Dynamic relationship among agriculture-renewable energy-forestry and carbon dioxide (CO2) emissions: empirical evidence from GUAM countries
DOI:
https://doi.org/10.6092/issn.2281-4485/19087Keywords:
GUAM, agriculture, renewable energy, forest, sustainable, panel unit root test, pedroni and kao panel cointegration test, OLS, FMOLS, DOLSAbstract
Nowadays with the climate change the environmental degradation has became the crucial issue in the World. This study empirically investigates the impact of agriculture value-added, forest area, and renewable energy on CO2 emissions in GUAM union countries from 1996 to 2019. The independent variables in this study are agriculture value-added, forest, renewable energy and the dependent variable is CO2 emissions. The statistical methods as the Panel unit root test, Pedroni and Kao panel co-integration test and OLS, FMOLS, and DOLS long-run tests were employed for the empirical part of the paper. The independent variables in this study are agriculture value-added, forest, renewable energy and the dependent variable is CO2 emissions. The statistical methods as the Panel unit root test, Pedroni and Kao panel co-integration test and OLS, FMOLS, and DOLS long-run tests were employed for the empirical part of the paper. The outputs of the Pedroni and Kao panel co-integration tests confirmed that there is a long-term relationship between the analyzed series. The findings of the OLS, FMOLS, and DOLS tests indicate a negative relationship between the analyzed variables. According to the the results of empirical analyzes it was confirmed that there is a statistically significant and negative relationship between agriculture value-added, forest, renewable energy and CO2 emissions which means that an increase of agricultural production, forest areas and renewable energy consumption decreased the CO2 emissions in GUAM countries for the time span 1996-2019.
References
ANWAR M.A., NASREEN S., TİWARİ A. K. (2021) Forestation, renewable energy and environmental quality: Empirical evidence from Belt and Road Initiative economies. Journal of Environmental Management, 291, 112684. https://doi.org/10.1016/j.jenvman.2021.112684
AYDOŠAN B., VARDAR, G. (2020) Evaluating the role of renewable energy, economic growth and agricultu-re on CO2 emission in E7 countries. International Jour-nal of Sustainable Energy, 39(4):335– 348. https://doi.org/10.1080/14786451.2019.1686380
BALTAGİ B.H., KAO C. (2001) Nonstationary panels, cointegration in panels and dynamic panels: A survey. In Nonstationary panels, panel cointegration, and dynamic panels. Emerald Group Publishing Limited. ISBN: 978
BEN JEBLİ M., BEN YOUSSEF S. (2017) Renewable energy consumption and agriculture: Evidence for cointegration and Granger causality for Tunisian economy. International Journal of Sustainable Development & World Ecology, 24(2):149–158. https://doi.org/10.1080/13504509.2016.1196467
CHANDİO A.A., AKRAM W., AHMAD F., AHMAD M. (2020) Dynamic relationship among agriculture-energy-forestry and carbon dioxide (CO2) emissions: Empirical evidence from China. Environmental Science and Pollution Research, 27(27):34078–34089. https://doi. org/10.1007/s11356-020-09560-z
EYUBOGLU K., UZAR U. (2020) Examining the roles of renewable energy consumption and agriculture on CO2 emission in lucky-seven countries. Environmental Science and Pollution Research, 27(36):45031–45040. https://doi.org/10.1007/s11356-020-10374-2
GRANGER C., NEWBOLD P. (1974) Spurious regressions in econometrics. Journal of Econometrics, 2(2): 111–120. https://econpapers.repec.org/article/eco
nom/v_3a2_3ay_3a1974_3ai_3a2_3ap_3a111-120.htm
GRANGER C.W.J. (1969) Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3):424–438. https://doi. org/ 10.2307/ 1912791
GURBUZ I.B., NESİROV E., OZKAN G. (2021) Does agricultural value-added induce environmental degradation? Evidence from Azerbaijan. Environmental Science and Pollution Research, 28(18):23099–23112. https://doi.org/10.1007/s11356-020-12228-3
HARİPRİYA G.S. (2002) Biomass carbon of truncated diameter classes in Indian forests. Forest Ecology and Management, 168(1): 1–13. https://doi.org/10.1016/S03 78-1127(01)00729-0
IM K.S., PESARAN M., SHİN Y. (2003) Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1):53–74. https://econpapers.repec.org/article/econ
om/v3a115_3ay_3a2003_3ai_3a1_3ap_3a53-74.htm
IPCC - Intergovernmental Panel on Climat Change (2014). Working Group Ⅲ contribution to the IPCC Fifth Assessment Report. https://www.ipcc.ch/ report/ar5/wg3/
IPCC - Intergovernmental Panel on Climat Change (2021) Climate Change https://www.ipcc.ch/report/ar6/ wg1/downloadsreport/IPCC_AR6_WGI_SPM_final.pdf
KAO C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econome-trics, 90(1):1–44. https://doi.org/10.1016/S0304-4076
