Hasil untuk "Economic theory. Demography"

Sabrina Chiodo, Sonia M. Grandi, Jessica Gronsbell et al.

Introduction Perinatal outcomes are shaped by clinical, social, and environmental factors, yet Canada lacks a nationally representative pregnancy cohort capturing these influences at the individual-level. This gap has limited the ability to address multifactorial drivers of maternal and fetal health. To fill this need, we established a linked cohort integrating survey, clinical, and contextual data to support equity-focused, precision public health research in maternal health. Methods We linked the Canadian Community Health Survey (CCHS; 2000--2017) to the Discharge Abstract Database (DAD) using Statistics Canada's Social Data Linkage Environment. Eligible participants were female (as defined by the binary CCHS sex variable), aged 15-49 years, with a hospital delivery within two years of their CCHS interview. We excluded multifetal gestations and retained only the first delivery per individual. Area-level and environmental exposures (i.e., neighbourhood inequity, pollution, greenspace, neighbourhood walkability, etc.) were appended via residential postal codes using the Postal Code Conversion File Plus (PCCF+). Results The cohort includes 13,360 singleton births. Pre-pregnancy data include sociodemographics, health behaviours, chronic conditions, psychosocial factors, and reproductive history. Contextual measures capture neighbourhood marginalization, air pollution, greenness, and built environment characteristics. In the CCHS, individuals who reported being pregnant at interview and those who did not (but later delivered) had similar characteristics (SMDs < 0.1), except for age and marital status. Data quality is supported by Statistics Canada's survey protocols, CIHI's hospital validation processes, and standardised geocoding. Conclusion Approved researchers can recreate this dataset within Statistics Canada's Research Data Centres using reproducible R code, which will become openly available on GitHub. The cohort enables research across descriptive epidemiology, causal inference, predictive modelling, and health equity evaluation, supporting investigations into multilevel determinants of maternal health. Future work should prioritise national mother--child linkages to expand life course research.

SPULBAR CRISTI , DUPIR MIHAI CATALIN

This article analyses the evolution, structure, and dynamics of the academic literature on green finance in the context of climate change, using a bibliometric approach applied to publications indexed in the Web of Science – Core Collection for the period 2001–2025. The methodology is based on descriptive and relational bibliometric indicators, including the analysis of scientific production, sources, authors’ impact, co-authorship networks, and keyword co occurrence, complemented by thematic maps and temporal analyses of emerging themes, conducted using the Bibliometrix package within the R environment. The results highlight an accelerated growth of academic interest after 2016, with a concentration of publications in economics and finance journals such as Energy Economics, Finance Research Letters, and International Review of Financial Analysis, as well as a polycentric structure of international collaborations dominated by East Asia and Europe. The conceptual analysis reveals three major thematic clusters: the performance and impact of green investments, energy transition and sustainable economic growth, and systemic risks and financial stability. The emergence of themes such as financial digitalisation, fintech, and artificial intelligence indicates recent directions of research diversification. The article contributes by providing a systematic mapping of a rapidly maturing field and by identifying epistemic gaps, highlighting the need to expand comparative studies, interdisciplinary approaches, and analyses of green finance in emerging and transition economies.

Ayusha Fayyaz, Zoltan Bartha

The goal of this research is to uncover the channels through which research and development (R&D) impacts economic growth in developing countries. The study employed nine variables from three broader categories in the World Economic Forum database, each covering 32 countries from the lower-middle-income group for the year 2019. The theoretical framework is based on the R&D ecosystem, which includes components such as Institutions, Human capital, Capital market, R&D, and Innovation. Each of these components can contribute to the economic development of the country. Using Structural Equation Modelling (SEM), we build a path diagram to visualize and confirm a potential relationship between the components. R&D features had a positive impact on innovation (regression weight estimate: +0.34, p = 0.001), as did capital market institutions (regression weight estimate: +0.12, p = 0.007), but neither had a significant impact on growth. According to the Schumpeterian institutional interpretation, R&D and innovation efforts may not lead to sustained growth in middle-income countries. We find no significant connection between innovation performance and economic growth. This suggests that while R&D and capital markets may contribute to innovation through entrepreneurship, this contribution is not impactful enough to drive economic growth in developing countries. Our findings provide further evidence of the middle-income trap.

