Identifying the roles of energy and economic factors on environmental degradation in MINT economies: a hesitant fuzzy analytic hierarchy process


Yılancı V., Candan G., Shah M. I.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, cilt.2023, ss.1-14, 2023 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 2023
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1007/s11356-023-26142-x
  • Dergi Adı: ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, EMBASE, Environment Index, Geobase, MEDLINE, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1-14
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet

Özet

Globally, research communities have been studying the different determinants of environmental degradation or pollution using different contexts and methods. In this study, we identify several energy and economic factors, such as energy consumption (EC), gross domestic product (GDP), energy production (EP), urbanization (URB), and foreign direct investment (FDI) as the most effective factors of environmental degradation by obtaining several environmental researchers’ opinions and using the hesitant fuzzy analytic hierarchy process. In the later stage of the analysis, we use these variables as regressors of the ecological footprint (EF) as a proxy for environmental degradation. Since we find evidence of cross-sectional dependence among the members of the variables, we use second-generational panel tests. First, we test the stationarity of the variables using the cross-sectionally augmented IPS (CIPS) panel unit test. The results show that the regressors have different orders of integration. So, we employ the Durbin–Hausman panel cointegration test to test the existence of a long-run relationship between the variables. Having found a long-run relationship, we estimate the long-run coefficients using the common correlated effects mean group estimator, which reveals that energy consumption has an increasing effect on the EF in Indonesia and Turkey, while energy production has a negative impact in Mexico and Turkey. While GDP has an increasing effect in all countries, FDI has a similar effect in only Indonesia. Moreover, URB decreases the ecological footprint in Nigeria, while it increases in Turkey. Our approach to the evaluation of environmental degradation can be generalized to other regions as well as where there is a significant need to understand the roles of different drivers on environmental degradation or pollution.