Does agricultural value-added induce environmental degradation? Evidence from Azerbaijan

This study empirically analyzes the long-term relationship between agricultural production and carbon dioxide (CO 2 ) emissions in Azerbaijan using annual data covering the period of 1992–2014. Additionally, real income and energy consumption variables were included in the model in testing the exist...

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Veröffentlicht in:Environmental science and pollution research international 2021-05, Vol.28 (18), p.23099-23112
Hauptverfasser: Gurbuz, Ismail Bulent, Nesirov, Elcin, Ozkan, Gulay
Format: Artikel
Sprache:eng
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Zusammenfassung:This study empirically analyzes the long-term relationship between agricultural production and carbon dioxide (CO 2 ) emissions in Azerbaijan using annual data covering the period of 1992–2014. Additionally, real income and energy consumption variables were included in the model in testing the existence of the environmental Kuznets curve (EKC) hypothesis. Autoregressive distributed lag (ARDL) method is undertaken to reveal the existence of the long-term relationship between the CO 2 and its determinants. The ARDL mechanism shows that gross domestic product (GDP) and energy consumption have a positive and statistically significant effect on carbon dioxide emissions. However, agricultural production and the square of GDP have a negative impact on air pollution. Furthermore, when the coefficients of real GDP and squared GDP included in the model were examined to analyze the inverted-U-shaped relationship between economic growth and environmental pollution, the EKC hypothesis was confirmed to be valid. According to Toda-Yamamoto causality test results, there is a bidirectional relationship between GDP, the square of GDP, and carbon emissions. From energy consumption and agricultural value-added to CO 2 emissions, a unidirectional Granger causality relationship was found. Ultimately, the findings suggest that policies and reforms that increase or support agricultural production will help lower the country’s CO 2 emissions level.
ISSN:0944-1344
1614-7499
DOI:10.1007/s11356-020-12228-3