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Raw materials costs form an increasingly significant proportion of the total costs of renewable energy technologies that must be adopted at unprecedented rates to combat climate change. As the affordable deployment of these technologies grows vulnerable to materials price changes, effective strategies must be identified to mitigate the risk of higher input costs faced by manufacturers. To better understand potential threats to...
A hierarchical Bayesian regression model that reduces uncertainty in material demand predictionsNARA Subscribed
Predictions of metal consumption are vital for criticality assessments and sustainability analyses. Although demand for a material varies strongly by region and end‐use sector, statistical models of demand typically predict demand using regression analyses at an aggregated global level (“fully pooled models”). “Un‐pooled” regression models that predict demand at a disaggregated country or regional level face challenges due to...
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