My name is Jordan Beecher, and this Friday, 2 August marks the completion of my two-month internship at Development Initiatives.
I have been here as part of the Masters in Environmental Change and International Development course at the University of Sheffield, under the watchful eye of the Global Humanitarian Assistance (GHA) team.
Whilst here I have done and learnt many things about analytical techniques, humanitarian assistance, and international development in general. I have had to balance my GHA workload with carrying out research for my dissertation, but as it turns out, the two weren’t as incompatible as I had feared; the skills that I have been picking up through my work here have been directly applied to my own work.
For my dissertation I am analysing the financial resources available to address climate change, and in particular, money available for developing countries to adapt to changing conditions. I am using existing data to look at the volume of resources and their geographic distribution.
Understanding these resources is similarly difficult and involves similar challenges to tracking humanitarian assistance. With technical advice from GHA analysts, I have developed a viable method of assessing financial flows to and from different countries, all using publicly available data. I have learnt not only what you can do with data, but how much you can do with it. I have been unlocking the secrets of excel that are hidden from us as students!
For example, in a very similar fashion to GHA’s work, I have been able to compare the behaviours of different donors. I am able to report on who spends the most, who spends the least, who has met their commitments, and who has not on climate change-related aid. Below is one of the initial outputs of my analysis. It shows the proportion of donor countries’ official development assistance (ODA) that was spent on adapting to climate change in 2011. The data used for this figure comes from the OECD DAC’s Creditor Reporting System (CRS) database, and values for adaptation spending were obtained from the Rio Markers.
Figure 1: Percentage of ODA spent on climate change adaptation by OECD DAC donor governments in 2011
Source: OECD DAC CRS. Note: Figures exclude the newest DAC donor, Iceland
Firstly, you can see that different countries contribute different amounts of public money to climate change adaptation. This particular estimate shows that 15% of Finland’s ODA in 2011 assisted adaptation activities, whereas less than 1% of ODA from the United States went towards climate change adaptation. Of course, there are many methodological, political and definitional issues that make such analysis inherently subjective. For example, the quality of the OECD DAC CRS data is largely dependent on the respective donor’s capacity to report their spending accurately. This assumes a universal understanding of what constitutes adaptation activities, which is in fact non-existent. Nevertheless, I believe am able to provide an indication of current trends and patterns using this methodology.
As a student of geography, my analysis is naturally concerned with comparing spaces and places, so as part of my work I will also be asking the question: to what extent does the current pattern of resources meet the pattern of need in developing countries? This raises further questions on how to define need. Unlike humanitarian need, which can use numbers of people affected, there is no universally accepted metric for assessing how costly climate change is, or will be, to particular places or times. Instead, I am relying on a variety of existing assessments, of economic, social and biophysical vulnerability, to suggest where resources are needed the most. Mapping the distribution and volume of adaptation assistance alongside varying levels of climate change vulnerability, it becomes possible to at least begin to visualise the answer to my initial question regarding the extent to which the pattern of resources meets the pattern of need in developing countries.
Below is the result of such an exercise. It shows the vulnerability of different African countries (as assessed by DARA) and the public adaptation assistance that was disbursed in 2011.
Figure 2: Vulnerability to climate change and the distribution of public adaptation assistance 2011
Source: OECD DAC CRS and DARA data
With red representing ‘acute’ vulnerability to climate change, and the size of the black symbols representing the volume of assistance, it becomes clear that that the pattern of assistance does not exactly match the pattern of need. Various contributory factors such as perpetual definitional challenges make it impossible to make conclusive comments at this stage of my research; however I expect that the results shown above will be replicated in other global regions, and that existing financial resources will be shown to be largely inadequate. These findings can later be compared to the inadequacy of other development efforts such as tackling malnourishment or chronic poverty.
My work also raises more pragmatic and even ethical questions around responsibility, accountability and justice. Should, for example, adaptation to climate change be funded solely by developed countries (who have historically contributed the greatest to anthropogenic climate change)? Where should the money come from? And is adaptation to climate change a development issue or a separate issue altogether? I will tell you if I ever find out.