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The Nexus among Civil Aviation, Energy Performance Efficiency and GDP in terms of Ecological Footprint: Evidence from France and Finland

Author

Listed:
  • Erdal Dursun

    (School of Civil Aviation, Nisantasi University, Turkey.)

Abstract

The major goal of this research paper is to determine the long-run linkage among variables and the impact of civil aviation, energy productivity (efficiency), economic growth (GDP), on ecological footprint through conducting the multivariate regression method, Phillips-Ouliaris and Engle-Granger, Jarque Bera Normality, and Cusum tests from 1970 to 2020. According to results of multivariate regression method, civil aviation, energy efficiency, and economic growth affect the ecological footprint from 1970 to 2020 in France which is coincide with Phillips-Ouliaris and Engle-Granger tests. On the contrary, there is no effect of independent variables on dependent variable (ecological footprint) in Finland which is consistent with Phillips-Ouliaris and Engle-Granger tests. In this respect, The long-run relation of the model is verified by the cointegration test of Engle-Granger and Phillips-Ouliaris for France. However, there is no long-run co-integration among variables for Finland from 1970-2020. To sum up, empirical results of France is verified EKC hypothesis. However, EKC hypothesis is not verified for Finland.

Suggested Citation

  • Erdal Dursun, 2022. "The Nexus among Civil Aviation, Energy Performance Efficiency and GDP in terms of Ecological Footprint: Evidence from France and Finland," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 243-251, September.
    • Handle: RePEc:eco:journ2:2022-05-29
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    References listed on IDEAS

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    Cited by:

    1. Emrah Beşe & H. Swint Friday & Salih Kalaycı, 2024. "Examining the Relationship between Inflation Instability and Ecological Footprint: Evidence from Turkey," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 460-467, March.
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    3. Omri, Emna & Saadaoui, Haifa & Bazin, Damien, 2024. "Are renewable energy resources, oil price, and trade openness helping France achieve its environmental targets? Evidence from an asymmetric analysis," The Journal of Economic Asymmetries, Elsevier, vol. 30(C).
    4. Ayşe Özge Artekin & Salih Kalayci, 2024. "Comparative Analysis of Gini Coefficient, GDP, Energy Consumption, and Transportation Modes on CO 2 Using NARDL (Nonlinear Distributed Lag Autoregressive Model) for the USA," Sustainability, MDPI, vol. 16(20), pages 1-21, October.
    5. Sholpan Smagulova & Bakhytgul Chereyeva & Saltanat Zhakupova & Saule Intykbayeva & Bayan Abdulina & Taizhan Sarzhanov & Gulnar Abdulina & Aigerim Abeldanova, 2024. "Assessment of the Impact of Electric Power Production on the Economic Growth of Kazakhstan," International Journal of Energy Economics and Policy, Econjournals, vol. 14(4), pages 391-407, July.

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    Keywords

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    JEL classification:

    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation
    • P18 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Energy; Environment
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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