Throughout most of my research I have been visualising transport related issues, most of them involving flows of people at various spatial scales. Recently I have been looking at flows of a rather different nature: development flows. Here are some early notes on the data.
The main dataset analysed has been collected from Organisation for Economic Co-operation and Development (OECD) which has a really helpful website to collect all sort of development aid data. I downloaded the Geographical Distribution of Financial Flows. In this post I will focus the analysis on food aids.
To observe how aid was distributed I decided to give a go at plotting flows of food aid in a world map. The way I decided to do so is by highlighting the country about to donate food aid in orange at the start of the year. Then, packets of food aid come out of the donor towards each one of the recipients. The size of the packets is proportional to the amount in million USD they correspond to. When the flows are about to reach their destination recipient countries, those are highlighted in purple. There is also a bar indicator on top of each country centroid which indicates how much food aid each one has donated/received as years go by. This indicator is updated when flows come out of a donor and when they reach the recipient.
I should also point out that I have left flows involving the following donor/recipient entities out of the animation: AfDF; Africa, regional; America, regional; Asia, regional; Chinese Taipei; Developing Countries unspecified; Europe, regional; European Union; Far East Asia, regional; Gibraltar; Hong Kong, China; Kosovo; Mekong Delta Project; Middle East, regional; Montenegro; North & Central America, regional; North of Sahara, regional; Oceania, regional; Samoa; Serbia; Seychelles; South & Central Asia, regional; South America, regional; South Asia, regional; South of Sahara, regional; States Ex-Yugoslavia; Timor-Leste; Tokelau; UNDP; UNICEF; West Indies, regional and WFP. The reason for this being that in order for me to assign them on the world map I collected, it would require me to edit it out to explicitly define those regions. This is something that I might do later on. This is quite relevant as for instance, the European Union is the second top donor or the Developing Countries unspecified, the first top recipient. Flows with negative value have also been ignored.
The first thing which one notices after watching the entire clip is that US Food Aid amount is one order of magnitude higher than any other donor. Other proficient donor countries are Canada, Japan, Germany or Italy. Amongst the top recipient countries, Egypt stands out from the rest, followed by Bangladesh, India or Ethiopia.
It is curious to see how the US is not donating any food aid during 1994, but that is due to an error in the data collected.
Presumably, some historical events are present in the data as a result of conflicts occurring within that period but I haven’t looked at it yet.
Loading more stuff…
Hmm…it looks like things are taking a while to load. Try again?