Hasil untuk "Regional economics. Space in economics"

Туна Кёсе , Али Осман Озтоп

Since the 2008-09 global financial crisis, both emerging and developed economies have encountered increased economic uncertainty. Despite substantial research on macroeconomic uncertainties, there remains a significant gap in understanding asymmetric causal relationships between inflation uncertainty and economic growth in inflation-targeting emerging markets. This study addresses this gap by exploring both symmetric and asymmetric causality between inflation uncertainty and economic growth in selected countries: Brazil, Bulgaria, Czech Republic, Greece, India, Korea, Mexico, Russia, and Türkiye. Asymmetric causality tests are crucial as they offer a more nuanced view of how inflation uncertainty and economic growth impact each other in distinct ways, which is vital for enhancing macroeconomic stability and policy effectiveness. The research employs the ARMA-GARCH model to estimate inflation uncertainty and applies both symmetric and asymmetric causality tests. The findings reveal a unidirectional causality from inflation uncertainty to economic growth in Brazil and Bulgaria, and from economic growth to inflation uncertainty in Russia and Türkiye. Furthermore, asymmetric shock analysis shows that negative shocks in inflation uncertainty lead to negative shocks in economic growth in Russia and Korea, while positive shocks in inflation uncertainty correspond with positive shocks in economic growth in India. These insights can help policymakers in emerging markets develop more effective monetary policies. Future research should include a broader range of countries and additional macroeconomic variables to validate these findings and explore inflation uncertainty dynamics further.

Eliseo Curcio

As artificial intelligence (AI) becomes foundational to enterprise infrastructure, organizations face growing challenges in accurately assessing the full economic implications of AI deployment. Existing metrics such as API token costs, GPU-hour billing, or Total Cost of Ownership (TCO) fail to capture the complete lifecycle costs of AI systems and provide limited comparability across deployment models. This paper introduces the Levelized Cost of Artificial Intelligence (LCOAI), a standardized economic metric designed to quantify the total capital (CAPEX) and operational (OPEX) expenditures per unit of productive AI output, normalized by valid inference volume. Analogous to established metrics like LCOE (levelized cost of electricity) and LCOH (levelized cost of hydrogen) in the energy sector, LCOAI offers a rigorous, transparent framework to evaluate and compare the cost-efficiency of vendor API deployments versus self-hosted, fine-tuned models. We define the LCOAI methodology in detail and apply it to three representative scenarios, OpenAI GPT-4.1 API, Anthropic Claude Haiku API, and a self-hosted LLaMA-2-13B deployment demonstrating how LCOAI captures critical trade-offs in scalability, investment planning, and cost optimization. Extensive sensitivity analyses further explore the impact of inference volume, CAPEX, and OPEX variability on lifecycle economics. The results illustrate the practical utility of LCOAI in procurement, infrastructure planning, and automation strategy, and establish it as a foundational benchmark for AI economic analysis. Policy implications and areas for future refinement, including environmental and performance-adjusted cost metrics, are also discussed.

Francis Dennig, Bassel Tarbush

We characterize the outcomes of a canonical deterministic model for the intergenerational transmission of capital that features differential fertility. A fertility function determines the relationship between parental capital and the number of children, and a transmission function determines the relationship between the capital of a parent and that of their children. Together these functions generate an evolving cross-sectional distribution of capital. We establish easy-to-verify conditions on the fertility and transmission functions that guarantee (a) that the dynamical system has a steady state distribution that is either atomless (exhibiting inequality) or degenerate (not exhibiting inequality), and (b) that the system converges to such states from essentially any initial distribution. Our characterization provides new insights into the link between differential fertility and long-run cross-sectional inequality, and it gives rise to novel comparative statics relating the two. We apply our results to several parametric examples and to a model of economic growth that features endogenous differential fertility.

Tianyu Fan

This paper introduces a new event-based measure of bilateral geopolitical alignment and provides evidence that it shapes economic growth. The measure is built from 373,020 geopolitical events across 193 countries over 1960--2024, compiled using large language models. With local projections exploiting within-country temporal variation, we find that a one-standard-deviation permanent improvement in geopolitical alignment increases GDP per capita by approximately 10 percent over 25 years. These effects are associated with improvements in domestic stability, investment, productivity, trade, and human capital. In accounting exercises, geopolitical factors account for GDP variations ranging from -30 to +30 percent across countries and time periods.

