APPLYING ARTIFICIAL NEURAL NETWORKS TO ANALYZE THE IMPACT OF ICT-SECTOR ON THE ECONOMIC GROWTH IN UKRAINE
DOI:
https://doi.org/10.32782/ecovis/2025-2-1Keywords:
ICT-sector, economic growth, artificial neural networks, economic modelingAbstract
The article analyzes the impact of the ICT sector on the economic dynamics of Ukraine, with particular attention to nonlinear interactions that cannot be fully captured by traditional econometric models. The research is guided by the hypothesis that the influence of ICT is complex and multifaceted, being transmitted through resource, financial, and monetary channels. The dataset combines World Bank World Development Indicators and statistics from the State Statistics Service of Ukraine for 2000–2023. At the first stage, OLS regression with Newey–West robust errors was applied. The results showed that ICT’s direct share in GVA was not statistically significant, but its lagged value (ICT % GVA lag1) emerged as a stable and meaningful predictor of GDP growth. At the second stage, a neural network model was implemented to account for nonlinearities and hidden interactions. The model demonstrated high predictive accuracy (MAE ≈ 5 percentage points, RMSE ≈ 5.8, MASE < 1) and revealed that ICT, gross capital formation, and military expenditure are the top three factors shaping Ukraine’s economic dynamics. The findings highlight that ICT exerts a significant nonlinear effect on macroeconomic development, often interacting with other variables through indirect channels. The confirmed hypothesis emphasizes the strategic role of the ICT sector in economic stabilization and long-term growth, underscoring the importance of policies that enhance its expansion and integration into the broader economy.
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