(98)00023-2
KARİMOV M. (2019) The Impact of Foreign Direct Investment on Trade (Export and Import) in Turkey. European Journal of Interdisciplinary Studies, 5(1):6–17. https://doi.org/10.26417/ejis.v5i1.p6-17
KARİMOV M. (2020) An empirical analysis of the relationship among foreign direct investment, gross domestic product, CO2 emissions, renewable energy contribution in the context of the environmental Kuznets curve and pollution haven hypothesis regarding Turkey. European Journal of Formal Sciences and Engineering, 3(2):23-42. https://doi.org/10.26417/ejis.v5i1.p6-17
KATARZYNA C.F., AGNİESZKA K. (2017) The Orga-nization for Democracy and Economic Development—GUAM. Springer professional. De. https://www.springer professional.de/en/the-organization-for-democracy-and-economic-development-guam/11240600
KHAN M.T.I., ALİ Q., ASHFAQ M. (2018) The nexus between greenhouse gas emission, electricity production, renewable energy and agriculture in Pakistan. Renewable Energy, 118:437–451. https://doi.org/10.1016/j.renene. 2017.11.043
LEVİN A., LİN C.F., JAMES CHU C.S. (2002) Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1):1–24. https://econpapers.repec.org/article/eeeeconom/v_3a108_3ay_3a2002_3ai_3a1_3ap_3a1-24.htm
LİU X., ZHANG S., BAE J. (2017a) The impact of renewable energy and agriculture on carbon dioxide emissions: Investigating the environmental Kuznets curve in four selected ASEAN countries. Journal of Cleaner Production, 164:1239–1247. https://doi.org/10.1016/j. jclepro.2017.07.086
LİU X., ZHANG S., BAE J. (2017b) The nexus of renewable energy-agriculture-environment in BRICS. Applied Energy, 204:489–496. https://doi.org/10.1016/ j.apenergy.2017.07.077
MADDALA G.S., WU S. (1999) A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test. Oxford Bulletin of Economics and Statistics, 61(S1):631–652. https://doi.org/10.1111/1468-0084.0610s1631
MARK N.C., SUL D. (2003) Cointegration vector estima-tion by panel DOLS and long-run money demand. Oxford Bulletin of Economics and Statistics, 65(5):655–680. https://doi.org/10.1111/j.1468-0084.2003.00066.x
OKUMUŞ İ. (2020). Türkiye’de Yenilenebilir Enerji Tü-ketimi, Tarım ve CO2 Emisyonu İlişkisi. Uluslararası Eko no-mi ve Yenilik Dergisi, 21–34. https://doi.org/10.209 79/ueyd.659092
PARAJULİ R., JOSHİ O., MARASENİ, T. (2019) Incorporating forests, agriculture, and energy consumption in the framework of the Environmental Kuznets Curve: A dynamic panel data approach. Sustainability, 11(9):2688. https://doi.org/10.3390/su11092688
PEDRONİ P. (1999) Crıtıcal values for coıntegratıon tests ın heterogeneous panels wıth multıple regressors.18. https://doi.org/10.1111/1468-0084.0610s1653
PEDRONİ P. (2000) Fully modified OLS for hetero-geneous cointegrated panels. In Advances in Econome-trics, 15:93–130. https://doi.org/10.1016/S0731-9053 (00)15004-2
PEDRONİ P. (2001) Purchasing Power Parity Tests In Cointegrated Panels. The Review of Economics and Statistics, 83(4):727–731. https://econpapers.repec.org/
article/tprrestat/v_3a83_3ay_3a2001_3ai_3a4_3ap_3a727-731.htm
PEDRONİ P. (2004) Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis (Department of Economics Working Paper No. 2004–15). Department of Economics, Williams College. https://econpapers.re
pec.org/paper/wilwileco/2004-15.htm
PHILLIPS P.C., HANSEN B.E. (1990) Statistical infe-rence in instrumental variables regression with processes. The Review of Economic Studies, 57(1):99–125. https://doi.org/10.2307/2297545
QİAO H., ZHENG F., JİANG H., DONG K. (2019) The greenhouse effect of the agriculture-economic growth-renewable energy nexus: Evidence from G20 countries. Science of The Total Environment, 671:722–731. https://doi.org/10.1016/j.scitotenv.2019.03.336
STOCK J.H., WATSON M. W. (1993) A simple esti-mator of cointegrating vectors in higher order integrated systems. Econometrica: Journal of the Econometric Society, 783–820. https://doi.org/10.2307/2951763
WAHEED R., CHANG D., SARWAR S., CHEN W. (2018). Forest, agriculture, renewable energy, and CO2 emission. Journal of Cleaner Production, 172:4231–4238. https://doi.org/10.1016/j.jclepro.2017.10.287
YASMEEN R., PADDA I.U.H., YAO X., SHAH W.U.H., HAFEEZ M. (2022) Agriculture, forestry, and environmental sustainability: The role of institutions. Environment, Development and Sustainability, 24(6): 8722–8746. https://doi.org/10.1007/s10668-021-01806-
YUFANG P., WEİDONG C., PENGBANG W. (2019) Examining the comprehensive effects of renewable ener-gy, forest, and agriculture on CO2 emissions: Evidences from China and India. Fresenius Environmental Bulletin, 28(11A):8708–8720. https://www.cabdirect.org/cabdirect/abstract/20219911295
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