Geopolitical risks and energy transition: the impact of environmental regulation and green innovation

The study investigates whether and how geopolitical risk (GPR) influences energy transition (ET) in OECD countries, and whether environmental regulation (EPS) and green innovation (GI) strengthen this relationship. ET is framed as the shift from fossil fuels toward renewable and clean energy to achieve carbon neutrality. Prior work highlights key roles of environmental regulations and green innovation in improving energy efficiency, stimulating technological change, and supporting renewable deployment. Heightened geopolitical tensions (e.g., Russia–Ukraine conflict) can disrupt energy supply chains, increase price volatility, and reshape policy and investment decisions, potentially accelerating diversification into renewables. The paper posits that, particularly in developed OECD economies with stronger regulatory institutions and innovation capacity, GPR may catalyze ET, and that EPS and GI are likely to moderate and amplify GPR’s effect. The study contributes by focusing on OECD countries, explicitly modeling moderating and threshold effects of EPS and GI, and providing empirical evidence on the direct and nonlinear links from GPR to ET.

The review covers three strands: (1) Energy transition and geopolitical risk: Global geopolitical risks arising from conflicts and instability affect renewable energy markets and the feasibility of ET. Evidence is mixed—some studies find GPR hinders renewables/ET by reducing project attractiveness, while others find it can spur ET via energy security concerns, competition for critical materials, and trade dynamics, implying a dual role of geopolitics (hindering and facilitating). (2) Energy transition and environmental regulation: Stringent environmental policies (carbon pricing, cap-and-trade, standards) are widely shown to improve energy efficiency, reduce emissions, stimulate innovation, and guide markets toward cleaner energy, thereby advancing ET. (3) Energy transition and green innovation: Green technologies and innovation enhance renewable energy deployment, energy efficiency, and reduce energy intensity, with multiple studies documenting positive effects on ET and sustainability across various regions (e.g., BRICS, G7, APAC). Research gaps identified include a lack of OECD-focused analyses integrating GPR, ET, EPS, and GI into one framework and limited understanding of nonlinear/threshold dynamics. The study addresses these by modeling moderation and threshold effects of EPS and GI on the GPR–ET nexus.

Data: Balanced panel of 20 OECD countries from 1991–2020 (600 observations). Key variables: ET (renewable energy consumption as % of total final energy consumption, WDI), GPR (Caldara and Iacoviello index; monthly series averaged to annual; robustness with geometric mean), EPS (Environmental Policy Stringency Index, OECD), GI (environment-related technologies as % of all technologies, OECD). Controls: inflation (GDP deflator, WDI), total natural resource rents (% GDP, WDI), economic globalization (trade % GDP, WDI), official exchange rate (LCU per US$, WDI). All variables are log-transformed. Preliminary analyses: Descriptive statistics, Pearson correlations, VIF (all < 2), panel cointegration tests (Pedroni and Westerlund show cointegration). Models: (1) Linear log–log fixed-effects style multiple regression: lnET = a + β1 lnGPR + β2 lnIFLA + β3 lnNRR + β4 lnEG + β5 lnEXR + ε. (2) Moderation models with interaction terms: lnET = a + b1 lnGPR + b2 lnEPS + b3 (lnGPR×lnEPS) + controls; and lnET = a + c1 lnGPR + c2 lnGI + c3 (lnGPR×lnGI) + controls. Centered variables used to address collinearity. (3) Nonlinear threshold (panel threshold regression) models using EPS and GI as threshold variables (single vs. double threshold tested via bootstrap grid search; 350 bootstrap replications). Threshold estimation validated via LR plots and confidence intervals. Robustness checks: (a) One-period lag of ET (and interactions) to assess dynamics; (b) Replace GPR annualization method (geometric mean) and re-estimate linear, moderation, and threshold models; (c) Endogeneity addressed via instrumental variables using lagged lnGPR (Anderson LM and Cragg–Donald tests reported).

