Presently there are about 13 global Multilateral Environmental Agreements (MEAs) and/or conventions and about 500 international treaties or other agreements related to the environment. This proliferation of agreements has created concern among international and national communities regarding overlap and duplication of goals and programs, in part because lack of coherence results in high transaction costs and inefficiencies in achieving convention objectives. This growing concern has made policy coherence the single most important theme in the dialogue on International Environmental Governance (IEG).

 

Initiatives flowing out of various environmental conventions have yielded a more integrated approach towards environmental management, fostering more effective policy coherence. However, much remains to be done. There is still little effort being made to find coherence between environmental agreements and development initiatives, especially the Millennium Development Goals (MDGs). Drawing on a review of the policy coherence literature, we develop a methodology to quantitatively measure policy coherence, and then use it to evaluate the degree of policy coherence between the Convention on Biological Diversity (CBD), the UN Convention to Combat Desertification (UNCCD), the UN Framework Convention on Climate Change (UNFCCC), the Convention on Wetlands (Ramsar) and the MDGs.

 

The results show that we have a long way to go before we achieve an acceptable level of policy coherence. CBD does the best job of representing other MEA issues, while Ramsar does the worst. This is understandable since CBD has a greater number of synergy instruments and also has a greater mention of other conventions in its documents. One reason that Ramsar shows low levels of coherence with other conventions might be that Ramsar is a much older convention (1971) than the Rio Conventions (1992), and greater synergy efforts have taken place amongst the three Rio Conventions. The rankings also show that CBD is well-represented in other conventions, while UNCCD is the worst represented convention. This is a disturbing finding since arid and semi-arid areas contain a large section of rural poor, especially in developing countries.

 

Our results indicate that there is a significant need to improve certain relationships. However, attempts to strengthen these inter-linkages need to be assessed with care. This is so because there are limits to achieving policy coherence. Having overlaps or inter-linkages or strengthening them does not mean we need to achieve 100 per cent policy coherence. Attempting to do so would mean that the identity and objective of an MEA is no different from another MEA or MDG. In reality this is not so. A qualitative analysis along with our quantitative analysis can help us decipher the limits and achieve healthy interlinkages between overlapping conventions and goals.

The full paper can be accessed at: http://www.iisd.org/pdf/2007/measuring_policy.pdf