The Journal of European Economy is a quarterly peer-reviewed scientific periodical published since 2002. JEE is the only specialised economic journal in Ukraine to publish complete full-text issues in Ukrainian, English and Russian (untill 2015) languages. All archives untill 2017 are available at http://jee.tneu.edu.ua The journal aims to publish original manuscripts that analyse issues related to topical theories and concepts of international economics, peculiarities of economic development in transition economies, phenomena of global and European economic integration, as well as the place of the European countries in the world economy. The scope of the Journal covers the following topics: • Economic theory; • Macroeconomics; • Microeconomics; • International economics; • Economy of European countries; • European integration; • Regionalization in European economic area; • International economic relations of European countries; • Financial and banking services market. The Journal of European Economy is indexed by: «Ukrainika Naukova» database, «Dzherelo» abstracts journal, National Vernadskyi Library (Ukraine) Online scientometric database "Index Copernicus (IC)" (Poland) «Journal of Economic Literature» (JEL) American Economic Association (USA) <a href="https://doaj.org/toc/2519-4089?source=%7B%22query%22%3A%7B%22filtered%22%3A%7B%22filter%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22terms%22%3A%7B%22index.issn.exact%22%3A%5B%222519-4070%22%2C%222519-4089%22%5D%7D%7D%5D%7D%7D%2C%22query%22%3A%7B%22match_all%22%3A%7B%7D%7D%7D%7D%2C%22size%22%3A100%2C%22sort%22%3A%5B%7B%22created_date%22%3A%7B%22order%22%3A%22desc%22%7D%7D%5D%2C%22_source%22%3A%7B%7D%7D">Scientometric database "DOAJ" <a href="https://doaj.org/toc/2519-4089?source=%7B%22query%22%3A%7B%22filtered%22%3A%7B%22filter%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22terms%22%3A%7B%22index.issn.exact%22%3A%5B%222519-4070%22%2C%222519-4089%22%5D%7D%7D%5D%7D%7D%2C%22query%22%3A%7B%22match_all%22%3A%7B%7D%7D%7D%7D%2C%22size%22%3A100%2C%22sort%22%3A%5B%7B%22created_date%22%3A%7B%22order%22%3A%22desc%22%7D%7D%5D%2C%22_source%22%3A%7B%7D%7D">(Sweden) « The European Science Foundation » (Norway) «The Digital Object Identifier» Scientometric database “EBSCO” (USA) Academic Resource Index "ResearchBib" Publication of the journal is performed on a non-commercial basis. Manuscripts are subject to independent peer-review by three or more leading experts in the field. Please see “Guidelines for authors” for detailed description of the peer-review process and article submission details. Please see “Publishing Ethics” for detailed description of the duties of editors, reviewers and authors. The contents of each issue is subject to approval by the Scientific Council of West Ukrainian National University. «Journal of European Economy» is registered at the International Centre of Periodicals on November 10, 2016 (ISSN International Centre of. Paris) and received an ISSN 1684-90Ukrainian printed version), ISSN 2519-190X (Ukrainian electronic version), ISSN 2519-4070 (English printed version), ISSN 2519-4089 (English electronic version). Starting from September 2019, for English versions, the JEE received the DOI (The Digital Object Identifier) - a unique hyperlink that provides direct communication with the publication. https://doi.org/10.35774/jee Publishing partners: University of Western Macedonia (Kozani, Greece) Bratislava University of Economics and Management (Bratislava, Slovakia) The Journal is included in the List of Category B Professional Publications of the Ministry of Education and Science of Ukraine, i.e. periodicals recommended for publishing the results of candidate and doctoral dissertations in the field of economics in specialties 051, 072, 073, 075, 076, 292 (order of the Ministry of Education and Science of Ukraine No. 886 of July 02, 2020). The journal is listed in the Supreme Attestation Commission’s register of specialized publications in economic sciences (Resolution №1-05/2 of 10.03.2010 of the SAC of Ukraine). The Journal of European Economy is registered with the State Committee for Information Policy, Television and Broadcasting (Certificate of state registration of the printed mass media КВ №24737-14677ПР of March 16, 2021, issued by the Ministry of Justice of Ukraine). 2015 subscription index in the catalogue of “Ukrposhta” (Ukrainian State Enterprise of Posts): 23527 (Ukrainian version); 23528 (Russian version); 23529 (English version). Mailing address: Editorial office of the «Journal of European Economy», West Ukrainian National University, vul. Lvivska, 11 Ternopil 46020 Ukraine Tel.: +38 (0352) 47-58-75 (editor-in-chief), +38 (0352) 47-50-75 (editorial office). E-mail: Editor-in-chief: yev.savelyev@gmail.com Editorial office: jee.tneu09@gmail.com Publishing House «Economichna Dumka» (vul. Lvivska 11, Ternopil, 46000, Ukraine, tel (0352) 47 58 72).
