Финансовое сотрудничество является важнейшим направлением в углублении делового сотрудничества стран БРИКС. В данной статье проанализированы публикации ученых из Китая, России и других стран, посвященные БРИКС с момента его создания, а также рассмотрены вопросы, которые интересуют ученых. Было обнаружено, что в 2014–2015 гг. и после 2022 г. количество исследований резко возросло, что, несомненно, связано с финансовыми санкциями, введенными США и европейскими странами против России. Ученые более позитивно оценивают перспективы финансового сотрудничества стран БРИКС и считают, что в условиях санкций и контрсанкций значение углубления сотрудничества становится еще очевиднее. В статье представлены результаты анализа литературы и данных о финансовом сотрудничестве стран БРИКС за последние пятнадцать лет с основным фокусом на вопросах финансового взаимодействия, выдвинутых на первый план Россией как председательствующей страной. Считается, что инициатива «Мост БРИКС» соответствует общим требованиям стран-членов по созданию финансовой инфраструктуры, независимой от США и стран Европы, и является новой попыткой и прорывом в реформировании международной экономической и финансовой системы, однако ее реализация сталкивается со многими внутренними и внешними вызовами. Авторы исследования пришли к выводу, что финансовое сотрудничество всегда было важным направлением делового сотрудничества стран БРИКС, но с расширением БРИКС достичь консенсуса между странами и реализовать его становится все труднее. В 2025 г., в период председательства Бразилии, финансовое сотрудничество по-прежнему остается одной из главных тем, однако переизбрание Трампа и использование им инструментов таможенной политики привели к новой нестабильности в международной экономической ситуации, а угроза о «дедолларизации» стран БРИКС также усложнит финансовое сотрудничество.
Татьяна Сергеевна Новикова, Ольга Игоревна Гулакова
Развитие российско-китайской торговли открывает возможности перехода к новому этапу научно-технологического развития за счет активизации государственной политики в условиях обострения геополитических проблем и усиления фрагментации мировой экономики. Целью статьи является разработка адекватного инструментария индикативного планирования для обоснования внешнеторговой политики России, базирующейся на приоритетном сотрудничестве с Китаем и другими дружественными странами, в условиях многополярного мира. Анализ фактической взаимной внешней торговли России и Китая за период 2013–2023 гг. выявил стремительный рост ее объемов при практически неизменной структуре, характеризующейся архетипом сырьевой направленности российского экспорта и высокой долей импорта из Китая продукции машиностроения. Введена классификация трех архетипов торговых отношений и рассмотрена возможность расширения товарообмена продукцией высоких переделов и высокотехнологичными товарами, базирующаяся на созданном потенциале научно-технологического взаимодействия двух стран. Новый импульс развитию внешней торговли России и Китая можно придать за счет реализации конкурентоспособных проектов региональной научно-исследовательской инфраструктуры, выступающих драйверами перехода к архетипу товарообмена высокотехнологичной продукцией. Для получения количественных оценок разработаны три взаимосвязанных модели: финансово-экономическая модель проекта создания НИИ, оптимизационная межотраслевая межрегиональная модель, расширенная за счет включения технологического способа проекта, и модель внешней торговли России и Китая. Разработанный подход был адаптирован на примере проекта «Академгородок 2.0» на период 2013–2030 гг. Для оценки влияния на торговлю различных политик и технологических изменений в статье рассмотрены базовый, предельный и инерционный сценарии. Экспериментальные расчеты показали, что прогнозируемая к 2030 г. структура внешнеторгового обмена России и Китая характеризуется существенным ростом доли машиностроения и химии в российском экспорте, что соответствует долгосрочным изменениям взаимного внешнеторгового обмена стран с высоким научно-технологическим потенциалом.
The article addresses the issue of spatial differentiation in the socio-economic development of Thailand’s provinces in the context of the national «Thailand 4.0» strategy. The research problem arises from the limited empirical evaluation of regional heterogeneity that integrates demographic, sectoral, and institutional dimensions. The objective is to identify structural patterns of provincial development and to propose a typology that may serve as a basis for differentiated regional policy. The study relies on provincial-level indicators for 2010 2021, including per capita gross regional product, labor migration, industrial investment, land use, and inbound tourism. The Williamson coefficient was applied to quantify inequality, revealing its growth over the past decade. Clustering was performed using k-means, hierarchical agglomerative methods, and DBSCAN in Python with scikit-learn. The k-means algorithm with three and four clusters produced the most robust results, isolating Bangkok as a distinct cluster. Three persistent groupings were identified: industrial centers in the central region, agricultural provinces of the northern and northeastern areas, and tourism-driven provinces in the south. The analysis also revealed β-convergence processes in several transitional provinces, suggesting gradual alignment of development trajectories. Policy recommendations emphasize modernization of agriculture, innovation support for industrial centers, and infrastructure projects in tourism-intensive provinces. The findings confirm the persistence of spatial polarization and highlight the utility of cluster analysis as a tool for refining Thailand’s regional development strategy.
