The Roles of Renewable Energy and Natural Resources in Shaping a Greener Switzerland: A Consumption-Side Perspective


Anser M. K., Radulescu M., Khan Z., Nassani A. A.

Geological Journal, vol.60, no.11, pp.2652-2668, 2025 (SCI-Expanded, Scopus) identifier

  • Nəşrin Növü: Article / Article
  • Cild: 60 Say: 11
  • Nəşr tarixi: 2025
  • Doi nömrəsi: 10.1002/gj.5148
  • jurnalın adı: Geological Journal
  • Jurnalın baxıldığı indekslər: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Geobase, INSPEC
  • Səhifə sayı: pp.2652-2668
  • Açar sözlər: consumption perspective, environment, renewable energy, resource rent, Switzerland
  • Açıq Arxiv Kolleksiyası: Məqalə
  • Adres: Yox

Qısa məlumat

This research intends to examine how renewable energy (REN) consumption and natural resource (RES) rents affect the environmental impact of consumption in Switzerland. Along with REN and RES, the study considers Information and Communication Technology (ICT) and participatory democracy as other independent variables of interest. The study measures the environmental impact of consumption by considering consumption-based CO2 emissions. The study covers the period from 1990 to 2021. For econometric analysis, the study employs a dynamic version of the autoregressive distributed lag (ARDL) model along with other pre- and post-diagnostic tests. The study findings confirm that there are negative and significant effects of REN use on the environmental impact of consumption during the long run and short run period, which is further confirmed by causality results from frequency domain causality analysis. However, RES rents do not significantly affect the environment given the scarcity of RES in this country. The short-run analysis from the dynamic ARDL model confirms the negative impact of ICT and participatory democracy on the environmental impact of consumption, but long-run coefficients remain insignificant. However, the frequency domain result only confirms the causality from democracy to environmental impacts. The study findings are further validated by a machine learning algorithm. Finally, several policy implications are suggested to reduce the environmental impact of consumption in this economy.