System Dynamics of Carbon Price Volatility and Clean Technology Investment: A Causal Loop Analysis with Global Market Validation

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🔬研究者:Offers a validated causal loop model and empirical elasticities linking carbon price volatility to investment, useful for further research on climate finance and carbon market design.

🏢実務担当者:Provides evidence that managing carbon price volatility is more critical than price levels for clean tech investment decisions, guiding corporate risk management and investment planning.

🏛政策担当者:Demonstrates that integrated policy packages (price collars, technology support, risk-sharing) can significantly enhance investment and reduce volatility, informing carbon pricing reform and fiscal planning.

The global transition to net-zero emissions by 2050 necessitates unprecedented capital mobilization into clean technologies, yet persistent carbon price volatility continues to undermine investment certainty across global markets. This research presents a comprehensive system dynamics framework that quantifies the complex feedback mechanisms governing the relationship between carbon pricing volatility and clean technology investment decisions. Through analysis of empirical data from 80 operational carbon pricing instruments covering 28% of global greenhouse gas emissions (verified as of November 2025), we develop and validate a causal loop model revealing the intrinsic dynamics driving this critical economic relationship. Our framework identifies eight interconnected feedback loops four reinforcing mechanisms that drive positive outcomes and four balancing loops that constrain progress. A central finding is that volatility management generates greater investment stimulus than equivalent price increases, under 2025 baseline market conditions (EU ETS price ~$85/tCO2, annualised volatility σ = 0.42), each 10% reduction in carbon price volatility produces investment effects comparable to approximately a $15/tCO2 price rise. This equivalence is derived from the empirically calibrated difference between volatility elasticity (β2 = −0.68) and price elasticity (βı = 0.42) and should be understood as an order-of-magnitude policy heuristic not a universal exchange rate whose regional expression ranges from roughly $10−11/tCO2 in advanced economies to $22−24/tCO2 in the Middle East and Africa (see Section 5.2 for full qualification). Implementation of integrated policy packages combining dynamic price collars, technology-differentiated support, and risk-sharing mechanisms can increase clean technology deployment by 72% while reducing price volatility by 58%, requiring fiscal commitments of approximately 0.5% of GDP annually. Clean energy investment reached $2.1 trillion in 2024, representing 47% of the $4.5 trillion annual requirement for net-zero pathways by 2030. Empirical validation across 147 countries using 18,000 renewable energy projects confirms learning rates of 24% for solar photovoltaics, 17% for onshore wind, and 5−9% for carbon capture and storage. Regional heterogeneity analysis reveals investment elasticities ranging from −0.45 in advanced economies to −0.85 in emerging markets.

• semanticscholar https://doi.org/10.2118/232581-msfirst seen 2026-05-24 04:43:20 · last seen 2026-05-27 04:58:08