60853 research outputs found
Sort by
The Skill Premium Across Countries in the Era of Industrial Robots and Generative AI
Get PDFHow do new technologies affect economic growth and the skill premium? To answer this question, we analyze the impact of industrial robots and artificial intelligence (AI) on the wage differential between low-skill and high-skill workers across 52
countries using counterfactual simulations. In so doing, we extend the nested CES production function framework of Bloom et al. (2025) to account for cross-country income heterogeneity. Confirming prior findings, we show that the use of industrial robots tends to increase wage inequality, while the use of AI tends to reduce it. Our contribution lies in documenting substantial heterogeneity across income groups: the inequality-increasing effect of robots and the inequality-reducing effects of AI are particularly strong in high-income countries, while they are less
pronounced among middle- and lower-middle income countries. In addition, we show that both technologies boost economic growth. In terms of policy recommendations, our findings suggest that investments in education and skill-upgrading can simultaneously raise average incomes and mitigate the negative effects of automation on wage inequality
Assessing Greece’s plans towards climate-neutrality under a water-energy-food-emissions modelling nexus: Ambitious goals versus scattered efforts
Get PDFAchieving climate-neutrality is a global imperative that demands coordinated efforts from both science and robust policies supporting a smooth transition across multiple sectors. However, the interdisciplinary and complex science-to-policy nature of this effort makes it particularly challenging for several countries. Greece has set ambitious goals across different policies; however, their progress is often debated. For the first time, we simulated a scenario representing Greece’s climate-neutrality goals drawing upon its main relevant energy, agricultural and water policies, and compared it with a ‘current accounts’ scenario by 2050. The results indicate that most individual policies have the potential to significantly reduce carbon emissions across all sectors of the economy (residential, industrial, transportation, services, agriculture, and energy production). However, their implementation seems to be based on economic and governance assumptions that often overlook sectoral interdependencies, infrastructure constraints, and social aspects, hindering progress towards a unified and more holistic sustainable transition
On the Equivalence of Strategy-proofness and Directed Local Strategy-proofness under Preference Extensions
Get PDFWe consider a model in which outcomes are bundles of alternatives, each of size at most a fixed (but arbitrary) number. Each agent's type is a strict preference over individual alternatives, which is then lexicographically extended to induce a strict preference over outcomes. A social choice function assigns an outcome to each type profile of agents.
A social choice function is said to be locally strategy-proof if no agent can benefit by misreporting her type to another type that the designer considers plausible. The main departure from existing literature lies in the asymmetry of type misreports, which is captured using a directed graph that encodes the designer’s beliefs about feasible misreports.
An environment is said to satisfy Directed-Local-Global Equivalence (DLGE) property if every locally strategy-proof social choice function defined on it is, in fact, (globally) strategy-proof. In this paper, we provide a complete characterization of DLGE environments via a property we refer to as Property Strong DL.
Additionally, we derive necessary and sufficient conditions for DLGE under several specific notions of locality, such as adjacent, k-push-up, k-push-down, and k_1-push-up and k_2-push-down (some of which were studied in Altuntaș et al. (2023)) both in the setting where outcomes are individual alternatives and where any subset of alternatives may constitute a feasible outcome. Our analysis also extends to single-peaked domains as well. The main result in Cho and Park (2023) and several main results in Altuntaș et al. (2023) follow as corollaries of our framework
The Price of Proximity: How Bengaluru's Metro Affects Residential Property Values
Get PDFTransit networks significantly influence city evolution, with mass rapid transit systems enhancing access to jobs, housing, and infrastructure. Indian Government is promoting metro rail projects to strengthen public transport, and many cities are developing their metro rail corridors, making understanding their impact crucial in the Indian context. This study investigates the impact of the mass rapid transit system (Namma Metro) on residential property values in Bengaluru, India. It investigates the impact of recently operational and existing metro lines on property values in different neighborhoods across Bengaluru. The research uses a mixed-methods approach, combining quantitative data analysis with hedonic price regression based on household surveys. The regression results show that proximity to metro stations and higher income levels lead to significant housing value increases. The dense areas and longer metro operation years contribute to higher property values, while the distance from the city centre and higher metro connection costs negatively impact property values. The findings have significant implications for urban planning and policy decisions. It helps understand how building metro stations leads to real estate development and value creation in the vicinity of the metro corridor and how transit-oriented development policies around metro stations can support land value capture
How China's Rural Health Program Lifted Incomes: Evidence from 800 Million Beneficiaries
Get PDFThis study evaluates the economic impact of the New Rural Cooperative Medical Scheme in China, the world's largest rural public health program, covering over 800 million rural residents. Using longitudinal survey data from villages that gained access to the program in different years, we find that the program improved the probability of being in good health by 4.4% to 8.2% across age groups. For the average participating household, per capita income increased by 20.3% over a decade, driven primarily by greater off-farm labor participation and higher wages, alongside significant agricultural income growth. The aggregate income gains were six times the government's program investments. These effects can be replicated by a structural model that characterizes the health investments and labor allocation of utility-maximizing rural residents. Counterfactual analyses based on the structural model suggest that China could further increase the program's benefits by raising the reimbursement rate up to 0.8 (but not beyond). Additionally, eliminating the current cross-province reimbursement constraints would further boost income gains by 18.7%
Nato expansion: An open door policy?