Ali Zeytoon-Nejad

This article expands Milton Friedman's spending matrix to analyse 'spending efficiency' and 'preference compatibility' across different economic systems against five key outcome criteria. By generalising Friedman's typology, it compares efficiency and freedom as systems shift from laissez-faire capitalism to communism, illustrating a gradual deterioration in their key outcomes. While government intervention is sometimes necessary to address market failures, its role should always be carefully limited to avoid inefficiency and misalignment with individual preferences. The insights may provide guidance for policymakers in designing economic systems and policies that promote both economic prosperity and personal liberty.

Mandlenkosi Maphosa, Kablan Antoine Effossou, Philani Moyo

Conservation areas are increasingly seen as crucial for addressing biodiversity loss and climate change, yet their expansion often produces socio-economic tensions with adjacent communities, particularly where governance is exclusionary. This study examines perceptions of equity, resource access, and governance among rural communities and private game reserve officials in the Makana Local Municipality, Eastern Cape, South Africa. It also investigates how climate variability intensifies these challenges by deepening local vulnerability. Guided by vulnerability and participatory governance theory, the study adopted a qualitative, interpretivist approach. Data were collected between July and August 2024 through 58 in-depth interviews with community members, 2 focus group discussions and 5 key informant interviews with conservation managers and community leaders. The study focused on communities surrounding Amakhala and Lalibela Game Reserves, including Alicedale, Seven Fountains, and Kraabos. Findings reveal that while some benefits from conservation exist—such as employment and limited outreach, these are perceived as symbolic, precarious, and inequitably distributed. Communities report restricted access to land, water, and sacred sites, with governance processes experienced as opaque and exclusionary. Climate variability, particularly erratic rainfall and drought, exacerbates these vulnerabilities by undermining agricultural livelihoods and intensifying resource scarcity. The study concludes that socially just and climate-resilient conservation in South Africa requires a shift from rhetorical inclusion to meaningful participation, transparent governance, and equitable benefit-sharing. Aligning conservation with local rights, needs, and adaptive capacities is essential for enhancing both biodiversity protection and community resilience.

Dmitry Yu. Fedotov

The instability of economic processes fuels the inconsistency of the revenue flow to the budget system. In order to overcome the cyclical nature of the budget process, which depends on cyclical fluctuations of economic conditions, fiscal rules are actively applied worldwide. The purpose of the study is to assess the countercyclical effect of the budget rules in force in Russia. The theory of economic cycles constitutes the methodological basis of the research. The paper employs structural, logical and comparative analysis, elaboration, scientific generalisation, and correlation analysis. The evidence is the data obtained from the Federal State Statistics Service of Russia for 2000–2023. The paper examines business cycles in Russia, as well as the cycles of revenues and expenditures of the consolidated budget, the cycles of formation and use of Russian sovereign wealth funds over the indicated period. The correlation analysis found that the revenues of the consolidated budget of Russia are procyclical with the correlation coefficient of the budget revenues and GDP growth rates equal to 0.8029. The procyclical nature of the budget expenditures has decreased due to the fiscal rules applied since 2004 with the correlation coefficient of the budget expenditures and GDP growth rates amounting to 0.5223. However, the procyclical nature of budget expenditures has not been overcome completely. Among them only the procyclical nature of healthcare expenditures has been reduced, while budget expenditures on education and housing and utilities keep on being significantly and to a greater extent dependent on the fluctuations of economic conditions. The paper proposes invoking the principle of fixed expenditures when applying budget rules, which assumes avoiding a decrease in budget expenditures compared to the previous year, calculated at comparable prices.

