Copper demand forecasts and predictions of future scarcity. (October 2021) - Hunt, C.; Romero, J.; Jara, J.; Lagos, G.
Abstract: Several studies dealt in the past decades with future predictions of the copper demand, motivated mainly by potential copper shortages that could arise due to insufficient reserves. It is known that there was never a shortage of reserves in order to satisfy demand in the last century and up to the present time. This paper addresses two questions. Did these concerns arise due to excessive demand forecasts, or due to stagnating reserves assumption, or due to both aspects? The article evaluates some of these predictions of future copper demand and compares forecasts with the real metal demand that materialized in past years. Also, it analyses the reserve assumptions of several studies and compares them with what really happened with copper reserves. In the case of recent forecast models that span into future years, whose copper demand is not known yet, a backcasting method was used in order to estimate forecasts, which consists of applying the model in the past. Five out of the seven models rerun in the original periods overestimated demand and two out of them considered that reserves were a fixed stock. Also, the two models studied by the backcasting method considered that reserves were a fixed stock. The four models that considered reserves as a fixed stock run out of reserves, irrespective of whether they overestimated or underestimated demand. These results suggest that predictions of a future scarcity of copper could be mainly attributed to the assumption of a fixed stock of reserves and not necessarily to overestimations of demand. The remaining five models did not consider the future availability of copper. Highlights: Nine copper demand forecast models elaborated from 1952 to 2018 were evaluated. Four models that assumed fixed stock of reserves, predicted future copper scarcity. Most of the models that were rerun, overestimated copper demand. A backcasting method was used to forecast demand for recently published models.