technology and labor constitutes the focal point of labor market policies designed to align with technological transitions. In this context, studying the characteristics of digitized work content and work relations is crucial for comprehending the evolving landscape of the Egyptian labor market and accompanying policymaking. This paper investigates the evolution of the use of technology in the workplace in Egypt; we begin by exploring changes in computer and internet use, with particular attention to potential firms’ responses to COVID-19 (e.g., remote working…etc.). Further, we also assess the types and prevalence of digital/computer skills across the whole population, in the labor force, and by type of jobs. Finally, the paper examines employment through digital platforms in Egypt.Length: 41 |
| Date: | 2024–11–20 |
| URL: | https://d.repec.org/n?u=RePEc:erg:wpaper:1754 |
| By: | Kaustabh Adhya |
| Abstract: | Information shapes people’s narratives and, thus, collective action. The latter bears implications for both inter-group economic cooperation and conflict. In this paper, we examine the economic effects of ethnic conflicts under varying information levels as proxied by mobile Internet speeds. Our analysis of India from 2019 to 2023 yields that religious riots reduce night-time lights by 19.61% in the following year and mobile Internet speed amplifies the negative effects by approximately 1.2 - 5.1 percentage points. We posit that the mechanism is through spiteful narratives that are amplified by the faster Internet. The findings are robust to a battery of alternative specifications and tests. |
| Keywords: | Riots; Internet Speed; Hateful Narratives; Economic Activities |
| JEL: | D74 L86 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:ukc:ukcedp:2601 |
| By: | Piotr Lewandowski (Institute for Structural Research); Karol Madoń (Institute for Structural Research); Albert Park (Asian Development Bank) |
| 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 data from the Programme for the International Assessment of Adult Competencies (PIAAC) 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 United States (US) 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 information and communications technology 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: | job tasks;occupations;AI;technology;skills |
| JEL: | J21 J23 J24 |
| Date: | 2026–01–30 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:022156 |
| 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:wpaper:129938 |
| By: | Faruk Hadžić (Sarajevo School of Science and Technology, Bosnia and Herzegovina); Ema Radončić (Sarajevo School of Science and Technology, Bosnia and Herzegovina) |
| Abstract: | This paper explores the relationship between the level of digital maturity and innovation of SMEs in Bosnia and Herzegovina, with a particular focus on the role of ICT as one of the drivers of innovation within the enterprise. Based on data collected from 304 enterprises from different sectors, a composite ICT index was created that quantifies the level of digital maturity of enterprises, as well as an innovation index that measures their activities in the field of innovation. Using descriptive statistics, sectoral segmentation, and K-means cluster analysis, the paper identifies significant differences in the level of digitalization between sectors, and also companies a positive relationship between a higher ICT index and greater innovation. The results show that enterprises with a higher level of digital maturity also achieve a higher level of innovation, while enterprises with a lower ICT index show a lower propensity to innovate. Based on the analysis, three clusters were formed that clearly distinguish enterprise profiles according to digital-innovation behavior. Furthermore, the findings of this research provide an empirical basis for the development of a targeted policy to support the digital transformation of sectoral SMEs, while identifying sectors with the lowest digital capacities as priorities for government intervention. The results obtained should be viewed with caution due to the subjectivity of the respondents' responses. As a practical suggestion, vouchers for digital tools and reskilling programs for the construction and hospitality sectors could accelerate the digital literacy of these companies. The paper aims to contribute to the understanding of the relationship between digital technologies and the innovation capabilities of enterprises in a transitional economic context. |
| Keywords: | Digital maturity, ICT index, Innovation, SMEs, Cluster analysis, Small and medium-sized enterprises |
| JEL: | O33 L26 M15 |
| Date: | 2025–12–15 |
| URL: | https://d.repec.org/n?u=RePEc:aoh:conpro:2025:i:6:p:166-179 |
| By: | Arshad, Idrees Ahmad; Ali, Amjad; Audi, Marc |
| Abstract: | The purpose of this study is to evaluate how the implementation of working from home, as opposed to traditional office-based work, has influenced employee productivity, work-life balance, job satisfaction, communication effectiveness, and emotional wellbeing. A mixed-methods approach was employed, using data collected through structured surveys of two hundred professionals across various industry sectors, along with semi-structured interviews with the same participants. Quantitative analysis involved the application of descriptive statistics, independent sample t-tests, and the construction of a productivity and wellbeing index. Qualitative responses were examined through directed content analysis. The findings indicate that remote work generally enhances productivity, autonomy, and work-life balance, particularly among younger, digitally proficient employees in sectors such as information technology and finance. However, remote work also presents disadvantages, including communication gaps, social isolation, and reduced visibility within teams. In contrast, traditional office work fosters stronger team cohesion, real-time feedback, and integration into organizational culture, though it may lack flexibility and contribute to stress due to structured schedules and commuting demands. The study underscores the increasing relevance of hybrid work models as a strategic approach that integrates the strengths of both work modalities. Grounded in stakeholder theory, legitimacy theory, and systems theory, the research offers a multidimensional perspective on how work environments influence organizational outcomes and employee experiences. The study concludes that future-oriented organizations must design work systems that are flexible, inclusive, and adaptive, aligning operational efficiency with ethical and strategic considerations. |