Get PDFRussia’s 2022 invasion of Ukraine shook the world’s security architecture and ultimately led to Finland and Sweden officially joining NATO in 2023 and 2024 respectively. A key question which arises then, is what determines NATO membership? Is there an open door policy or are accession decisions based on geopolitics? This paper develops a predictive model assessing the probability of joining NATO for several European countries. The model is based on logis- tic regression and shows that the most important determinants of NATO membership are past geopolitics such as EU and USSR memberships. Less important factors include the strength of economy, political stability and geography. Using a sample from 1979 to 2020, the model predicts that Sweden and Finland were highly likely to join NATO, while the probability of Ukraine’s accession is low
High Tech and Innovative Emerging Industries and Pakistan's Policies and Regulations towards Adaptation in the light of China’s Strategies of Reverse Engineering
Get PDFThe evolution of innovation dates back to ancient civilizations and continues to shape modern economies through high-tech advancements. Reverse engineering—a process of deconstructing and enhancing technologies—has been instrumental in industrial growth worldwide, notably in countries like China and Japan. Pakistan’s potential in leveraging reverse engineering remains underutilized, hindered by outdated infrastructure, inadequate R&D investments, weak institutional frameworks, and fragmented policies. Initiatives like STZs and the Digital Pakistan Policy offer promise but suffer from misaligned execution. This study underscores the transformative potential of reverse engineering in Pakistan’s defense, agriculture, pharmaceuticals, and renewable energy sectors. By fostering academia-industry-government collaboration, improving infrastructure, and adopting global best practices, Pakistan can bridge its technological gaps, enhance export competitiveness, and reduce its import dependency. A robust reverse engineering strategy will catalyze innovation, strengthen industrial output, and pave the way for long-term economic sustainability and self-reliance
Work from home trends in European countries
Get PDFThis paper analyzes the evolution of working from home across European countries using data from the European Working Conditions Survey (2005–2021). The study documents a substantial increase in working from home, particularly during the COVID-19 pandemic, with notable cross-country and gender differences. It also examines how working from home correlates with individual characteristics such as gender, age, education, employment status, occupation, and household composition. We find that self-employment, digital work intensity, and higher education are consistently associated with greater working from home prevalence. Conversely, public sector employment and full-time contracts are negatively related to working from home
Work from home and household behaviors
Get PDFThis paper analyzes work from home from a household perspective, focusing on its various relationships with spouses’ wages, household labor supply, expenditures, and chores. We use a collective model that predicts that work-from-home decisions result from joint utility maximization. Using data from the PSID (2011-2021), we find that both partners’ wages and hours are associated with their own and their spouse’s WFH status in pooled specifications, but these associations weaken substantially when accounting for endogeneity and unobserved heterogeneity. Instrumental variable estimates suggest that wage effects are partly driven by occupational sorting, while fixed effects models reveal that changes in WFH status are strongly correlated across spouses but largely unrelated to short-term changes in wages or hours. Implications point to the need for models of remote work that incorporate intra-household dynamics, and to the importance of recognizing WFH as a negotiated outcome rather than an individual choice
Leading with Generosity and Responsibility through Reward Allocation Decisions in Teams
Get PDFLeadership generosity and responsibility are crucial elements in organizational management, particularly when leaders allocate rewards among team members. Through theoretical modeling and experimental validation, we examine leaders' allocation decisions at different stages of a project---before it begins, after completion but before outcomes are realized, and after outcomes are known---and how their decisions depend on their personality traits. Using a preregistered randomized controlled experiment with 520 participants, we examine two key leadership behaviors: generous commitment (taking a smaller share for oneself before the project starts) and responsibility (reducing one's share after poor performance), as well as how personal traits shape these behavioral styles. Our theoretical framework predicts that more altruistic leaders will demonstrate stronger generous commitment while less altruistic leaders, counterintuitively, will demonstrate greater responsibility following negative outcomes. The empirical findings largely support these predictions. Female leaders show more generosity, while both genders demonstrate responsibility by reducing self-allocation following negative outcomes, albeit through different psychological mechanisms. Personality traits, especially altruism, as well as other psychological factors, moderate these behaviors. Our study finds that personality traits that are often associated with "strong" leadership tend not to demonstrate responsibility. These findings provide insights into leadership decision-making, with implications for organizational design and leadership development