Economic complexity and energy uncertainty in the G7: Implications for sustainable development and energy security
- 1Irfan Suat Gunsel Operational Research Institute, Near East University, TRNC, Mersin, 10, Turkey; Research Center of Development Economics, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan; VIZJA University, Warsaw, Poland; Corresponding author. Irfan Suat Gunsel Operational Research Institute, Near East University, TRNC, Mersin, 10, Turkey.
- 2Irfan Suat Gunsel Operational Research Institute, Near East University, TRNC, Mersin, 10, Turkey
- 3Department of Business Administration, Faculty of Economics and Administrative Sciences, Tokat Gaziosmanpasa University, Tokat, Turkey; Arkin University of Creative Arts and Design (ARUCAD Research Centre), Turkey
Abstract
By unpacking the evolution of industrial sophistication in the G7, this study shows how deeper economic complexity can either buffer or amplify energy market uncertainty, with direct implications for sustainable development. Specifically, it pioneers an empirical assessment of the economic complexity–energy uncertainty nexus in the G7 using quarterly data from 1996 to 2021, drawing policy lessons that support resilient energy systems, low-carbon transition pathways, and progress toward SDG 7 and SDG 13. To achieve this objective, we employ a set of quantile-based methodologies. First, we apply the quantile KPSS (QKPSS) and quantile Zivot–Andrews (QZA) tests to examine the stationarity properties of the variables. Second, we use the Quantile Granger Causality (QGC) approach to provide insights into distribution-dependent predictive relationships across quantiles. The QKPSS and QZA results indicate that all variables become stationary after first differencing across all quantiles. Moreover, the QPSS bounds and QGC findings confirm that economic complexity and energy uncertainty are cointegrated, and that economic complexity exerts a causal influence on energy uncertainty. Moreover, the findings of the quantile-on-quantile regression demonstrate that economic complexity reduces energy uncertainty in the G7 nations, except for the United Kingdom and the United States, where the results indicate a positive effect of economic complexity on energy uncertainty in the middle and upper quantiles. Based on these findings, we propose specific policy recommendations.
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BibTeX
@article{adebayo2026economic,
title = {{Economic complexity and energy uncertainty in the G7: Implications for sustainable development and energy security}},
author = {Tomiwa Sunday Adebayo and Berna Uzun and Oktay Özkan},
journal = {Innovation and Green Development},
year = {2026},
month = oct,
doi = {10.1016/j.igd.2026.100402},
url = {https://doi.org/10.1016/j.igd.2026.100402},
note = {CC BY},
}
RIS
TY - JOUR
TI - Economic complexity and energy uncertainty in the G7: Implications for sustainable development and energy security
AU - Tomiwa Sunday Adebayo
AU - Berna Uzun
AU - Oktay Özkan
PY - 2026
DA - 2026/10/23
JO - Innovation and Green Development
DO - 10.1016/j.igd.2026.100402
UR - https://doi.org/10.1016/j.igd.2026.100402
AB - By unpacking the evolution of industrial sophistication in the G7, this study shows how deeper economic complexity can either buffer or amplify energy market uncertainty, with direct implications for sustainable development. Specifically, it pioneers an empirical assessment of the economic complexity–energy uncertainty nexus in the G7 using quarterly data from 1996 to 2021, drawing policy lessons that support resilient energy systems, low-carbon transition pathways, and progress toward SDG 7 and SDG 13. To achieve this objective, we employ a set of quantile-based methodologies. First, we apply the quantile KPSS (QKPSS) and quantile Zivot–Andrews (QZA) tests to examine the stationarity properties of the variables. Second, we use the Quantile Granger Causality (QGC) approach to provide insights into distribution-dependent predictive relationships across quantiles. The QKPSS and QZA results indicate that all variables become stationary after first differencing across all quantiles. Moreover, the QPSS bounds and QGC findings confirm that economic complexity and energy uncertainty are cointegrated, and that economic complexity exerts a causal influence on energy uncertainty. Moreover, the findings of the quantile-on-quantile regression demonstrate that economic complexity reduces energy uncertainty in the G7 nations, except for the United Kingdom and the United States, where the results indicate a positive effect of economic complexity on energy uncertainty in the middle and upper quantiles. Based on these findings, we propose specific policy recommendations.
SN - 2949-7531
ER -