- Cointegration and specification checks: Panel cointegration is confirmed (Pedroni and Westerlund significant), and multicollinearity is low (VIF < 2). Correlations show ET positively related to GI, EPS, NRR, EG; GPR’s correlation with ET is negative, but regression results reverse once controls are included. - Linear main effect (Table 7): Geopolitical risk promotes energy transition. A 1% increase in GPR is associated with a 0.117% increase in ET (lnGPR coef. 0.117, p<0.1). Controls: inflation and exchange rate negatively associated; economic globalization positively associated with ET. - Moderation by environmental regulation (Table 8): Interaction lnGPR×lnEPS is positive and significant (p<0.01). Results robust to centering. Interpretation: Stronger EPS amplifies the positive effect of GPR on ET. - Moderation by green innovation (Table 9): Interaction lnGPR×lnGI is positive and significant (p<0.01). Results robust to centering. Interpretation: Higher GI strengthens GPR’s positive effect on ET. - Threshold effects (Tables 10–12; Fig. 2): Single-threshold models are supported for EPS and GI. • EPS threshold (lnEPS = 0.9042; 95% CI [0.8775, 0.9400]): - Below threshold: coef. 0.016 (GPR→ET) - Above threshold: coef. 0.185 (GPR→ET) • GI threshold (lnGI = 2.3437; 95% CI [2.3104, 2.3504]): - Below threshold: coef. 0.054 (GPR→ET) - Above threshold: coef. 0.196 (GPR→ET) Interpretation: As EPS or GI passes the threshold, the positive impact of GPR on ET becomes markedly stronger. - Robustness: • Lagged models (Tables 11–15): With ET lagged one period, GPR’s effect rises to 0.146 (p<0.01). Thresholds remain and effects strengthen when above-threshold: EPS threshold lnEPS=1.0116 with coefficients 0.065 (≤thr) vs 0.227 (>thr); GI threshold lnGI=2.3292 with coefficients 0.091 (≤thr) vs 0.228 (>thr). Moderation effects of EPS and GI remain positive and significant. • Alternative GPR aggregation (geometric mean): Linear coef. increases to 0.149 (p<0.01). Moderation remains positive and significant (EPS interaction ≈0.1715; GI interaction ≈0.1949). Threshold effects persist: EPS 0.035 (≤0.9042) vs 0.209 (>0.9042); GI 0.077 (≤2.3437) vs 0.222 (>2.3437). • Endogeneity (Table 19): IV results using lagged lnGPR confirm a significantly positive causal effect of GPR on ET; instrument validity and strength tests passed (Anderson LM significant; Cragg–Donald F > 16.38). Overall: Geopolitical risk consistently and positively affects energy transition in OECD countries; this effect is amplified by stricter environmental regulation and higher green innovation, with clear single-threshold nonlinearities and stronger lagged impacts.

The findings directly address the research question by showing that geopolitical risk can act as a catalyst for energy transition in OECD economies. Mechanistically, geopolitical shocks heighten energy security concerns and price volatility, encouraging diversification away from vulnerable fossil imports and toward domestically deployable renewables. Environmental regulation provides incentives and standards (e.g., carbon pricing, efficiency norms) that convert these pressures into concrete investment shifts, while green innovation lowers costs and improves performance of clean technologies, enabling faster adoption. The nonlinear threshold evidence indicates that only after EPS and GI surpass certain levels do countries fully leverage geopolitical shocks to accelerate ET. This underscores the policy relevance of complementary institutional and technological readiness: stronger EPS and GI transform geopolitical disruptions from threats into opportunities to advance ET. Robustness across lags, alternative GPR measures, and IV estimation supports the causal interpretation and general reliability of the results.

The study shows that in OECD countries, higher geopolitical risk is associated with increased renewable energy transition, and this positive relationship is significantly strengthened by stringent environmental regulations and strong green innovation capacity. Single-threshold nonlinearities are identified for both EPS and GI, with markedly larger GPR→ET effects above the thresholds. Robustness checks using lag structures, alternative GPR aggregation, and instrumental-variable estimation corroborate these conclusions. Contributions include: (1) OECD-focused evidence that GPR can promote ET; (2) demonstration of moderating and threshold roles of EPS and GI; (3) comprehensive robustness validation. Policy implications emphasize building resilient ET strategies that pair regulatory stringency with innovation support to harness geopolitical shocks for accelerating decarbonization. Future research could extend to non-OECD regions, incorporate broader institutional dimensions (e.g., governance quality), explore technology-specific transitions, and assess distributional and justice implications of fast-tracked ET under geopolitical stress.