Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Material productivity (MP) is a sustainability indicator that measures usage efficiency for raw materials. The use of natural resources has grown steeply since the Industrial Revolution and this growth has even accelerated in recent decades. It has thus become critical to monitor the intensity of natural resource usage when producing intermediate or final goods. Discovering which socio-economic variables influence the MP indicator and explain differences between economic units is, nowadays, a key issue. On average, MP has increased over the past two decades but, at the same time, so has disparity between countries. This paper's contribution consists in discovering the explanatory variables for both these phenomena. In order to achieve that aim, a regression-based inequality decomposition (RBID) methodology is used. The original Fields' RBID model has been transformed into a logarithmic model, which allows us to directly obtain the elasticity of MP to changes in its drivers. The sample we use is broadly representative of the worldwide situation in the years 1990–2010. Our main results are that, in terms of explaining inequalities and changes in MP, the Agricultural share of GDP is the most relevant explanatory variable and that this is followed by Affluence. The explanatory powers of Population Density and Trade Openness are, perhaps surprisingly, of much lower importance. The results are useful, not only in academic terms, but also for policy guidance.