Luca Corazzini, Elisa Deriu, Marco Guerzoni

Large language models (LLMs) increasingly mediate economic and organisational processes, from automated customer support and recruitment to investment advice and policy analysis. These systems are often assumed to embody rational decision making free from human error; yet they are trained on human language corpora that may embed cognitive and social biases. This study investigates whether advanced LLMs behave as rational agents or whether they reproduce human behavioural tendencies when faced with classic decision problems. Using two canonical experiments in behavioural economics, the ultimatum game and a gambling game, we elicit decisions from two state of the art models, Google Gemma7B and Qwen, under neutral and gender conditioned prompts. We estimate parameters of inequity aversion and loss-aversion and compare them with human benchmarks. The models display attenuated but persistent deviations from rationality, including moderate fairness concerns, mild loss aversion, and subtle gender conditioned differences.

Eduardo Koffmann Jopia, Patricia Galilea Aranda

Does it matter whether a government is "left wing" or "right wing" for economic growth? Using a panel of 113 countries (1995 2022), we combine: (i) the economic ideology of the executive branch (V Dem), (ii) the disaggregated institutional quality of the economic freedom index (Heritage), separating a core institutional block (HN: property rights, government integrity, judicial effectiveness) from a block of liberalization policies (HL: trade/financial openness, regulatory efficiency, size of government), and (iii) economic performance (GDP per capita PPP and its growth, World Bank). We estimate panel models with fixed effects by country and year, and standard errors grouped by country. We find that HN is strongly associated with higher income levels, while HL, on average globally, is not significant for income level once HN is controlled for, nor does it consistently predict short term growth. Government ideology exhibits weak direct effects on growth, although it operates indirectly via HL (right wing governments tend to have higher HL scores). Robustness tests with long five-year differences and country specific trends reinforce that, in the long run, "institutions prevail over politics." We conclude with recommendations for developing countries: prioritize the institutional core (rule of law, anti-corruption, effective justice) as a basis for policies whether left-wing or right wing to bear fruit in terms of growth

Merlinda Andoni, Benoit Couraud, Valentin Robu et al.

Amid global interest in resilient energy systems, green hydrogen is considered vital to the net-zero transition, yet its deployment remains limited by high production cost. The cost is determined by the its production pathway, system configuration, asset location, and interplay with electricity markets and regulatory frameworks. To compare different deployment strategies in the UK, we develop a comprehensive techno-economic framework based on the Levelised Cost of Hydrogen (LCOH) assessment. We apply this framework to 5 configurations of wind-electrolyser systems, identify the most cost-effective business cases, and conduct a sensitivity analysis of key economic parameters. Our results reveal that electricity cost is the dominant contributor to LCOH, followed by the electrolyser cost. Our work highlights the crucial role that location, market arrangements and control strategies among RES and hydrogen investors play in the economic feasibility of deploying green hydrogen systems. Policies that subsidise low-cost electricity access and optimise deployment can lower LCOH, enhancing the economic competitiveness of green hydrogen.

Shailender Singh, Amar Singh, Arvind Mohan et al.

In Central Europe and the Baltic region, healthcare expenditure has been growing slightly faster than across the euro area and in OECD countries. However, health outcomes as re­gards chronic diseases prove to be modest in the euro area and OECD countries compared to Central Europe and the Baltic region. Panel data analysis and country-specific regres­sions were conducted using World Bank data spanning from 2000 to 2019. Evidence sug­gests a significant correlation between private and current health expenditures and reduced ­mortality from chronic diseases in males, females and the total population across the panel, leading to improved longevity. Yet, public health expenditure does not correlate with a sub­stantial reduc­tion in mortality or a higher lifespan among the population, whether consid­ered collectively or among males and females separately. Similarly, an increase in current health expenditure by one unit leads to significant reductions in mortality from non-com­municable diseases: by 29 percent in the total population, 22 percent in females and 36 per­cent in males. Public health spending in Lithuania and Russia has been shown to decrease mortality from non-com­municable diseases. Furthermore, chronic mortality is associated with a significant decline in labour productivity: by 42 percent in the total population, 40 percent in males and 45 percent in females. Therefore, interventions implemented through public health systems may reduce mortality from chronic conditions in the study countries.