Economic complexity - a group of dimensionality-reduction methods that apply network science to trade data - represented a paradigm shift in development economics towards materializing the once-intangible concept of capabilities as inferrable and quantifiable. Measures such as the Economic Complexity Index (ECI) and the Product Space have proven their worth as robust estimators of an economy's subsequent growth; less obvious, however, is how they have come to be so. Despite ECI drawing its micro-foundations from a combinatorial model of capabilities, where a set of homogeneous capabilities combine to form products and the economies which can produce them, such a model is consistent with neither the fact that distinct product classes draw on distinct capabilities, nor the interrelations between different products in the Product Space which so much of economic complexity is based upon. In this paper, we extend the combinatorial model of economic complexity through two innovations: an underlying network which governs the relatedness between capabilities, and a production function which trades the original binary specialization function for a fine-grained, product-level output function. Using country-product trade data across 216 countries, 5000 products and two decades, we show that this model is able to accurately replicate both the characteristic topology of the Product Space and the complexity distribution of countries' export baskets. In particular, the model bridges the gap between the ECI and capabilities by transforming measures of economic complexity into direct measures of the capabilities held by an economy - a transformation shown to both improve the informativeness of the Economic Complexity Index in predicting economic growth and enable an interpretation of economic complexity as a proxy for productive structure in the form of capability substitutability.
Paul X. McCarthy, Xian Gong, Marieth Coetzer
et al.
This study explores the relationship between personality diversity and national economic performance, introducing the Global Personality Diversity Index ($Ψ$-GPDI) as a novel metric. Leveraging a dataset of 760,242 individuals across 135 countries, we quantify within-country diversity based on the Big Five personality traits. Our findings reveal that personality diversity accounts for 19.9% of the variance in GDP per capita and provides an additional 2.8% explanatory power beyond institutional quality and immigration, underscoring its unique contribution to economic vitality. Through multi-factor analysis, we demonstrate how personality diversity complements existing economic frameworks, offering actionable insights for policymakers seeking to enhance innovation, productivity, and resilience. This research positions psychological diversity as a critical yet under explored factor in driving economic growth, bridging the fields of psychology and economics.
This article proposes predictive economics as a distinct analytical perspective within economics, grounded in machine learning and centred on predictive accuracy rather than causal identification. Drawing on the instrumentalist tradition (Friedman), the explanation-prediction divide (Shmueli), and the contrast between modelling cultures (Breiman), we formalise prediction as a valid epistemological and methodological objective. Reviewing recent applications across economic subfields, we show how predictive models contribute to empirical analysis, particularly in complex or data-rich contexts. This perspective complements existing approaches and supports a more pluralistic methodology - one that values out-of-sample performance alongside interpretability and theoretical structure.
The main goal of this article is to introduce an economic perspective in the social logic of space. Firstly, we describe the economic model of a linear city to show how depth can generate value by creating local monopolies in less integrated spaces. Then, a new syntactic measure, the d-value, is proposed to capture the relation between the depth of some space from outside and the mean depth of all spaces from outside. An application to a public housing estate suggests that economic activities and services may be located in spaces with a d-value close to one. The article is complemented by a Prolog programme with a special predicate to compute the d-value.
Rahman Aulia Fuad, Agusti Rosalita Rachma, Kurniawati Desi Tri
The mounting environmental concerns have become a pressing issue across industries. Nevertheless, the banking sector has a distinct influence in shaping economic growth and development. This study sought to evaluate the impact of green banking in strengthening corporate value through its level of sustainability reporting in order to address these concerns. A research framework was developed based on theoretical support. The sampled data was collected from banks listed on the Indonesian Stock Exchange from 2018-2021. An empirical analysis was performed through hierarchical regression. The study’s findings indicated that green banking positively and significantly impacts firm value. Furthermore, there is a mediating effect between green banking and business value due to the quality of sustainability reporting. The empirical test revealed that the quality of sustainability reporting has a mediating effect to some extent. The results also showed that there is an interaction between business size (assets) and correlations between firm value and green banking. By undertaking a data-driven research that explains the impact of green banking on business value, this study aims to fill a significant gap in the body of knowledge on green banking and sustainability reporting.
Regional economics. Space in economics, Economics as a science
The term of big data was used since 1990s, but it became very popular around 2012. A recent definition of this term says that big data are information assets characterized by high volume, velocity, variety and veracity that need special analytical methods and software technologies to extract value form them. While big data was used at the beginning mostly in information technology field, now it can be found in every area of activity: in governmental decision-making processes, manufacturing, education, healthcare, economics, engineering, natural sciences, sociology. The rise of Internet, mobile phones, social media networks, different types of sensors or satellites provide enormous quantities of data that can have profound effects on economic research. The data revolution that we are facing transformed the way we measure the human behavior and economic activities. Unemployment, consumer price index, population mobility, financial transactions are only few examples of economic phenomena that can be analyzed using big data sources. In this paper we will start with a taxonomy of big data sources and show how these new data sources can be used in empirical analyses and to build economic indicators very fast and with reduced costs.