Наталія Калугіна, Людмила Галан, Олена Івасенко

Статтю присвячено дослідженню впливу цифрових інновацій на розвиток маркетингових стратегій українських компаній, що є важливим аспектом сучасного бізнес-середовища. Актуальність теми зумовлена необхідністю адаптації українських компаній до швидких змін у цифровому середовищі, де інноваційні технології стають важливими інструментами ефективної реалізації маркетингових стратегій. Результати дослідження свідчать, що цифрові технології є вагомим елементом трансформації бізнес-процесів. Наголошено на важливості впровадження персоналізованих рішень для клієнтів, що є одним з основних напрямів у сфері маркетингу. У висновках підсумовано, що сучасні технології, зокрема цифрові інновації, значно змінюють підходи до розроблення та реалізації маркетингових стратегій українських компаній, що дозволяє підвищити їхню ефективність і зміцнити позиції на ринку, сприяючи сталому розвитку та досягненню успіху в цифровому середовищі.

Celia Sifre-Armengol, Jose M. Pavía, Josep Lledó Benito

BACKGROUND: Analysing mortality is relevant for decision-making. Life tables have traditionally been based on age and sex, assuming homogeneous mortality rates within these groups. This omits other factors that could affect mortality risks. Advances in information technology and improved access to official microdata now enable the construction of life tables that incorporate additional variables, offering a more detailed analysis. OBJECTIVE: This paper aims to expand the classical approach of using age and sex by integrating additional risk factors related to the area of residence. Specifically, the factors of climate, habitat size, and income are considered, using detailed georeferenced population data at the census level. Additionally, we aim to estimate future central death rates using various forecasting models. METHODS: Utilising almost 2 billion microdata events from the Spanish population between 2010 and 2019, we begin by estimating new life tables that incorporate climate, habitat size, and income as risk factors. Then, after addressing random variations, erratic peaks, and the unexplained observed decline in mortality at extreme older ages, we use a triad of classical longevity models to project future mortality trends. All the generated data are offered in a public repository. CONTRIBUTION: The database introduced in this paper can be used by social planners, demographers, and insurers, as well as being employed to validate existing findings and explore new research questions, particularly within the demographic and actuarial-economic fields.

Luca Barbaglia, Sergio Consoli, Sebastiano Manzan et al.

We propose an Economic Lexicon (EL) specifically designed for textual applications in economics. We construct the dictionary with two important characteristics: 1) to have a wide coverage of terms used in documents discussing economic concepts, and 2) to provide a human-annotated sentiment score in the range [-1,1]. We illustrate the use of the EL in the context of a simple sentiment measure and consider several applications in economics. The comparison to other lexicons shows that the EL is superior due to its wider coverage of domain relevant terms and its more accurate categorization of the word sentiment.

Zachary Sheldon, Peeyush Kumar

This paper explores the intersection of economic anthropology and generative artificial intelligence (GenAI). It examines how large language models (LLMs) can simulate human decision-making and the inductive biases present in AI research. The study introduces two AI models: C.A.L.L.O.N. (Conventionally Average Late Liberal ONtology) and M.A.U.S.S. (More Accurate Understanding of Society and its Symbols). The former is trained on standard data, while the latter is adapted with anthropological knowledge. The research highlights how anthropological training can enhance LLMs' ability to recognize diverse economic systems and concepts. The findings suggest that integrating economic anthropology with AI can provide a more pluralistic understanding of economics and improve the sustainability of non-market economic systems.

Douglas S. Massey, J. Arango, Graeme Hugo et al.