Anton Pichler, Jan Hurt, Tobias Reisch et al.

The Russian invasion of Ukraine on February 24, 2022 entailed the threat of a drastic and sudden reduction of natural gas supply to the European Union. This paper presents a techno-economic analysis of the consequences of a sudden gas supply shock to Austria, one of the most dependent countries on imports of Russian gas. Our analysis comprises (a) a detailed assessment of supply and demand side countermeasures to mitigate the immediate shortfall in Russian gas imports, (b) a mapping of the net reduction in gas supply to industrial sectors to quantify direct economic shocks and expected relative reductions in gross output and (c) the quantification of higher-order economic impacts through using a dynamic out-of-equilibrium input-output model. Our results show that potential economic consequences can range from relatively mild to highly severe, depending on the implementation and success of counteracting mitigation measures. We find that securing alternative gas imports, storage management, and incentivizing fuel switching represent the most important short-term policy levers to mitigate the adverse impacts of a sudden import stop.

Maria Laura Victoria Marques, Ronaldo Seroa da Motta, Daniel de Abreu Pereira Uhr et al.

The journal Energy Economics, a leading international peer-reviewed outlet for economic theory in the energy sector, celebrates its 45th anniversary in 2024. This article uses a bibliometric approach to present a retrospective of the journal's contributions. The study includes all publications from the journal based on data from the Web of Science and Scopus databases. The resulting sample comprises 6,563 documents covering the period from 1979 to April 2024. The annual publication rate increased by 1.02 percent, with an average of 40.07 citations per document. Institutions from the United States of America and China lead in the number of articles published in the journal. A co-occurrence analysis of keywords was conducted, complemented by a sub-sample analysis, to provide a detailed view of thematic development and evolution over time. Finally, the article highlights future thematic trends of the journal, offering insights for editorial guidelines and interested authors.

Monika Daňová , Elena Širá

Человеческий капитал — важный фактор экономического роста и развития социально-экономических систем. Однако вопросы, связанные с адекватным выражением ценности человеческого капитала и механизмами его влияния на экономическое развитие, до сих пор остаются открытыми. В статье выдвигается гипотеза о наличии взаимосвязи между человеческим капиталом и экономическим ростом. Для ее проверки проанализированы данные стран Вишеградской группы за период 2000–2019 гг. При помощи статистических методов исследована причинно-следственная связь между некоторыми аспектами человеческого капитала и экономического роста, а также условиями, обеспечивающими положительный эффект. Также проанализирована роль некоторых характеристик, используемых для выражения влияния человеческого капитала на экономический рост. Представленная в статье модель продемонстрировала наличие положительной статистически значимой связи между валовым внутренним продуктом на душу населения и показателями инновационного потенциала человеческого капитала и квалификации работников. Влияние инструментов создания и развития человеческого капитала проявляется в долгосрочном периоде и снижается из-за одновременного воздействия иных факторов рынка труда. К примеру, пандемия Covid-19 негативно повлияла на развитие экономики, что привело к соответствующим изменениям в сфере занятости, в частности к переходу на удаленную работу. Воздействие подобной трансформации на экономический рост представляет научный интерес. Изменения в карьерном продвижении сотрудников и отношении компаний к человеческому капиталу также являются перспективной темой для дальнейших исследований, которые можно проводить раз в несколько лет.

