Understanding US Cobalt Market Vulnerability Through Structural Price and Material Flow Analysis
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garg-kgarg21-sm-tpp-meche-2026-thesis.pdf
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Author(s)
Garg, Khyati
Advisor(s)
Knittel, Christopher
Gutowski, Timothy
Date Issued
February 2026
Publisher
Massachusetts Institute of Technology
Abstract
Cobalt is a critical input to batteries, superalloys, and industrial materials central to the energy transition, yet its supply chain is characterized by pronounced geographic concentration, complex trade pathways, and limited transparency. This study combines a detailed material flow analysis (MFA) of cobalt in the United States with a structural vector autoregression (SVAR) framework to examine how physical supply constraints and demand growth jointly shape cobalt price dynamics. The MFA reconstructs U.S. cobalt flows across mining, refining, manufacturing, end use, and waste management, explicitly accounting for majority of the cobalt consumed in the US embodied in imported batteries, vehicles, and other finished products. Results show that U.S. cobalt demand is substantially underestimated by conventional apparent consumption metrics and that a large share of cobalt entering the U.S. economy accumulates in long-lived in-use stocks rather than being immediately available for recycling. The econometric analysis indicates that demand shocks associated with battery deployment generate persistent price increases, while supply responses remain constrained due to cobalt’s byproduct nature, global production concentration, and exogenous shocks. Together, these findings suggest that policies focused solely on domestic mining are unlikely to materially reduce near-term cobalt exposure. Instead, battery chemistry choices, mineral reserves, refining capacity, and improved accounting of embodied critical minerals emerge as more effective levers for managing supply risk in the United States.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
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