We develop an iterative framework for economic measurement that leverages large language models to extract measurement structure directly from survey instruments. The approach maps survey items to a sparse distribution over latent constructs through what we term a soft mapping, aggregates harmonized responses into respondent level sub dimension scores, and disciplines the resulting taxonomy through out of sample incremental validity tests and discriminant validity diagnostics. The framework explicitly integrates iteration into the measurement construction process. Overlap and redundancy diagnostics trigger targeted taxonomy refinement and constrained remapping, ensuring that added measurement flexibility is retained only when it delivers stable out of sample performance gains. Applied to a large scale public employee retirement plan survey, the framework identifies which semantic components contain behavioral signal and clarifies the economic mechanisms, such as beliefs versus constraints, that matter for retirement choices. The methodology provides a portable measurement audit of survey instruments that can guide both empirical analysis and survey design.
This paper examines Modern Mercantilism, characterized by rising economic nationalism, strategic technological decoupling, and geopolitical fragmentation, as a disruptive shift from the post-1945 globalization paradigm. It applies Principal Component Analysis (PCA) to 768-dimensional SBERT-generated semantic embeddings of curated news articles to extract orthogonal latent factors that discriminate binary event outcomes linked to protectionism, technological sovereignty, and bloc realignments. Analysis of principal component loadings identifies key semantic features driving classification performance, enhancing interpretability and predictive accuracy. This methodology provides a scalable, data-driven framework for quantitatively tracking emergent mercantilist dynamics through high-dimensional text analytics
Society as a whole faces a host of economic tradeoffs, many of which emerge around economic policies. An example of tradeoffs that any society faces in many economic realms is the tradeoff between economic efficiency and income equality (aka the efficiency-equality tradeoff). This tradeoff has been called "the Big Tradeoff" by the esteemed economist Arthur Okun, who also termed it "the Double Standard of a Capitalist Democracy." Although the efficiency-equality tradeoff is more or less an inevitable tradeoff in most societal settings and economic contexts, there are still some special circumstances in which this tradeoff can be avoided. This paper identifies five such avenues and elaborates on why and how the tradeoff between these two somewhat contradictory societal goals-efficiency and equality-can be deftly averted under the mentioned circumstances. These avenues with their transformative potential can and should be used so that a capitalist society as an integrated whole can promote both efficiency and equality at the same time under these scenarios and avoid facing the Big Tradeoff in cases where it is evitable. Static and dynamic economic models are developed, solved, and applied to facilitate the articulation and exposition of the main points of each solution with formal rigor and logical coherence. Finally, policy implications are discussed.
This study employs a co-integrated socio-economic model to investigate the long-run drivers of Chinese government expenditure on public pensions, addressing critical stability and sustainability challenges. Our methodology establishes a genuine long-run relationship and confirmed uni-directional causality from key socioeconomic variables to government spending. The central finding is the confirmation that China still possesses an exploitable demographic dividend (DD), which counters widespread assumptions of an immediate demographic crisis and provides a limited window for proactive policy action. However, the analysis also conclusively demonstrates that relying solely on strong GDP growth is insufficient for fund stabilization. Sustainability is fundamentally governed by the ratio of contributors to pensionaries. Consequently, the study concludes that comprehensive, structural labour market reforms are mandatory to maximize the current DD and strategically mitigate the financial imbalance caused by the eventual absence of this demographic advantage.
The strategic choice of model "openness" has become a defining issue for the foundation model (FM) ecosystem. While this choice is intensely debated, its underlying economic drivers remain underexplored. We construct a two-period game-theoretic model to analyze how openness shapes competition in an AI value chain, featuring an incumbent developer, a downstream deployer, and an entrant developer. Openness exerts a dual effect: it amplifies knowledge spillovers to the entrant, but it also enhances the incumbent's advantage through a "data flywheel effect," whereby greater user engagement today further lowers the deployer's future fine-tuning cost. Our analysis reveals that the incumbent's optimal first-period openness is surprisingly non-monotonic in the strength of the data flywheel effect. When the data flywheel effect is either weak or very strong, the incumbent prefers a higher level of openness; however, for an intermediate range, it strategically restricts openness to impair the entrant's learning. This dynamic gives rise to an "openness trap," a critical policy paradox where transparency mandates can backfire by removing firms' strategic flexibility, reducing investment, and lowering welfare. We extend the model to show that other common interventions can be similarly ineffective. Vertical integration, for instance, only benefits the ecosystem when the data flywheel effect is strong enough to overcome the loss of a potentially more efficient competitor. Likewise, government subsidies intended to spur adoption can be captured entirely by the incumbent through strategic price and openness adjustments, leaving the rest of the value chain worse off. By modeling the developer's strategic response to competitive and regulatory pressures, we provide a robust framework for analyzing competition and designing effective policy in the complex and rapidly evolving FM ecosystem.
