Visualizing Global Conflicts and Economies

As anyone who has read my blogs, you may notice that I have much interest in big data applications in the military. After researching military spending in different nations, I thought it would be interesting to combine percent GDP spent on military with GDP per capita and watch how conflicts along with economic problems affect nations around the world.

Before discussing the motion chart and what it entails, I’d like to discuss how I created the chart. First of all I wanted to find a reliable source that could give me data that I could transfer into excel without any problems. I found that worldbank.org was the most suited for what I was searching for. 

Next, I transferred all of the data for GDP per capita and percent GDP spending on military into excel spreadsheets. After looking at the data over the past few decades, I decided that I would start extracting data in 1995. I chose this year because there was a lot of data missing prior to it, yet it would still allow for a good perspective of the effects of the attacks on September 11^th and the subsequent years of conflict and economic recession to 2011.

Raw data taken from WorldBank (GDP/capita from '95 to '11)

Next, I removed nations that lacked sufficient data. My general rule was any nation missing more than four years of data were automatically removed. Nations missing four years were only removed if all four of the years missing data were successive. Nations not falling under these categories were kept. Once I had all of this data, I compiled a master list of the nations that had sufficient data in both GDP per capita and percent GDP spending on military. There was enough data on population that it did not diminish the list.

The list, now at 130 nations, still had missing data. The years missing data were simply given the previous years’ data to prevent countries from spontaneously disappearing on the chart and to minimize time spent on this step. If there was a drastic difference in years before and after missing data, I inserted numbers approximately midpoint of the data on either side to prevent sudden changes that most likely did not occur as radically as they would have shown. The final indicator I used was the region that the nation was located. I separated the countries into ten categories. 

Then I transferred this data to Google spreadsheets in order to create a motion chart of the data over 16 years. 

Raw data transferred to Google spreadsheets

Now, the data needed to be transferred to Google spreadsheet, and organized correctly in order to create the motion chart.

Organized data in correct columns

Lastly, I simply had to create the chart by selecting INSERT, CHARTS, and the motion chart. Once the chart was created, I changed the color indicator to be dependent on the region, and the size of the nation icons to be dependent on the nation’s population. 

Completed motion chart

There is too much to gather from this motion chart to address, however, I will discuss some of the aspects that stood out to me the most. The first was the obvious similarities in neighboring nations, and nations in the same regions. The best example of this is the nations I classified as western European which included northern European nations like Sweden, Norway, and Finland. Indicated by blue and labeled below, these nations are most easily recognized by how much higher their GDP per capita is than most nations used in this visualization. Watching their movements over the sixteen years, it is obvious that they react similarly to effects in the economy. 

You can also see nations jump across the x-axis every few years. Almost all of these nations are either African nations with isolated conflicts, or Middle Eastern nations responding to the nearby wars in Iraq and Afghanistan. One exception to this is Georgia during the Russian invasion in 2008.

At the same time, nations like the United States, Japan, and Australia have the GDP/capita and military spending relatively independent of the nations surrounding them. During the economic collapse in 2008, you can see almost all first world nations have a significant decrease in GDP/capita. You can also see that the percent GDP on military increases for almost all of these nations. This is primarily because of the decrease in GDP combined with the lag in the time it takes lawmakers' in those nations do decrease military spending.

When watching the United States, one can tell that the years of economic prosperity and minimal conflict up to the year 2000 left the US in a direction of increasing GDP and decreasing defense spending. Some of this decrease in percent of GDP spent on military may be attributed to the steadily rising GDP. Beginning in 2000, you can see that the decreasing spending on military ceases. Once 9/11 occurs, you can see the obvious increasing military spending. From 2004 to 2007 there was little increase in military spending, however, in 2007 with the surge in Iraq military spending is drastically increased. In the last few years with the removal of troops and the ending of the war in Iraq, you can see a shift into decreasing military spending. 

To view the data and chart:

https://docs.google.com/spreadsheet/ccc?key=0AqWGjpVWoZFSdExzVkN2UG9xWjNZcC1yZTJGODA5SXc&usp=sharing