Benchmarking Sustainable Development via Data envelopment Analysis:an Italian case study


Dipartimento di Elettronica, Informatica e Sistemistica, University of Calabria, Via P. Bucci 41C, 87030 Rende (Cosenza), Italy


The need for monitoring the overall performance of countries in Sustainable Development (SD) is widely recognized, but scant attention has been devoted to methods for aggregating and analyzing vast amounts of empirical data. This paper describes the development and application of a Data Envelopment Analysis (DEA) methodology for addressing the challenges of benchmarking sustainable development. The methodology involves linear optimization techniques, and it is based on the identification of a number of attributes that provide proxy sustainable development indicators. Using these techniques, a SD index is derived, which might combine existing aggregate SD indices (developed by well-established organizations and/or expert teams) into a single synthesizing overall SD index. We propose the use of four different modeling techniques to address these concerns and report the results of an Italian case study. From the results obtained, it is possible to note that the inefficient regions are, overall, southern regions and some central regions. In particular, their inefficiency comes from high poverty rate and CO2 emissions. Nevertheless, regional economic disparities are evident and with root in government’s preferential policies towards on foreign investment for the northern regions, greater access to markets and better infrastructure. The political implication of these findings is that these regions have to concentrate to keep low the rate of CO2 emissions and to favor a good sustainable development from a social point of view. Exceptions are Basilicata and Sardegna regions, which exhibit a low poverty rate and a medium GDP per capita. The most inefficient DMUs are Sicilia, Calabria, Puglia, Campania and Abruzzo. Piemonte is borderline, even though the region has a good geographical position for the industrial placement. We view this approach as a first step towards more systematic international comparisons, aimed at facilitating the diffusion of the best practices and policies from the benchmark countries to the less developed world regions.