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Exploring Economic Growth and Environment Nexus in Nine Southeastern European Countries

Author

Listed:
  • Mitić Petar

    (Institute of Economic Sciences, Belgrade, Republic of Serbia)

  • Cvetanović Slobodan

    (University of Niš, Faculty of Economics, Niš, Republic of Serbia)

Abstract

This paper investigates the interdependence between environmental degradation (CO2 emissions) and economic growth (GDP per capita) in nine SEE countries over the period 1992 – 2016. The results of Granger causality testing indicate that in the short run there is a positive bidirectional causal relationship between CO2 emissions and GDP per capita, but in the long run, there is causality running just from GDP per capita to CO2 emissions, with the 2.0279% speed of adjustment. In pursuit of adequate policy measures, SEE countries need to work on inclusion of non-EU countries into European Union’s Emissions Trading Scheme, further developing carbon taxation policies and using renewable energy sources on a larger scale.

Suggested Citation

  • Mitić Petar & Cvetanović Slobodan, 2018. "Exploring Economic Growth and Environment Nexus in Nine Southeastern European Countries," Economic Themes, Sciendo, vol. 56(2), pages 253-268, June.
  • Handle: RePEc:vrs:ecothe:v:56:y:2018:i:2:p:253-268:n:7
    DOI: 10.2478/ethemes-2018-0015
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    More about this item

    Keywords

    CO2 emissions; GDP per capita; environmental degradation; economic growth; Granger causality testing; panel data;
    All these keywords.

    JEL classification:

    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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