УДК 330.34.01

DOI: https://doi.org/10.36887/2415-8453-2025-2-9

Kolyada Yurii,
Doctor of Economic Sciences, Associate Professor, Professor, Department of Mathematical Modeling and Statistics,
Institute of Information Technologies in Economics,
Kyiv National Economic University named after Vadym Hetman
https://orcid.org/0000-0003-2516-9817
Poznyak Sergii,
PhD Student, Department of Mathematical Modeling and Statistics, Institute of Information Technologies in Economics,
Kyiv National Economic University named after Vadym Hetman
https://orcid.org/0009-0006-4894-7983

JEL classification: C31, O11, O15, O16, O17, O41

The article discusses the author’s multivariate models of economic growth with a particular focus on improving their generalisability and applicability to diverse economic contexts. The central aim of the study is to enhance the adaptability of economic growth models by systematically incorporating factors often overlooked or insufficiently addressed in mainstream economic literature. These include population dynamics, market structures, and the influence of informal economic sectors such as the shadow and grey economies. A significant innovation introduced in the model is replacing a constant or static population growth rate with a dynamic demographic component based on the Verhulst logistic growth model. This approach enables a more accurate reflection of real-world demographic shifts and their nonlinear impact on economic output. The article also delves into the implications of various market structures—perfect competition, monopoly, monopolistic competition, and oligopoly—for economic development. Each structure is modelled within the framework to capture its unique effects on resource allocation and capital accumulation. Furthermore, the study highlights the often-underestimated influence of the informal economy. The grey economy is modelled through corrections to savings behavior, while the shadow economy is introduced via a distinct capital intensity equation derived from an independent production function. By integrating these elements, the proposed multivariate models attain greater realism, flexibility, and predictive accuracy, thus offering a more robust analytical tool for researchers engaged in long-term economic planning and development forecasting. The study’s relevance is determined by the growing complexity of global economic systems and the need for more adaptable analytical instruments capable of capturing multifactorial influences on growth. Traditional models often fail to reflect real-world dynamics, especially in economies undergoing structural transformations. Incorporating demographic, market, and informal sector variables responds to contemporary challenges and ensures higher analytical precision in diverse economic environments.

Keywords: economic growth, models of economic growth, demography, types of market structure, shadow economy.

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The article was received 04.03.2025