Clement E. Bohr, Marti Mestieri, Frederic Robert-Nicoud
As countries develop, the relative importance of agriculture declines and economic activity becomes spatially concentrated. We develop a model integrating structural change and regional disparities to jointly capture these phenomena. A key modeling innovation ensuring analytical tractability is the introduction of non-homothetic Cobb-Douglas preferences, which are characterized by constant unitary elasticity of substitution and non-constant income elasticity. As labor productivity increases over time, economic well-being rises, leading to a declining expenditure share on agricultural goods. Labor reallocates away from agriculture, and industry concentrates spatially, further increasing aggregate productivity: structural change and regional disparities are two mutually reinforcing outcomes and propagators of the growth process.
Este artigo analisa os fatores que influenciam a implementação da Política de Atenção à Saúde e Segurança do Trabalho do Servidor Público Federal – PASS no Instituto Federal de Educação da Bahia – IFBA. Os conceitos de Políticas Públicas, e sua fase de implementação foram usados. É um trabalho com abordagem quantitativa, usando regressão múltipla a uma amostra de 346 questionários respondidos, obtidos entre os meses de agosto e setembro de 2018. Os resultados apontam que a PASS não está efetivamente implementada, evidenciada pela falta de conhecimento dos servidores sobre ela e baixa participação deles nas ações desenvolvidas. Indicam também que os fatores variáveis contextuais, cultura organizacional, organização do aparato administrativo e recursos disponíveis são os que se relacionam com a eficácia no processo de implementação da política estudada.
Nadezhda Yashina, Oksana Kashina, Sergey Yashin
et al.
The need to take into account imbalances among regional indicators in the development of state policy for financing national projects makes it necessary to develop a methodology that will enable objective assessment of the effectiveness of socially significant projects in Russia. This paper reports the development of a methodology for financial monitoring of national project implementations in the constituent entities of the Russian Federation, taking into account the correlation of their target indicators and using cluster analysis and methods in mathematical statistics. The proposed methodology was tested on health and demography national project data obtained from the Federal Treasury of Russia, the Federal State Statistics Service and the Accounts Chamber for 2020–2021. The analysis of public funding for national projects based on centralization indices and target indicators for their implementation enabled classifying the regions of Russia according to the levels of effectiveness and the financial risks of implementing the projects. The results of the study correspond to the actual effectiveness of national projects and can be used in the development of flexible state policy in financing national projects, taking into account the level of the target indicators achieved.
There has been a shift from a few pioneering institutions to a far larger number of conventional universities in a wider range of countries engaged in designing online education. In light of the fact that online education is a phenomenon that occurs on a global scale, it is necessary for us to investigate the manner in which these practices were carried out by adopting an international and systematic point of view. This study uses complex network analytics to map out the worldwide landscape of massive open online courses (MOOCs) from a disciplinary and regional viewpoint, drawing reference from the product space and comparative advantage theories from the field of development economics. The study found that the course space of global MOOCs presents diversity and cooperation. Ultimately, the courses provided by universities and colleges are consistent with the proximity principle and are fairly comparable to the University's comparative advantage disciplines. There is a positive correlation between a region's level of economic development and the rate at which MOOCs are being offered. Strong advantages persist for North America and Western Europe. Differences in the level of development of MOOCs between nations are most pronounced in computer science and other cutting-edge disciplines. When it comes to the overall strategy for implementing MOOCs, different nations are moving at varying rates of speed. It has been found that the way subjects are spread out and how close they are to each other in the course space can make it harder to upgrade the MOOC curriculum.
This paper optimizes path planning for a trunk-and-branch topology network in an irregular 2-dimensional manifold embedded in 3-dimensional Euclidean space with application to submarine cable network planning. We go beyond our earlier focus on the weighted costs of cables (cable laying cost, resilience, design level and repair rate) to include the cost of branching units (BUs), including material and labor, as well as submarine cable landing stations (CLSs). This optimization also includes choices of locations of BUs and CLSs. These are important issues for the economics of cable laying and significantly change the model and the optimization process. We pose the problem as a variant of the Steiner tree problem, but one in which the Steiner nodes can vary in number, while incurring a penalty. We refer to it as the weighted Steiner node problem. It differs from the Euclidean Steiner tree problem, where Steiner points are forced to have degree three; this is no longer the case, in general, when nodes incur a cost. We are able to prove that our algorithm is applicable to Steiner nodes with degree greater than three, enabling optimization of network costs in this context. The optimal solution is achieved in polynomial-time using dynamic programming.
This article describes methods used in the field of spatial economics that combine insights from economic theory and evidence from data in order to answer counterfactual questions. I outline a general framework that emphasizes three elements: a specific question to be answered, a set of empirical relationships that can be identified from exogeneity assumptions, and a theoretical model that is used to extrapolate from such empirical relationships to the answer that is required. I then illustrate the application of these elements via a series of twelve examples drawn from the fields of international, regional, and urban economics. These applications are chosen to illustrate the various techniques that researchers use to minimize the theoretical assumptions that are needed to traverse the distance between identified empirical patterns and the questions that need to be answered.