| Keywords: | Remote Work, Work-Life Balance, Employee Productivity, Hybrid Work Models |
| JEL: | O4 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127312 |
| By: | Andrijana Bojadjievska Danevska (Faculty of Economics and Administrative Sciences International Balkan University, Skopje, North Macedonia) |
| Abstract: | Purpose Innovation and human capital are considered the two main pillars of contemporary economic growth (Aiting et al., 2022). Additionally, certain scholars consider that human capital is an innovation engine (Acemoglu, 1996; Aghion and Howitt, 1998). However, the evidence from developing countries shows that the increased investment in human capital has not brought the corresponding innovation growth (Li and Nan, 2019). In this context, this paper investigates the path from human capital, through innovation inputs and processes to innovation outcomes, by utilizing data from the Digital Evolution Index (2025) for 125 countries over the timespan 2008-2023. More specifically, this research examines whether human development presented as the “state of human condition” and measured within the Digital Evolution Index, translates into higher levels of innovation inputs, processes, and finally innovation outcomes, i.e., technological and innovation outputs that reflect society’s digital progress. In this framework, human development is conceptualized as a set of socio-economic conditions that enable individuals and communities to adopt, adapt, and benefit from digital technologies. Design/methodology/approach Panel regressions, i.e., Fixed Effects and Random Effects models, were applied to control for unobserved country heterogeneity. The Hausman Test statistics with 1.87 and a p-value of 0.76 showed that Random Effects estimators are more consistent. Additionally, to complement the causal inference, a Random Forest Regressor was used in order to capture non-linear patterns and provide feature importance analysis. Also, to account for structural differences across development levels, income group classifications by the World Bank (low, lower–middle, upper–middle, high) were included as additional predictors in the Random Forest Model. In simple terms, to test whether the development stage modifies the path. This study uses a combination of econometrics with machine learning models in order to improve predictive accuracy, provide more accurate and robust predictions (Khan and Wyrwa, 2025). Findings Panel regression confirms that the improvements in human development (measured and presented as human condition) are significantly associated with greater innovation inputs, which in turn foster processes and eventually outcomes. In the preferred Random Effects model, human development, inputs, and processes are all positive and significant predictors of outcomes. The Random Forest model has a strong predictive performance (R2 > 0.70, MAE low relative to outcome scale). It was trained on 80% of the sample and tested on the remaining 20%. The feature importance analysis provides insights into the relative predictive power of each analyzed determinant, where both impurity–based and permutation importance (see Figure 1) confirm that: - Innovation processes emerge as by far the most influential predictor of innovation outcomes (accounting for the vast majority of predictive power, i.e., close to 1.0 in permutation importance) - State of human development contributes modestly (~0.20) - Innovation inputs are weaker (~0.07) - Income groups contribute modestly, with Lower-middle (~0.03) and Upper-middle (~0.01) income classifications adding small predictive value, while Low-income countries show negligible importance. In summary, these findings show that while structural development levels matter, actually the strength of processes rather than income group status per se that primarily explains the cross-country differences in innovation outcomes. Originality/value This research combines panel regression and machine learning to empirically trace the path from human development, through innovation inputs and processes to outcomes. Findings suggest that investments in human development and innovation inputs are necessary but insufficient unless supported by robust processes, i.e. “systems in place which can facilitate the development of innovative ideas and practices” (Chakravorti et al., 2025), that translate inputs into tangible outputs, measured through ICT Service Exports (%), ICT Goods Exports (% Total Goods Exports), Apps developed per person, Scientific and Technical Journal Articles etc. Figure 1: Permutation importance of Predictors for Innovation Outcomes (Random Forest) (Source: Authors’ calculation based on DEI 2025) Table 1: Panel Regression Results (Dep. variable: Innovation outcomes) Variable FE coef. (t) RE coef. (t) Human Development 0.311 (3.21)*** 0.320 (15.60)*** Inputs 0.101 (2.11)** 0.090 (4.33)*** Processes 0.147 (2.10)** 0.198 (7.69)*** Constant -0.705 (-0.21) -2.476 (-2.13)** R2 (overall) 0.602 0.630 No.obs 2000 2000 (Source: Authors’ calculation based on DEI 2025) As shown in Table 1, both models fit the data well, indicating that around 60% of the variation in innovation outcomes is explained by the included predictors. Human development is a significant predictor in both FE and RE models, which means that improvements in social readiness, i.e., education, health, and income levels, etc., are strongly associated with higher innovation outcomes. Inputs and processes also show positive and statistically significant effects, highlighting that R&D investments, financial resources, effective institutional and organizational mechanisms, such as digital adoption, collaborative networks, and policy support, are critical in translating human development into tangible innovation results. |