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FRAUD DETECTION IN BANKING TRANSACTIONS WITH THE USE OF ARTIFICIAL INTELLIGENCE AND ANONYMIZED DATA
This paper examines whether AI machine-learning classifiers trained on anonymized bank transaction data can effectively predict fraudulent transactions. The study tests H1: at least one classifier’s area under the ROC curve (AUC) > 0.50 against H0: the best classifier’s AUC ≤ 0. 50. Using an anonymized dataset from a U.S.-based commercial bank, we assess an extensive set of classifiers, including tree-based ensembles, probabilistic, distance-based, linear and marginbased learners and a neural network using Orange Data Mining Software. The models were evaluated with stratified 10-fold cross-validation. Multiple models achieved AUC > 0.50, with tree-boosting methods providing the strongest balance between detecting fraud and limiting false alarms. Linear baselines and distance based methods were weak, while SVM produced high recall with operationally costly false positives. Overall, results support H1 and are inconsistent with H0. The study offers a transparent, bank-ready benchmark on anonymized, production-plausible features, and the framework is readily replicable for threshold tuning and governance in financial institutions. JEL: G21, C45, C52, C55, M42.
METHODOLOGICAL DEVELOPMENT FOR ASSESSING THE IMPACT OF M2-TO-GDP AND DEBT-TO-GDP RATIOS ON MACROECONOMIC STABILITY: A POLYNOMIAL ANALYSIS APPROACH
This study analyzes Ukraine’s M2/GDP and Debt/GDP ratios from 2000 to 2024 using polynomial smoothing techniques to uncover long-term trends in monetary and fiscal dynamics. The analysis demonstrates how fluctuations in money supply and public debt interact to influence inflation, liquidity, and overall macroeconomic stability. Findings indicate that both excessive and insufficient liquidity exacerbate inflationary pressures, while rising public debt, particularly during crises, constrains the effectiveness of monetary policy. By filtering out short term volatility, polynomial analysis provides a clearer understanding of structural economic patterns and the impact of exogenous shocks such as financial crises, geopolitical tensions, and domestic policy shifts. The results offer valuable insights for policymakers, highlighting the importance of maintaining balanced monetary and fiscal conditions to ensure price stability, adequate liquidity, and sustainable economic growth in transitional and emerging economies. JEL: E51, E52, H63, E62, C22, C32, E41, H68.
CRYPTOCURRENCY USAGE AND ITS RELATIONSHIP WITH TAX EVASION IN THE GREEK ECONOMY
The research aims to find out how cryptocurrency aids tax evasion in Greece, the socio-economic factors contributing to the practice, and the efficiency of the Greek taxation legislation in deterring such conduct. A total of 359 questionnaires were completed by respondents who engage in cryptocurrencies in Greece. Cross correlational statistical analysis and multiple regression analysis were used to test the relationship of cryptocurrency usage, anonymity, tax policies and socio-economic factors and their impact on tax evasion. Also, sociodemographic factors such as income levels and education levels greatly affected the ability to engage in tax evasion. The study provides a validation that the frequency of cryptocurrency usage, anonymity, ineffectual tax laws, socio-economic factors have a positive correlation with tax evasion rates and influence tax dodging in Greece. Based on the issues highlighted in this study, the following steps are advised for the improvement of the Greek anti-money laundering and combating the financing of terrorism regime: i) improve the regulation and enforcement measures concerning cryptocurrencies, ii) enhance the transparency of the cryptocurrency transactions, and iii) address the socio-economic circumstances that enable tax evasion. JEL: F10, G10, G23, H71, K40.