Important game-changer economic events and transformations cause uncertainties that may affect investment decisions, capital flows, international trade, and macroeconomic variables. One such major transformation is Brexit, which refers to the multiyear process through which the UK withdrew from the EU. This study develops and uses a new Brexit-Related Uncertainty Index (BRUI). In creating this index, we apply Text Mining, Context Window, Natural Language Processing (NLP), and Large Language Models (LLMs) from Deep Learning techniques to analyse the monthly country reports of the Economist Intelligence Unit from May 2012 to January 2025. Additionally, we employ a standard vector autoregression (VAR) analysis to examine the model-implied responses of various macroeconomic variables to BRUI shocks. While developing the BRUI, we also create a complementary COVID-19 Related Uncertainty Index (CRUI) to distinguish the uncertainties stemming from these distinct events. Empirical findings and comparisons of BRUI with other earlier-developed uncertainty indexes demonstrate the robustness of the new index. This new index can assist British policymakers in measuring and understanding the impacts of Brexit-related uncertainties, enabling more effective policy formulation.
Wildfires in urbanized regions, particularly within the wildland-urban interface, have significantly intensified in frequency and severity, driven by rapid urban expansion and climate change. This study aims to provide a comprehensive, fine-grained evaluation of the recent 2025 Los Angeles wildfire's impacts, through a multi-source, tri-environmental framework in the social, built and natural environmental dimensions. This study employed a spatiotemporal wildfire impact assessment method based on daily satellite fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS), infrastructure data from OpenStreetMap, and high-resolution dasymetric population modeling to capture the dynamic progression of wildfire events in two distinct Los Angeles County regions, Eaton and Palisades, which occurred in January 2025. The modelling result estimated that the total direct economic losses reached approximately 4.86 billion USD with the highest single-day losses recorded on January 8 in both districts. Population exposure reached a daily maximum of 4,342 residents in Eaton and 3,926 residents in Palisades. Our modelling results highlight early, severe ecological and infrastructural damage in Palisades, as well as delayed, intense social and economic disruptions in Eaton. This tri-environmental framework underscores the necessity for tailored, equitable wildfire management strategies, enabling more effective emergency responses, targeted urban planning, and community resilience enhancement. Our study contributes a highly replicable tri-environmental framework for evaluating the natural, built and social environmental costs of natural disasters, which can be applied to future risk profiling, hazard mitigation, and environmental management in the era of climate change.
This study develops a conceptual simulation model for a tokenized recycling incentive system that integrates blockchain infrastructure, market-driven pricing, behavioral economics, and carbon credit mechanisms. The model aims to address the limitations of traditional recycling systems, which often rely on static government subsidies and fail to generate sustained public participation. By introducing dynamic token values linked to real-world supply and demand conditions, as well as incorporating non-monetary behavioral drivers (e.g., social norms, reputational incentives), the framework creates a dual-incentive structure that can adapt over time. The model uses Monte Carlo simulations to estimate outcomes under a range of scenarios involving operational costs, carbon pricing, token volatility, and behavioral adoption rates. Due to the absence of real-world implementations of such integrated blockchain-based recycling systems, the paper remains theoretical and simulation-based. It is intended as a prototype framework for future policy experimentation and pilot projects. The model provides insights for policymakers, urban planners, and technology developers aiming to explore decentralized and market-responsive solutions to sustainable waste management. Future work should focus on validating the model through field trials or behavioral experiments.
This paper integrates Austrian capital theory with repeated game theory to examine strategic miner behaviour under different institutional conditions in blockchain systems. It shows that when protocol rules are mutable, effective time preference rises, undermining rational long-term planning and cooperative equilibria. Using formal game-theoretic analysis and Austrian economic principles, the paper demonstrates how mutable protocols shift miner incentives from productive investment to political rent-seeking and influence games. The original Bitcoin protocol is interpreted as an institutional anchor: a fixed rule-set enabling calculability and low time preference. Drawing on the work of Bohm-Bawerk, Mises, and Hayek, the argument is made that protocol immutability is essential for restoring strategic coherence, entrepreneurial confidence, and sustainable network equilibrium.
