AI Infrastructure and Critical Minerals : Short-Run Silicon Supply Elasticity and Implications for AI-Relevant Mineral Markets

Sammanfattning

This thesis estimates the short-run price elasticity of supply for commodity-grade silicon and examines whether it changed during the expansion of artificial intelligence (AI) infrastructure that began in late 2022. Using monthly global data from January 2015 to February 2026, a production proxy is constructed from international trade statistics and estimated using ordinary least squares with Newey-West standard errors, instrumental variables to address endogeneity, and a structural-break specification. The estimated supply elasticity is positive prior to the break but weakens sharply from early 2024, approximately a year and a half after the AI boom began. The structural break, a continuous interaction term for AI intensity, and a robustness check of the break date all point in the same direction. The results suggest that silicon producers had spare capacity prior to the AI boom but operated near their limits afterwards, implying that price signals alone are unlikely to generate sufficient additional supply in the short run.