INTEGRATION POTENTIAL OF SMES IN THE EASTERN PARTNERSHIP COUNTRIES WITHIN THE EU GREEN DEAL IMPLEMENTATION
The article examines the integration potential of small and medium-sized enterprises in the Eastern Partnership countries in the context of the European Green Deal. Using a mixed-method approach and drawing on EU4Business data, the study identifies spatial differences in the structure and effectiveness of SME support across three key areas: access to finance, competence development, and the institutional environment. The analysis highlights country-specific patterns in the use of SME development instruments that shape the green transition in Ukraine, Georgia, Moldova, Armenia, and Azerbaijan. Based on these findings, the paper proposes a conceptual model for strengthening SME integration potential, built around five interconnected components: integration readiness and environmental compliance; financial accessibility; competence and innovation development; the institutional integration framework; and monitoring and evaluation. The study shows that this model aligns with the core directions of EU SME support programs. It outlines a systemic approach to enhancing business resilience in the Eastern Partnership region, facilitating gradual convergence with the EU internal market and adaptation to the requirements of the green transition. JEL: F15, Q56, L26, O44.
MILITARY EXPENDITURE IN THE CONTEXT OF LABOR MARKET STRUCTURING
This paper investigates the role of changes in military expenditure as a driver of structural transformations in the labour market, specifically through their impact on the employment-to-population ratio (EPR) in Germany, the Czech Republic, and Ukraine over the period of 1993–2024. Missing EPR data for Ukraine were estimated using a logit-AR(1) model. To analyse nonlinear and asymmetric effects, five machine learning models (MLP, LSTM, 1D CNN, Random Forest, and XGBoost) were developed and compared, incorporating hybrid autocorrelation correction of residuals. The interpretation of the results was conducted using SHAP analysis, and counterfactual «what‑if» scenario simulations with ±σ variations were performed, alongside the identification of sensitivity threshold points. The findings reveal a pronounced asymmetry in the influence of military expenditure on labour‑market structure: in Ukraine, a +1 σ increase in ME_diff raises the EPR by 0.295%, whereas a -1 σ decrease lowers it by only 0.064%. Critical threshold values at ±0.25 σ were identified, beyond which the effects become statistically and economically significant. Estimated multipliers indicate that additional military expenditure is associated with the creation of approximately five jobs per million USD in Germany and the Czech Republic, and more than twenty‑nine jobs per million USD in Ukraine. These values exceed World Bank and IMF estimates for developed economies, reflecting the specific structural conditions and transformational dynamics of Ukraine’s labour market. JEL: E270.
IMPACT OF SHORT-TERM EXTERNAL SHOCKS ON THE WORLD AND EUROPEAN ECONOMIES
This study models the response of the global and European economies to short-term external shocks, including changes in trade and import tariffs, as well as geo-economic and geopolitical factors. The analysis examines the stochastic relationship between external events and variations in key macroeconomic indicators, including global and European GDP, global and European trade volumes, and the Composite Purchasing Managers’ Index (PMI) across major sectors of the world economy. A regression framework incorporating a formalized binary variable is employed to capture the effects of changes in tariff and sanctions policies on economic performance. The empirical results indicate statistically significant effects of external shocks on individual macroeconomic indicators of the global and European economies, as well as on an aggregated index constructed from these indicators. The findings reveal differences in the responses of the examined economies to external shocks, enabling a comparative assessment of their stability and resilience. The results suggest that the European economy demonstrates a higher degree of resistance to external shocks compared to the global economy as a whole and to the Chinese economy. JEL: C32, C51, E32, F44, F62
THE IMPACT OF NON-TARIFF BARRIERS OF THE EU ON THE EXPORT OF KEY AGRARIAN GOODS OF UKRAINE
The article analyses the impact of the European Union’s non-tariff barriers – particularly sanitary and phytosanitary (SPS) measures and technical barriers to trade (TBT) – on the volume and structure of Ukraine’s agricultural exports over the period 2015–2025. The aim of the study is to quantitatively assess the trade costs generated by EU regulatory requirements and to identify patterns in their influence on the commodity composition of exports, taking into account institutional developments such as the implementation of the DCFTA Agreement and temporary trade liberalization measures. The methodological framework of the research is based on gravity modeling using the PPML estimator, complemented by the calculation of ad valorem equivalents that capture the magnitude of non-tariff pressure. Unlike previous studies, this work provides the first detailed quantitative assessment of the impact of SPS notifications on specific groups of Ukrainian agricultural products over a ten-year period, enabling the identification of hidden trade costs generated by regulatory requirements. The analysis reveals differentiated sensitivity across product groups: exports of sugar and sunflower oil are the most vulnerable to increasing SPS burdens, whereas the impact of TBT measures exhibits greater heterogeneity and is partially mitigated by the digitalization of procedures and the harmonization of technical standards. The results offer new insights into the role of non-tariff barriers in shaping Ukraine’s agricultural trade flows and form an analytical basis for enhancing the effectiveness of export support policies, aligning production processes with European standards, and developing digital certification platforms. The proposed approach also makes it possible to forecast future trade costs and optimize strategies for entering the EU market, which is of practical importance for building a resilient and competitive Ukrainian agricultural export sector under conditions of intensifying regulatory pressure. JEL: F13, Q17, C33, F15.
