Decoding Environmental Sustainability in Nordic Economies: The Interplay of AI Innovation, Banking Development, and Stock Markets
Abstract
This study examines the influence of Artificial Intelligence (AI) innovation on Ecological Footprint (EF) in the Nordic region, while accounting for the roles of Banking Development (BD), Stock Market Capitalization (SMC), economic growth, and urbanization over the period 1995–2021. Grounded in the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) framework, the analysis employs a panel econometric approach that incorporates cross sectional dependence and slope heterogeneity. Both first- and second-generation unit root tests confirm a mixed order of integration, justifying the application of the Panel Autoregressive Distributed Lag Model (Panel ARDL) to explore short run and long run dynamics. The empirical findings reveal that economic growth, SMC, and urbanization exert upward pressure on EF, indicating that expansion in economic and financial activities intensifies environmental stress in the region. In contrast, AI innovation and BD contribute to reducing ecological pressure, suggesting that technological advancement and financial intermediation can support environmentally sustainable outcomes. The error correction mechanism confirms a stable long run equilibrium relationship among the variables. Furthermore, causality analysis indicates directional linkages running from key explanatory variables to EF. The results highlight the critical importance of integrating digital innovation and sustainable finance strategies to achieve long term environmental sustainability in advanced economies.
Keywords:
Artificial intelligence, Ecological footprint, Banking development, Stock market capitalization, Nordic economiesReferences
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