The Gulf Cooperation Council countries -- Oman, Bahrain, Kuwait, UAE, Qatar, and Saudi Arabia -- holds strategic significance due to its large oil reserves. However, these nations face considerable challenges in shifting from oil-dependent economies to more diversified, knowledge-based systems. This study examines the progress of Gulf Cooperation Council (GCC) countries in achieving economic diversification and social development, focusing on the Social Progress Index (SPI), which provides a broader measure of societal well-being beyond just economic growth. Using data from the World Bank, covering 2010 to 2023, the study employs the XGBoost machine learning model to forecast SPI values for the period of 2024 to 2026. Key components of the methodology include data preprocessing, feature selection, and the simulation of independent variables through ARIMA modeling. The results highlight significant improvements in education, healthcare, and women's rights, contributing to enhanced SPI performance across the GCC countries. However, notable challenges persist in areas like personal rights and inclusivity. The study further indicates that despite economic setbacks caused by global disruptions, including the COVID-19 pandemic and oil price volatility, GCC nations are expected to see steady improvements in their SPI scores through 2027. These findings underscore the critical importance of economic diversification, investment in human capital, and ongoing social reforms to reduce dependence on hydrocarbons and build knowledge-driven economies. This research offers valuable insights for policymakers aiming to strengthen both social and economic resilience in the region while advancing long-term sustainable development goals.
Jo-An Occhipinti, William Hynes, Ante Prodan
et al.
Work is fundamental to societal prosperity and mental health, providing financial security, identity, purpose, and social integration. The emergence of generative artificial intelligence (AI) has catalysed debate on job displacement. Some argue that many new jobs and industries will emerge to offset the displacement, while others foresee a widespread decoupling of economic productivity from human input threatening jobs on an unprecedented scale. This study explores the conditions under which both may be true and examines the potential for a self-reinforcing cycle of recessionary pressures that would necessitate sustained government intervention to maintain job security and economic stability. A system dynamics model was developed to undertake ex ante analysis of the effect of AI-capital deepening on labour underutilisation and demand in the economy. Results indicate that even a moderate increase in the AI-capital-to-labour ratio could increase labour underutilisation to double its current level, decrease per capita disposable income by 26% (95% interval, 20.6% - 31.8%), and decrease the consumption index by 21% (95% interval, 13.6% - 28.3%) by mid-2050. To prevent a reduction in per capita disposable income due to the estimated increase in underutilization, at least a 10.8-fold increase in the new job creation rate would be necessary. Results demonstrate the feasibility of an AI-capital- to-labour ratio threshold beyond which even high rates of new job creation cannot prevent declines in consumption. The precise threshold will vary across economies, emphasizing the urgent need for empirical research tailored to specific contexts. This study underscores the need for governments, civic organisations, and business to work together to ensure a smooth transition to an AI- dominated economy to safeguard the Mental Wealth of nations.
Abstract Faced with increasingly serious environmental risks, it is necessary to conduct a comprehensive evaluation of the regional environment to provide a solid foundation for environmental policies and actions in the future. This article builds a composite environment risk index that considers spatiotemporal factors and uses annual socio-economic and environmental data of China’s 31 provincial administrative regions from 2004 to 2019 to quantitatively analyze environmental risks. Furthermore, the article employs a panel data model to empirically test the key factors that lead to environmental risks. Moreover, this article employs SVAR models to analyze the dynamics of regional environmental systems in China. The study finds that, at least at this stage, the environmental risks in provincial regions in China are still relatively high, and the key factors of the risks are economic growth, urbanization development, secondary industry growth, and green policy. Therefore, China must adopt more stringent environmental protection policies and actions in the future.
Narratives that portray macroeconomic policies in Japan as unlike ones pursued in other large economies persist. I revisit how several factors, including monetary, fiscal, and demographic factors impact Japan, the US, and the euro area. Panel VARs driven by factors or observed macroeconomic determinants are used. Many, but not all, of the shocks examined have similar impact across all three economies considered. This is true for monetary policy and the response of global inflation to demographic shocks. The response of real economic activity to many of the shocks considered is also comparable. Fiscal and demographic factors, often omitted in studies of this kind, also significantly impact all three economies although the size of the response does differ across the economies examined. Japan may not be like other systemically important economies in all respects, but its experience is less idiosyncratic than usually portrayed.