Egor A. Prokopyev

ntroduction. Effective management of regional socioeconomic development processes is not possible without an objective understanding of impact on the economy exerted by internal territorial disparities. The lack of open data in the official statistics concerning settlements and displaying such a basic indicator as an average wage does not contribute to the task also. For the first time, the suggested solution of the following problem is to use an alternative source of data ‒ Russian form of personal income tax (5-NDFL) tax reports. The goal of the article is to determine territorial disparities between average wages on the settlement level in the North-West Federal District. Materials and Methods. The research covers all municipalities of the North-West Federal District from 2015 to 2020. Average wages in urban and rural settlements, municipal districts and city districts were calculated based on the analysis of 7947 5-NDFL tax reports. A comparison was made with the data from the official statistics. The coefficient of variation and the Gini index were calculated for each area and the North-West District in whole as well as the difference between progressive and regressive types of average wages. Mappings were made for selected municipal areas. Results. Based on the data extracted from 5-NDFL forms, the research suggests a method of average wage calculation in municipalities. The proof is given that the following tax reports can be viewed as an appropriate source of data for determination of income inequality in case of settlements. It is established that territorial disparities in the Federal District have decreased due to the slight growth of average and median wages. Through the example of selected municipal districts, the research displays the existing difference in wages amid urban and rural settlements and also indicates the decisive role of the area center in the consolidated regional scores. Discussion and Conclusion. A comparative analysis of inequality indicators in wages has revealed higher values of territorial disparities at the settlement level. In practical terms, the transition from district values of indicators to settlement values in the state monitoring system makes it possible to increase the objectivity of assessing ongoing processes and improve the quality of managerial decision-making.

Marco Gortan, Lorenzo Testa, Giorgio Fagiolo et al.

Although high-resolution gridded climate variables are provided by multiple sources, the need for country and region-specific climate data weighted by indicators of economic activity is becoming increasingly common in environmental and economic research. We process available information from different climate data sources to provide spatially aggregated data with global coverage for both countries (GADM0 resolution) and regions (GADM1 resolution) and for a variety of climate indicators (average precipitations, average temperatures, average SPEI). We weigh gridded climate data by population density or by night light intensity -- both proxies of economic activity -- before aggregation. Climate variables are measured daily, monthly, and annually, covering (depending on the data source) a time window from 1900 (at the earliest) to 2023. We pipeline all the preprocessing procedures in a unified framework, which we share in the open-access Weighted Climate Data Repository web app. Finally, we validate our data through a systematic comparison with those employed in leading climate impact studies.

Niels Gillmann, Ostap Okhrin

The availability of data on economic uncertainty sparked a lot of interest in models that can timely quantify episodes of international spillovers of uncertainty. This challenging task involves trading off estimation accuracy for more timely quantification. This paper develops a local vector autoregressive model (VAR) that allows for adaptive estimation of the time-varying multivariate dependency. Under local, we mean that for each point in time, we simultaneously estimate the longest interval on which the model is constant with the model parameters. The simulation study shows that the model can handle one or multiple sudden breaks as well as a smooth break in the data. The empirical application is done using monthly Economic Policy Uncertainty data. The local model highlights that the empirical data primarily consists of long homogeneous episodes, interrupted by a small number of heterogeneous ones, that correspond to crises. Based on this observation, we create a crisis index, which reflects the homogeneity of the sample over time. Furthermore, the local model shows superiority against the rolling window estimation.

Vargas-Hernández José G., Rakowska Joanna, Vargas-González Omar C.

Subject and purpose of work: This study aims to analyse the main elements of the green economic development as a framework for green finance and green investment. The analysis spurs from the underlying notion that green economics is inherently a normative framework and a school of thought development of the neo-classical economic thinking with conceptual assumptions, deficiencies, and contradictions, beginning to set out the roots, aims and philosophical principles.

Jo Blanden, Matthias Doepke, Jan Stuhler

This chapter provides new evidence on educational inequality and reviews the literature on the causes and consequences of unequal education. We document large achievement gaps between children from different socio-economic backgrounds, show how patterns of educational inequality vary across countries, time, and generations, and establish a link between educational inequality and social mobility. We interpret this evidence from the perspective of economic models of skill acquisition and investment in human capital. The models account for different channels underlying unequal education and highlight how endogenous responses in parents' and children's educational investments generate a close link between economic inequality and educational inequality. Given concerns over the extended school closures during the Covid-19 pandemic, we also summarize early evidence on the impact of the pandemic on children's education and on possible long-run repercussions for educational inequality.