| Keywords: | Panel regression, Random forest, Digital evolution, Innovation outcomes, Human development |
| JEL: | O15 O31 O33 |
| Date: | 2025–12–15 |
| URL: | https://d.repec.org/n?u=RePEc:aoh:conpro:2025:i:6:p:313-315 |
| By: | Kauhanen, Antti; Rouvinen, Petri |
| Abstract: | Abstract While research by Brynjolfsson et al. (2025) suggests that youth employment in the United States has declined significantly in occupations highly exposed to artificial intelligence, the position of older workers has remained stable. A new working paper by Kauhanen and Rouvinen (2026) replicates this analysis in the Finnish context, leveraging exceptionally comprehensive national income register data. In contrast to the US experience, Finland shows no evidence of AI-driven displacement among young workers, nor has exposure negatively impacted wage growth. A modest decline in youth employment is attributed to demographic shifts and aging-induced impacts rather than AI exposure. This divergence between the US and Finland stems from structural and institutional resilience: the Nordic labor market model and robust employment protection legislation help buffer technological shocks. Regarding policy, the memorandum emphasizes the need for pedagogical reform, advocating for an educational focus on higher-order critical thinking and AI integration from the very beginning of professional studies. |
| Keywords: | Generative artificial intelligence, Technological change, Employment, Wages, Occupations |
| JEL: | E24 J21 J23 O33 |
| Date: | 2026–01–27 |
| URL: | https://d.repec.org/n?u=RePEc:rif:briefs:173 |
| By: | Sasho Arsov (Faculty of Economics-Skopje, Ss. Cyril and Methodius University in Skopje, North Macedonia); Aleksandar Naumoski (Faculty of Economics-Skopje, Ss. Cyril and Methodius University in Skopje, North Macedonia); Pece Nedanovski (Faculty of Economics-Skopje, Ss. Cyril and Methodius University in Skopje, North Macedonia) |
| Abstract: | The paper explores the issue of digital financial inclusion as a means to overcome the traditional hurdles in access to financial services and its impact on the level of financial development. Using a broad sample of 102 countries worldwide and a time series of data ranging from 2011 to 2021, a Principal Component Analysis is applied to derive a single measure of digital financial inclusion (DFI). The ranking shows that the developed countries and the European nations in general dominate the list, while the bottom is mostly populated by African countries. Using a modified digital financial inclusion index to meet the availability of data, a regression analysis using OLS and GMM techniques was applied to determine the impact of DFI on the level of financial development. The results show that digital financial inclusion has a positive impact on financial development, so the authorities should closely monitor and support the use of digital technologies in the financial sector, as well as enhance the access of the population to these opportunities and their ability to use modern communication technologies. |
| Keywords: | Financial development, Digital financial inclusion, Debit card, ATM |
| JEL: | G20 G50 |
| Date: | 2025–12–15 |
| URL: | https://d.repec.org/n?u=RePEc:aoh:conpro:2025:i:6:p:91-101 |
| By: | Phoebe Koundouris (School of Economics, Department of IEES and Director, ReSEES, Athens University of Economics and Business; Department of Earth Sciences, University of Cambridge; Peterhouse, University of Cambridge; Director, Sustainable Development Unit, ATHENA Information Technologies Research Center; Chair, Alliance of Excellence for Research Innovation on Aephoria (AE4RIA)); Anastasia Litina (Department of Economics, University of Macedonia, Visiting Researcher at the University of Luxembourg); Ioannis Patios (Department of Economics, University of Macedonia) |
| Abstract: | An unexplored impact of natural disasters is the scarcity they create and the resulting reallocation of resources. This paper examines this effect by analyzing how disaster-driven scarcity reshapes fairness considerations. Using data from the International Disaster Database and the European Social Survey, we show that disaster exposure increases perceptions of solidarity-driven fairness, including social support, rewards for effort, and equal access to services, while reducing perceptions of scarcity-driven fairness such as wage equality, access to education or the functioning of the political system. As disasters are a cross-border phenomenon, we further study spillovers from neighboring countries and find that they can strengthen solidarity-based fairness while simultaneously heightening skepticism toward institutional and societal fairness. Finally, we explore mechanisms, i.e., ιnstitutional trust, FDI, EU funds, that condition these relationships and shape how individuals interpret fairness norms after a disaster. |
| Keywords: | Fairness; NaturalDisasters; Justice; Equality; ClimateChange. |
| JEL: | Q54 D63 D64 H84 Z13 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:mcd:mcddps:2026_01 |