Measuring biodiversity performance: A conditional efficiency measurement approach

This paper uses a methodological framework based on the new advances of Data Envelopment Analysis (DEA) and a sample of 71 developed, developing and under-developed countries to model and evaluate their biodiversity performance. Specifically, by using conditional DEA, bootstrapping and kernel density estimations, the efficiency levels of these countries are compared and analysed in such a way as to show whether the countries environmental policies have been used efficiently in order to enhance biodiversity. Our empirical results indicate that there are major inefficiencies among the countries considered in terms of their biodiversity performances revealing that population level is the dominant threat of countries’ biodiversity performance followed up by GDP per capita and income inequalities. At the same time CO2 per capita, population, income inequalities and GDP per capita have different impact on developed, under-developed and developing countries which implies that environmental policies must be adopted and implemented accordingly.