Transport sustainability governance and green growth in the EU-27: Evidence from panel CS-ARDL and MMQR models

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Type of the article: Research Article

Abstract
The study examines the nexus between environmental tax revenues, renewable energy adoption, transport research and development expenditure, and green growth across EU-27 countries from 2000 to 2024. The study addresses the critical gap in understanding how fiscal environmental instruments and technological innovation in transport sectors contribute to sustainable development outcomes. Using panel data analysis, the paper employs cross-sectionally augmented autoregressive distributed lag (CS-ARDL) and method of moments quantile regression (MMQR) models to analyze both short-run and long-run relationships while accounting for cross-sectional dependence and heterogeneity. Results reveal that environmental tax revenues positively influence green growth with a long-run elasticity of 0.358, indicating that a 1% increase in environmental taxes enhances adjusted net savings by 0.358%. Renewable energy adoption demonstrates a stronger positive effect with an elasticity of 0.531 in the long run, while transport R&D expenditure exhibits a coefficient of 0.289, suggesting significant contributions to sustainable outcomes. The MMQR analysis demonstrates heterogeneous effects across quantiles, with stronger impacts observed at higher green growth levels. Cross-sectional dependency tests confirm significant spatial spillover effects among EU member states. The findings provide empirical evidence supporting the effectiveness of coordinated environmental fiscal policies and targeted innovation investments in transport sectors.

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    • Table 1. Descriptive statistics
    • Table 2. Correlation matrix
    • Table 3. Cross-sectional dependence tests
    • Table 4. Cross-sectionally augmented panel unit root tests (CIPS)
    • Table 5. Westerlund panel cointegration tests
    • Table 6. CS-ARDL estimation results
    • Table 7. Method of moments quantile regression (MMQR) results
    • Conceptualization
      Nuriddin Shanyazov, Dilshodbek Saidov, Javohir Babajanov, Dilshod Karimboev, Doniyor Niyozmetov, Zokir Mamadiyarov, Shaira Djumabayeva
    • Formal Analysis
      Nuriddin Shanyazov
    • Funding acquisition
      Nuriddin Shanyazov, Dilshodbek Saidov, Javohir Babajanov, Dilshod Karimboev, Doniyor Niyozmetov, Zokir Mamadiyarov, Shaira Djumabayeva
    • Methodology
      Nuriddin Shanyazov, Javohir Babajanov, Dilshod Karimboev, Zokir Mamadiyarov
    • Project administration
      Nuriddin Shanyazov, Dilshodbek Saidov
    • Software
      Nuriddin Shanyazov, Zokir Mamadiyarov
    • Supervision
      Nuriddin Shanyazov, Javohir Babajanov
    • Writing – original draft
      Nuriddin Shanyazov, Dilshodbek Saidov, Dilshod Karimboev, Zokir Mamadiyarov
    • Writing – review & editing
      Nuriddin Shanyazov
    • Data curation
      Dilshodbek Saidov, Dilshod Karimboev, Doniyor Niyozmetov
    • Investigation
      Dilshodbek Saidov, Javohir Babajanov, Dilshod Karimboev, Doniyor Niyozmetov, Zokir Mamadiyarov, Shaira Djumabayeva
    • Resources
      Dilshodbek Saidov, Javohir Babajanov, Dilshod Karimboev, Doniyor Niyozmetov, Zokir Mamadiyarov, Shaira Djumabayeva
    • Validation
      Dilshodbek Saidov, Dilshod Karimboev, Doniyor Niyozmetov, Shaira Djumabayeva
    • Visualization
      Javohir Babajanov, Dilshod Karimboev, Doniyor Niyozmetov, Zokir Mamadiyarov, Shaira Djumabayeva