Max Carter

The unitary representation theory of locally compact contraction groups and their semi-direct products with $\mathbb{Z}$ is studied. We put forward the problem of completely characterising such groups which are type I or CCR and this article provides a stepping stone towards a solution to this problem. In particular, we determine new examples of type I and non-type-I groups in this class, and we completely classify the irreducible unitary representations of the torsion-free groups, which are shown to be type I. When these groups are totally disconnected, they admit a faithful action by automorphisms on an infinite locally-finite regular tree; this work thus provides new examples of automorphism groups of regular trees with interesting representation theory, adding to recent work on this topic.

Oleg V. Pavlov, Jason M. Sardell

This chapter develops a feedback economic model that explains the rise of the Sicilian mafia in the 19th century. Grounded in economic theory, the model incorporates causal relationships between the mafia activities, predation, law enforcement, and the profitability of local businesses. Using computational experiments with the model, we explore how different factors and feedback effects impact the mafia activity levels. The model explains important historical observations such as the emergence of the mafia in wealthier regions and its absence in the poorer districts despite the greater levels of banditry.

Igor V. Nikolaev

We study a relation between the Drinfeld modules and the even dimensional noncommutative tori. A non-abelian class field theory is developed based on this relation. Explicit generators of the Galois extensions are constructed.

Gocha Ugulava

Artificial intelligence methods and technologies are increasingly included in human's everyday life. Managing actors in the context of their activities, from the planning stage to the decision-making stage, are faced with the need to operate with big data, non-linear, exponentially growing, critically overloaded data scenarios. In these conditions, the need to introduce artificial intelligence technologies is due to the exhaustion of the intellectual and analytical capabilities of a person. The article discusses a variety of methods and approaches of artificial intelligence, examines the content of key algorithms, models and theories, their strengths and weaknesses in such important areas of the economy as planning and decision-making. The focus is on their classification. Due to the dependence of the planning process on environmental factors, both classical and non-classical planning environments are discussed. If the environment is fully observable, deterministic and static (external changes are ignored) and discrete in terms of time and action, then we are dealing with a classical planning environment. In the case of a partially observable or stochastic environment, we get a non-classical planning environment. The simplest and most intuitive approach to the planning process algorithms is a Total Order Planning. A scheduling algorithm with parallel execution of actions or without specifying the sequence of their execution is a Partial Order Planning algorithm. Recent research into the development of efficient algorithms has sparked interest in one of the earliest planning approaches – Prepositional Logic Planning. With the Critical Path Method, a schedule of activities is drawn up as part of a plan with zero critical travel time margin for each activity, taking into account the calculation of the time margin for each activity and sequence of activities. A forward-looking planning method for solving complex problems is a hierarchical decomposition based on a Hierarchical Task Networks. The influence of time and resource factors on planning procedures is separately highlighted. Approaches and methods used in a non-classical planning environment: compatible planning, conditional planning, continuous planning, multi-agent planning. Special attention is paid to the issues of constructing planning models in conditions of uncertainty based on the theoretical-probabilistic (stochastic) approaches. Bayesian networks are used to represent vagueness. The Relational Probability Model includes certain constraints on the presentation means, thereby guaranteeing a fully defined probability distributions. The main tasks of probabilistic representation in temporal models are: filtering, forecasting, smoothing, determining a probabilistic explanation. By combining these algorithms and additional enhancements, three large blocks of temporal models can be obtained: Hidden Markov Models, Kalman Filter, and Dynamic Bayesian Network. Decision theory allows the agent to determine the sequence of actions to be performed. A simpler formal system for solving decision-making problems is decision-making networks. The use of expert systems containing information about utility creates additional opportunities. Sequential multiple decision problems in an uncertain environment, such as Markov Decision Processes, are defined using transition models. When several agents interact simultaneously, game theory is used to describe the rational behavior of agents. As we can see, planning has recently become one of the most interesting and relevant directions in the field of artificial intelligence research. There is still a long way to go: it is necessary to develop a clear vision of the problem of choosing the appropriate specific methods depending on the type of task, perhaps by creating completely new methods and approaches.

