Can ESG Uncertainty Alter the Emissions Impact of Renewable Energy Consumption? Statistical Evidence from a Novel Wavelet Quantile Moderation–Mediation Regression


SUNDAY ADEBAYO T.

Statistical Journal of the IAOS, 2026 (ESCI, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2026
  • Doi Number: 10.1177/18747655261445375
  • Journal Name: Statistical Journal of the IAOS
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, EconLit, INSPEC
  • Keywords: CO2emissions, ESG uncertainty, moderating and mediating, renewable energy consumption, sustainable development goal, wavelet analysis
  • Azerbaijan State University of Economics (UNEC) Affiliated: Yes

Abstract

ESG uncertainty has emerged as a critical friction for the United States energy transition, yet little is known about how it shapes the emissions consequences of renewable energy consumption across different emissions states and time horizons. This study provides new evidence on the moderating and mediating role of ESG uncertainty in the renewable energy consumption and CO2 emissions relationship using monthly U.S. data from 01/11/2002 to 01/06/2025. In doing so, the study extends the wavelet quantile regression framework to incorporate both moderation through an interaction term and mediation through quantile-specific indirect effects across short-, medium-, and long-horizon components. The results show that (a) the effect of TREC on TCO2 is positive and significant in the short run, negative in the medium run, and positive again in the long run; (b) ESGUI's moderating effect is mostly weak in the short run, becomes selectively negative in the medium run, and turns positive and stronger at mid-to-upper quantiles in the long run; (c) for mediation, path a suggests that TREC generally reduces ESGUI across several regimes, particularly over longer horizons, with some tail reversals; and (d) for path b, ESGUI affects TCO2 mainly at the long-run upper tail. However, the overall indirect (mediated) effect is statistically insignificant. The study proposes precise policies based on these results.