Efficiency: The sustainability criterion that provides useful guidance for statistical research

Abstract

This paper is a contribution to the present debate on how to effectively measure progress towards sustainability, which is currently engaging environmental statisticians and users of data worldwide. The three pillars of Sustainable Development – economic, social and environmental – throw up a large number of potential 'indicators' for each of the pillars, but unless these can be linked, they do not necessarily help to answer the fundamental questions:

- Are we moving towards a more sustainable society/economy?

- Is our economy progressing at the expense of the environment? Or of the health of society?

- Are the ‘improvements’ we see in some environmental indicators real improvements or simply a result of a sluggish economy, or of the ‘exporting’ of environmental problems to other countries?

While eco-efficiency indicators cannot answer all these questions, they attempt to link the different pillars and to produce at least a partial answer to some of the questions.

In the first part the paper describes the sustainability measurement criteria, i.e. capital stocks, efficiency and equity as well as the ecological, economic and social dimensions and the major statistical areas of work or studies that aim to produce information for the policy-decision process.

In the second part the focus is on the concept and design of eco-efficiency indicators which have the large advantage of presenting data so that the ecological, economic and social dimensions as well as the measurement criteria are integrated in a simple ratio that can be multiplied but remains easy to calculate and understand. It defends that sector-oriented eco-efficiency indicators are possible to calculate, provide useful information and serve the purposes of national and international statistical production as well as the users needs quite adequately.

Sector-oriented eco-efficiency indicators, obtained by combining existing and well known environment statistics or indicators (physical data) with even more widely used economic statistics, require an adequate graphical display and analysis to be able to communicate to a wide audience. This is illustrated in the last pages of this paper.