No 1 (2026)
- Year: 2026
- Published: 31.03.2026
- Articles: 4
- URL: https://vektornaukieconomika.ru/jour/issue/view/67
Full Issue
Empirical verification of Esping-Andersen’s typology of welfare state financial models on a global sample of countries
Abstract
Problem. The relevance of the study is caused by the need for empirical verification of G. Esping-Andersen’s classical typology of welfare state systems in the context of the global transformation of public financial regulation models. Aim. The aim of this work is to test the stability of the three ideal types (social-democratic, conservative-corporatist, liberal) based on outcome indicators of poverty and income inequality, as well as the standard of living, using a global sample of countries. Methods. The methodological framework consisted of principal component analysis (PCA) and k-means clustering (optimal number of clusters k=9, silhouette coefficient 0.405) based on World Bank data for 2019– 2024 (142 countries), followed by verification using instrumental characteristics of tax and transfer mechanisms. Results. It was established that the classical Esping-Andersen models do not form separate clusters based on outcome indicators but are united into a single cluster, demonstrating outcome convergence (poverty rate 0.6–1.3 %, income Gini coefficient 0.280–0.317). At the same time, instrumental divergence persists, manifested in differences in tax progressivity, the structure of social insurance contributions, and the volume of social transfers. Russia is classified within the subgroup of post-socialist hybrid models with a limited redistributive function and the potential for increasing the progressivity of personal income taxation. A structural division was identified between countries with institutionalised social protection systems and states where informal solidarity mechanisms dominate (clusters 6–9). Conclusions. The conclusion is drawn about the necessity of a two-level typology of welfare state financial models: (1) institutional for upper-middle and highincome countries and (2) oriented towards informal social protection models for low-income economies with underdeveloped welfare systems.
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Development of the global petroleum products market: opportunities and constraints
Abstract
The current stage of development of the global petroleum products market is characterised by a unique confluence of global challenges that compel to re-evaluate its prospects. It is viewed not simply in the context of increasing production and consumption of crude oil and its refined products, but rather as a fundamental transformation of the entire system of market relations in this segment of the global economy. The key idea of the paper is to conduct a comparative analysis of existing forecasts and scenarios for the development of the global oil market, characterised by a state of structural break caused by the confrontation between two multidirectional trends – the spread of the “green agenda” aimed at reducing the use of mineral resources, and the increase in demand for petroleum products from developing countries. The authors identified a contradiction between the inertia of oil demand and the pressure of the energy transition, which causes a structural transformation of the economies of most states. It is shown that the “green agenda” acts not as an external threat, but as an internal factor determining investment decisions and the future map of global commodity flows of petroleum products. It replaces linear forecasts with the analysis of bifurcation points and strategic flexibility. The paper analyses the historical dynamics and current state of key parameters of the global petroleum products market, identifies drivers of uncertainty, and constructs models for the future development of this segment. It is concluded that the high uncertainty of the current dynamics of the global petroleum products market conditions is determined not so much by environmental factors as by geopolitical and economic factors.
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Success factors of crowdfunding projects: a predictive model based on binary logistic regression
Abstract
Problem. The absence of reliable tools for predicting the success of crowdfunding projects at the early stages of campaigns limits the ability of platforms to select promising initiatives and reduces investment efficiency. Existing research is fragmentary and does not account for the specifics of different project categories or the characteristics of the Russian market. Aim. The aim of this work is to construct a predictive model based on binary logistic regression that allows assessing the probability of a project’s success on a crowdfunding platform. Methods The study investigated the influence of the following factors on the success of crowdfunding projects: target amount and fundraising duration, number of sponsors and average contribution size, presence of a video file in the description, number of news updates and comments, author’s experience, use of social networks; number of project subscriptions; number of days required to raise 25 % of the target amount; and the number of “quick” investments. Additionally, the analysis was conducted considering the project category. The study employed binary logistic regression as a predictive analysis method. Results. The study showed that for predicting the success of most projects, a single factor (the presence of more than one “quick” investment) is sufficient, and the accuracy of such prediction is very high. For example, for projects in the “Creative Products” category, the success prediction accuracy was 99.42 %, and the failure prediction accuracy was 98.98 %. Conclusions. The binary logistic regression model built on data from the Russian platform Planeta.ru allows for high-accuracy prediction of crowdfunding project success. Key predictors are raising 25 % of the target amount within the first week and the presence of “quick” investments. For categories with low success rates (“Business”, “Innovations”), accuracy increases when combining factors. The results can be used by platforms for scoring and project support.
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Assessment of the transformational potential of Russia's creative sector: between a driver and a conglomerate
Abstract
Problem. Despite the recognition of the creative sector as a driver of structural transformation in developed economies, there is no comprehensive quantitative assessment of the degree of its integration into global trends as applied to Russia. Existing studies are fragmentary, rely on outdated data, and do not account for the post-crisis transformation of 2022–2024, which hinders the development of sound economic policy. Aim. Based on a comparative analysis of quantitative indicators and institutional conditions, to identify the specific influence of the creative sector on the structural transformation processes of the Russian economy in the context of global trends and to determine the key barriers to realising its transformational potential. Methods. The study is based on a comprehensive methodology, including a comparative analysis of macroeconomic indicators of Russia, the United States, and China for 2021–2024 and a qualitative analysis of institutional factors. For a quantitative integral assessment, the authors developed the Global Trend Alignment Index (GTAI), which includes four components: digitalisation, exports, polycentrism, and institutions. Results. A fundamental gap was revealed between Russia and the leading countries: the share of the creative sector in Russia’s GDP reached 4.1 % (compared to 4.5–4.6 % in the US and China); however, this growth was driven primarily by the IT cluster. Exports of creative services decreased by more than fourfold, and employment in the sector is also insignificant – 1.55 % of the labour force (in the US – 3.23 %). Spatial hyperconcentration in the Central Federal District reached 68 % of gross value added. The GTAI for Russia was 0.28, corresponding to a low level of alignment with global trends. Conclusions. In its current state, the Russian creative sector represents not a unified agent of transformation, but a conglomerate of heterogeneous assets with conjunctural rather than structural growth. The identified imbalances require not an increase in funding, but a deep structural restructuring aimed at overcoming the gaps between technologies and content, the capital and the regions, and government procurement and market expansion.
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