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Wird die deutsche Energiewende und damit ein Teil der ökologischen Nachhaltigkeit Deutschlands auf Kosten der Bevölkerung in den Rohstoffabbauländern ausgetragen? Zur Quantifizierung der schwierigen sozialen Arbeitsbedingungen beim Rohstoffabbau erstellt diese Studie ein Bewertungsmodell, mithilfe dessen ressourcenintensive Projekte anhand ihrer sozialen Bedingungen beim Rohstoffabbau klassifiziert und bewertet werden können. Die Anwendung des Modells auf die Ressourcenbedarfe von acht potentiellen Entwicklungspfaden des deutschen Energiesystems verdeutlicht, dass die vermehrte Verwendung von Rohstoffen wie Kobalt, Gallium, Dysprosium und Neodym, benötigt für Technologien wie Batteriespeicher, Solar- und Windkraftanlagen, den sozialen Fußabdruck der Energiewende negativ beeinflusst.

In this study, we develop a framework, based on the Global Vector Autoregression Model (GVAR), to unite two differing perspectives on commodity markets, the single-market centered approach, investigating the micro- and macroeconomic drivers of commodity prices, as well as the inter-market perspective, which observes joint movements of commodity prices, beyond macroeconomic variables, on exchanges. The strong co-movement between industrial metal prices is represented exceptionally well by our framework, which connects the markets using co-consumption, co-production and co-trading data. While the microeconomic supply and demand attributes have no significant impact on individual market level, indicating a contradiction to the single-market centered approach, the cross-commodity dimension reveals these attributes are determining, even on price variables.

In our study, we individually forecast 26 metal prices one-month ahead and outperform the predefined benchmark model, a random-walk (with drift) in 18 (18) cases. These forecasts are based on an overview over a large set of potential predictors for mineral commodities, originating from studies which only consider a selection of attributes and apply them to predict specific commodities or commodity indices. We pre-select the relevant, commodity-specific, individual factors through a correlation analysis, followed by a BIC based regression selection. The results of our out-of-sample, one-month ahead forecasts show a significant outperformance for 18 of the 26 commodities considered, especially those in the minor metals sector. The differences in predictability between the metal groups are remarkable, as we are able to forecast 13 of 17 minor metals, 5 of 6 industrial metals, but no precious metal, highlighting the heterogeneity in metal commodity markets. Focusing on the influential factors, the value factor has a dominating, highly significant, negative effect in the prediction and determination of prices.