Olha Vovchanska, Liliya Ivanova

Стаття присвячена аналізу особливостей реалізації інструментів маркетингу в умовах воєнного стану. Маркетингові прийоми під час війни чи військових конфліктів будуть корисні бізнесу у будь-якій галузі економіки. Сформульовано комплекс запитань, на які має знати відповіді компанія, здійснюючи свою маркетингову діяльність в умовах воєнного стану. Визначено основні напрями, в яких доцільно зосереджувати маркетингову діяльність підприємства в умовах воєнного стану. Охарактеризовано основні особливості інструментів маркетингу в умовах воєнного стану. Наведено різнопланові приклади маркетингової діяльності окремих брендів під час воєнного стану як у світі, так і в Україні. Зазначено, що воєнні реалії суттєво змінили купівельну поведінку і купівельні звички споживачів. Висновується, що брендам потрібно намагатися завжди бути в курсі поточної воєнної, економічної, політичної ситуації, щоб бути готовими у разі необхідності змінити бізнес-вектор з власними маркетинговими підходами до своїх цільових і потенційних споживачів.

Alexandru Simion

In order to be successful in an increasingly competitive environment, today every sports organization has to face challenges, which are increasingly difficult to anticipate with accuracy, a fact that causes management to care more and more about performance. The strategic approach to the management of a sports organization has as its starting point the fact that sport has become, in the current era, a complex phenomenon with economic, political and social connotations. We have focused the study on the analysis of financial management strategies and practices used by top sports clubs in Europe, as this is where the highest turnover is obtained in the field of football, highlighting the factors that led to the advantages or disadvantages of applying such strategie.

Kang K. L. Liu, N. Lubbers, W. Klein et al.

The agent-based Yard-Sale model of wealth inequality is generalized to incorporate exponential economic growth and its distribution. The distribution of economic growth is nonuniform and is determined by the wealth of each agent and a parameter $λ$. Our numerical results indicate that the model has a critical point at $λ=1$ between a phase for $λ< 1$ with economic mobility and exponentially growing wealth of all agents and a non-stationary phase for $λ\geq 1$ with wealth condensation and no mobility. We define the energy of the system and show that the system can be considered to be in thermodynamic equilibrium for $λ< 1$. Our estimates of various critical exponents are consistent with a mean-field theory (see following paper). The exponents do not obey the usual scaling laws unless a combination of parameters that we refer to as the Ginzburg parameter is held fixed as the transition is approached. The model illustrates that both poorer and richer agents benefit from economic growth if its distribution does not favor the richer agents too strongly. This work and the accompanying theory paper contribute to understanding whether the methods of equilibrium statistical mechanics can be applied to economic systems.

W. Klein, N. Lubbers, Kang K. L. Liu et al.

We develop a mean-field theory of the growth, exchange and distribution (GED) model introduced by Kang et al. (preceding paper) that accurately describes the phase transition in the limit that the number of agents $N$ approaches infinity. The GED model is a generalization of the Yard-Sale model in which the additional wealth added by economic growth is nonuniformly distributed to the agents according to their wealth in a way determined by the parameter $λ$. The model was shown numerically to have a phase transition at $λ=1$ and be characterized by critical exponents and critical slowing down. Our mean-field treatment of the GED model correctly predicts the existence of the phase transition, critical slowing down, the values of the critical exponents, and introduces an energy whose probability satisfies the Boltzmann distribution for $λ< 1$, implying that the system is in thermodynamic equilibrium in the limit that $N \to \infty$. We show that the values of the critical exponents obtained by varying $λ$ for a fixed value of $N$ do not satisfy the usual scaling laws, but do satisfy scaling if a combination of parameters, which we refer to as the Ginzburg parameter, is much greater than one and is held constant. We discuss possible implications of our results for understanding economic systems and the subtle nature of the mean-field limit in systems with both additive and multiplicative noise.

M. Iannelli, F. Milner