Flera K. Sokolova, Anna V. Lyalina

A well-acknowledged driver of change, population movement intensifies the development of coastal territories. The Russian North-West holds a vast coastal zone. Granting access to the Baltic, the White, and the Barents Seas, it is an area of geostrategic importance where much of the country’s coastal economy — one of the national priorities — is located. Push and pull factors are enormously diverse in the area, as are migration flows forming attraction poles for migrants. There is little research on the issue despite its social and practical significance. Thus, research is required to examine how the coastal factor can benefit the migration attractiveness and human resources of Russian coastal territories of geostrategic importance. This study aims to delineate coastal territories and investigate local migration flows compared to those recorded in inland regions. The research draws on the concept of coastalisation, employing universal, geographical, and statistical research methods. It uses documentary sources and official 2011—2020 statistics. The findings show that the coastal position and maritime economic activity are relevant factors for migration attractiveness. Saint Petersburg and the coastal municipalities of the Leningrad and Kaliningrad regions are more attractive to migrants than more northerly territories. However, there are attraction poles farther north too, and the coastal zone of the Arkhangelsk region attracts more migrants than its inland part. The study demonstrates the growing polarisation of migration space in the coastal areas and especially agglomerations. Changes in the age structure of immigration flows have caused social factors in attractiveness to migrants to replace employment-related factors.

Pavel V. Druzhinin, Ekaterina V. Molchanova

Introduction. The COVID-19 (coronavirus) pandemic has had a strong impact on the socio-economic situation in the country, especially on demographic processes. The article analyzes the change in the mortality rates in Russian regions and assesses the influence of various factors on them during the pandemic. Materials and Methods. The paper examined data from the Federal State Statistics Service on mortality rates in Russian regions. Based on the graphs analyzed and regression equations built, the factors that determined the increase in mortality rates during the pandemic and the degree of their influence were identified. Results. Changes in the rates of morbidity and mortality in Russian regions depended on the development of the healthcare system, demographic, socio-economic, and geographical factors, as well as on the actions of regional and federal authorities. The geographical location of the regions turned out to be the determining factor. The highest mortality rates were found in the regions located in the center of the European part of Russia at the intersection of transport routes. In some months, high mortality rates were observed in the regions bordering China, Kazakhstan, and Finland. The proportion of pensioners and the degree of decline in personal income were also significant. Discussion and Conclusion. Calculations have shown that at the beginning of both waves of the pandemic, the increase in mortality rates depended on the provision of the population of the regions with doctors and hospital beds. In the spring, the restrictions imposed restrained the spread of the disease, but led to an economic recession and an increase in unemployment. In the autumn, less severe restrictions were introduced, which led to a significant increase in mortality rates and a slight decline in the economy. The research results can be used to optimize the managerial decisions in the field of medical and demographic policy.

A. G. A. Cariappa, B. S. Chandel, G. Sankhala et al.

Calcium (Ca) requirement increases tenfold upon parturition in dairy cows & buffaloes and its deficiency leads to a condition called milk fever (MF). Estimation of losses is necessary to understand the depth of the problem and design preventive measures. How much is the economic loss due to MF? What will be the efficiency gain if MF is prevented at the advent of a technology? We answer these questions using survey data and official statistics employing economic surplus model. MF incidence in sample buffaloes and cows was 19% and 28%, respectively. Total economic losses were calculated as a sum total of losses from milk production, mortality of animals and treatment costs. Yearly economic loss due to MF was estimated to be INR 1000 crores (US$ 137 million) in Haryana. Value of milk lost had the highest share in total economic losses (58%), followed by losses due to mortality (29%) and treatment costs (13%). Despite lower MF incidence, losses were higher in buffaloes due to higher milk prices and market value of animals. The efficiency gain accruing to producers if MF is prevented, resulting from increased milk production at decreased costs was estimated at INR 10990 crores (US$ 1.5 billion). As the potential gain if prevented is around 10 times the economic losses, this study calls for the use of preventive technology against MF.