Sensitivity Analysis of Factors Influencing Coal Prices in China

A scientific assessment of the sensitivity of the Chinese coal market has become an important research topic. This paper combines Gaussian Process Regression (GPR) and Sobol sensitivity analysis to construct a GPR–Sobol hybrid model innovatively applied to the Chinese coal market, thus addressing a gap in the economic applications of this method. The model is used to analyze the sensitivity of factors influencing coal prices in China. The GPR–Sobol model effectively handles nonlinear relationships, enabling an in-depth exploration of key factors affecting price volatility and quantifying their impacts, thus overcoming the limitations of traditional econometric models in nonlinear data processing. The results indicate that economic growth, energy prices, interest rates, exchange rates, and uncertainty factors exhibit high sensitivity and significantly impact coal price fluctuations in China. Coal prices in northwest China are more sensitive to interest rates and geopolitical risks, while prices in east and south China are more responsive to exchange rates but less so to economic policy uncertainty. Additionally, coal prices in north, south, and east China are highly sensitive to international energy prices, indicating that coal prices are dominated by the global energy market, yet their weak response to macroeconomic indicators suggests these regions is still insufficiently mature.