ASSESSING THE UTILITY OF EU STRUCTURAL FUNDS INVESTMENTS IN LATVIA
The purpose of the article is to develop an integrated methodology for assessing the utility of European Union structural funds investments, combining the theory of relative utility, Utilization-Focused Evaluation and the Analytic Hierarchy Process (AHP) method, considering the theory of stakeholders. The tasks of the study include identifying and classifying stakeholders, defining criteria and alternatives, creating a hierarchy of dominance, performing pairwise comparisons and calculating the final utility assessment. The methodology is based on a combined approach: determining the weights of stakeholders, calculating AHP priorities and the Vargas formula for the final synthesis. The data were obtained in an expert survey, where each expert represented a cluster of stakeholders. The results show that in Latvia for the EU structural funds planning period 2021-2027, the priorities «A More Social and Inclusive Europe» and «A Greener Europe» are prioritized, while «Just Transition Fund» and «A Europe Closer to Citizens» are the lowest. The original contribution is the development of an integrated evaluation model that combines AHP with a relative utility approach and stakeholder weighting, providing a balanced and practical tool for cohesion investment decisionmaking. JEL: C44; H54; O22; Q01; R58.
DEVELOPMENT OF A DATA-DRIVEN TRENDWATCHING MODEL IN THE EUROPEAN BUSINESS ENVIRONMENT: THE «AGENTIC AI» CASE
The article is devoted to addressing the issue of strategic business adaptation within the context of the digital transformation of the European economy. Traditional intuitive forecasting methods are losing effectiveness, necessitating a transition to data-driven approaches for the early detection of market opportunities. The aim of the research is the development and methodological substantiation of an authors’ model of integrated trendwatching, which combines web analytics tools with strategic planning methods. The proposed methodology is implemented through a three-tiered algorithm: 1) identification of «weak signals» using an adaptive algorithm for filtering Google Trends data; 2) analytical assessment via a developed business trend matrix that integrates SWOT analysis; 3) strategic modelling of development scenarios (Foresight). The model was tested on the emerging technological trend «Agentic AI». A comparative analysis of search interest dynamics was conducted for the period from December 2024 to November 2025 across key European economies (Great Britain, Germany, France), Eastern European countries (Poland, Ukraine), and the USA as a global benchmark. The research results demonstrate that the proposed model allows for not only recording the appearance of an innovation but also assessing the level of regional market readiness. A significant asymmetry in the perception of the trend between EU countries and the USA was revealed, opening specific «windows of opportunity» for European business. The practical value of the work lies in providing a unified toolkit for transforming «raw» data into verified business strategies. JEL: M15, O31, L86.
DETERMINANTS OF SUBJECTIVE POVERTY IN THE WESTERN BALKANS
This study explores what drives subjective poverty in the Western Balkans, a region where many people still consider themselves poor despite two decades of economic growth and reforms. We provide evidence that the disconnect between measured income poverty and how people feel about their own poverty can undermine poverty reduction efforts and affect social cohesion during the EU accession process. Unlike earlier work that focuses mainly on income poverty, we offer a micro-level, cross-country analysis of subjective poverty in the six Western Balkan post-transition economies. Using data from the 2022–2023 Life in Transition Survey (LiTS IV), which covers 5,196 households in Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, and Serbia, we examine how factors such as economic security, health, remittance income, COVID-19 impacts, and demographic characteristics influence individuals’ placement on a selfrated ten-step wealth ladder. We estimate generalized ordered logit models to re spect the ladder’s ordinal nature and to allow effects to differ across levels of subjective poverty. Our findings indicate that having financial buffers, owning a home, and being in good health significantly reduce the likelihood of feeling poor, whereas experiencing economic setbacks from the pandemic increases subjective poverty. Married individuals report greater subjective poverty, likely reflecting dependency and income-sharing not captured by income-based indicators. Cross-country differences are pronounced: Albania shows the highest levels of subjective poverty, whereas Kosovo the lowest. The evidence suggests that perceived vulnerability rather than income alone is a key driver of poverty assessments, highlighting the need for resilience-focused social policies during EU integration. JEL: I32; O15; P36; C25.