Please use this identifier to cite or link to this item: http://rps.chtei-knteu.cv.ua:8585/jspui/handle/123456789/4221
Title: Impact of Cryptocurrency Markets on Eastern European Economies: A Structural Equation Modeling Analysis
Authors: Вдовічен, Данило Анатолійович / Vdovichen, Danylo
Королюк, Юрій Григорович / Koroliuk, Yurii
Keywords: cryptocurrency
blockchain
Eastern Europe
structural equation modeling
economic indicators
Issue Date: Mar-2026
Publisher: Journal of Applied Computer Science & Mathematics
Citation: Vdovichen, D., & Koroliuk, Y. (2026). Impact of Cryptocurrency Markets on Eastern European Economies: A Structural Equation Modeling Analysis. Journal of Applied Computer Science & Mathematics, 20(40), 3-9. https://doi.org/10.4316/JACSM.202601001
Abstract: The rapid expansion of cryptocurrency markets presents both opportunities and challenges for Eastern European economies, particularly amid post-Soviet transitions and geopolitical instability. Key problems investigated include market volatility, regulatory fragmentation, informal economy overlaps, environmental costs of mining, and the vulnerability exposed by the October 2025 crypto crash, which triggered $19 billion in liquidations due to U.S.-China trade tensions. The aim of this research is to empirically evaluate the influence of cryptocurrency adoption on macroeconomic performance in the region, focusing on fostering financial inclusion and trade efficiency while mitigating risks. Research objectives encompass assessing direct and mediated effects of crypto penetration on GDP growth, inflation stability, and unemployment reduction; testing hypotheses on transaction volumes, user adoption, and Virtual Asset Service Providers (VASPs) as drivers of economic outcomes; and deriving policy insights for sustainable integration. The methodology employs Structural Equation Modeling (SEM) on a balanced panel dataset from 11 Eastern European countries (Poland, Czechia, Slovakia, Hungary, Romania, Bulgaria, Croatia, Lithuania, Latvia, Estonia, Ukraine) over 2020–2024 (N=55). Variables include Crypto_Users (%), Crypto_Transactions (billion USD), ln_VASPs, GDP (billion EUR), Inflation (%), and Unemployment (%). Data sourced from Chainalysis (2024) and Eurostat (2024) were analyzed using robust maximum-likelihood estimation with 5,000 bootstraps, incorporating country fixed effects. Model fit indices (χ² p=.168, RMSEA=.052, CFI=.968) confirm robustness. Results indicate significant positive paths from transaction volumes (β=.59, p<.001) and VASPs (β=.48, p<.001) to GDP, with partial mediation (indirect β=.16, p=.008); user adoption hedges inflation (β=.29, p=.008) but shows no unemployment impact. Conclusions underscore crypto's GDP-boosting potential (e.g., 2% uplift in Romania) amid risks, advocating harmonized regulations to balance innovation and stability in Eastern Europe.
Description: https://www.jacsm.ro/view/?pid=40_1
URI: http://rps.chtei-knteu.cv.ua:8585/jspui/handle/123456789/4221
ISSN: 2066-4273
Appears in Collections:06.35.51 Економіко-математичні методи та моделі

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