México tiene firmados 13 tratados comerciales con 50 países, sin embargo, cerca del 80% de su comercio lo realiza únicamente con Estados Unidos. Por ende, resulta crucial diversificar las relaciones comerciales de México con otros países, y América Latina se presenta como una oportunidad prometedora. Esta investigación tiene como objetivo determinar el tipo de comercio de México con los países de Sudamérica (si es intra-industrial o inter-industrial), durante el periodo 2010-2019, a través de la aplicación de la metodología de Grubel y Lloyd (1975, 1979). Los hallazgos revelan que, aunque el comercio de México con los países de Sudamérica es poco relevante, también se observa que el Índice de Comercio Intraindustrial (ICI) se ha incrementado con el paso de los años. En este trabajo, se evidencia que únicamente Argentina y Brasil presentan un IGL relevante de los 10 países analizados, mientras que con los restantes ocho países se mantiene un comercio de menor relevancia, pero con un incremento progresivo durante el periodo de estudio. Es importante destacar que el proceso de globalización ha desempeñado un papel fundamental en el comercio internacional tanto de América del Sur como de México, al abrir nuevos mercados y fomentar la diversificación de productos y servicios.
Celem niniejszego artykułu jest przedstawienie stanu współpracy między Polską a Stanami Zjednoczonymi na przestrzeni ostatnich kilku lat. Od początku lat 90. współpraca polsko-amerykańska odbywa się w kilku obszarach: wojskowym, politycznym i gospodarczym. Bliskie relacje sojusznicze między tymi partnerami są kluczowe dla utrzymania architektury bezpieczeństwa w Europie Środkowej i przeciwdziałania imperialnej polityce Rosji. Intensyfikacja współpracy w obszarach wojskowym, politycznym i gospodarczym nastąpiła po 2015 roku i zmianach politycznych w Polsce. Kolejnym impulsem do zacieśnienia współpracy była agresja Rosji na Ukrainę, która rozpoczęła się w lutym 2022 roku.
In recent years, European regulators have debated restricting the time an online tracker can track a user to protect consumer privacy better. Despite the significance of these debates, there has been a noticeable absence of any comprehensive cost-benefit analysis. This article fills this gap on the cost side by suggesting an approach to estimate the economic consequences of lifetime restrictions on cookies for publishers. The empirical study on cookies of 54,127 users who received 128 million ad impressions over 2.5 years yields an average cookie lifetime of 279 days, with an average value of EUR 2.52 per cookie. Only 13% of all cookies increase their daily value over time, but their average value is about four times larger than the average value of all cookies. Restricting cookies lifetime to one year (two years) decreases their lifetime value by 25% (19%), which represents a decrease in the value of all cookies of 9% (5%). In light of the EUR 10.60 billion cookie-based display ad revenue in Europe, such restrictions would endanger EUR 904 million (EUR 576 million) annually, equivalent to EUR 2.08 (EUR 1.33) per EU internet user. The article discusses these results' marketing strategy challenges and opportunities for advertisers and publishers.
Purpose ― Reasons why Multinational Enterprise (MNEs) engage in foreign direct investment (hereafter referred to as FDI) abroad have been of great interest to policy markets, academia and international portfolio investors. This examines FDI inflow motives to the Middle East and North Africa (MENA) region for the period 2005 to 2019.
Design/methodology/approach ― This research paper applies both the static and dynamic panel methodologies such as SYS-GMM, fixed effects, and pooled OLS estimators to investigate the motivational factors of MNEs FDI inflows to MENA countries.
Findings ― Although specificity applies to countries, estimated results suggest that MNEs in the MENA region are predominantly interested in serving both home and host markets. Other motives such as efficiency-seeking FDI vary across countries, indicating that FDI motives are not homogeneous among region members. This paper provides useful insight for both firms and host countries in the region.
Originality/value ― This research paper investigates the factors that motivate MNEs to consider FDI decisions in MENA countries. Rather than investigate the individual countries within the region as done in existing literature, this research paper simultaneously examines MNEs' investment motivations in the MENA region. The findings are significant, plausible and in line with the economic development of most countries in the region.
Economic growth, development, planning, Regional economics. Space in economics
Charnavalau Aliaksandr Viktor, Kuźmicki Marek Grzegorz, Charnavalava Zanna Vasylij
Subject and purpose of the work: Working time management has become particularly relevant by mid-20th century. It has now become one of the top areas of interest for scientists who conduct research on management. This study is designed to review and evaluate selected new forms of work organization in the reality of today’s digital economy.
Regional economics. Space in economics, Economics as a science