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Statistical Projection of Material Intensity: Evidence from the Global Economy and 107 Countries
Author(s) -
Efthimiou George C.,
Kalimeris Panos,
Andronopoulos Spyros,
Bartzis John G.
Publication year - 2018
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/jiec.12667
Subject(s) - context (archaeology) , gross domestic product , econometrics , productivity , production (economics) , index (typography) , economic statistics , economics , statistics , computer science , mathematics , macroeconomics , geography , archaeology , world wide web
Summary The material intensity (MI) of the economy remains among the most widely cited indicators in international statistics and reports, evaluating the efficient use and productivity of natural resources in the economic process. In the context of the contemporary economy‐wide material flow accounting framework, the material intensity of a country is evaluated through the estimation of the ratio of the domestic material consumption (DMC) to the gross domestic product (GDP) index (DMC/GDP). Indeed, the essential contribution of natural resources to the economic process requires the establishment of reliable projections of this intricate relationship to the future. These projections may provide critical information to policy makers and practitioners in order to evaluate the future dynamics of the efficient use of natural resources in the production process. Toward this objective, the present study evaluates and proposes an alternative novel methodology for MI statistical projections, based on the beta distribution, by using a deterministic model for predicting the maximum expected values. The parameters of the deterministic model are calculated from the estimated MI of the global economy. The evaluation of the model is then performed by using MI estimates from 107 individual countries. The agreement between the model and the estimates is very good. The proposed method's merit is its simplicity, as by using two statistics of the material intensity (mean and variance) and an integral time scale, it is feasible to calculate the probabilities of the MI of any country with a high degree of confidence.