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January 28, 2008

Comments

Diana Lee

Looking at income per capita plotted against military expenditure, I think I was surprised to see a negative relationship between the two, although the data was a bit sparse. First, I had never realized that South Asian countries spent so much on the military. It makes me wonder whether there is any partial causal relationship between income and military spending and which way the relationship might go. Is it that countries that face national insecurity do not have an economic atmosphere that is conducive to development or that countries with more economic security have less incentives/need to enter into war? Or is it a vicious cycle. Also, it had also never occurred to me that U.S. military spending was so much of an outlier and it makes me wonder if its high military spending may be a predictor a decrease in its relative level of prosperity in the long run. Having lived in the U.S. my entire life, I had formed the perception that we spend so much on the military because we are so well off and fearful that our position as world leaders would be threatened. Yet, most of the high income countries, namely in western Europe, have relatively low levels of military spending. So it makes me wonder what it is that has led to this fairly large divergence and which national policy will win out in the end.

Alex Hornof

The degree to which other variables correspond to the change in GDP per
capita is particularly telling; with clear positive correlation with carbon dioxide emissions, life expectancy, and urban population, and negative correlation with birth rates and infant mortality. India is a remarkably clear example of all these trends, following the general curve perfectly. However, one trend exhibited a very interesting regional variability: percent women in the work force. In Europe (with the exception of Turkey) and the Americas there was a clear positive correlation with GDP per capita, however in South Asia and the Middle East the correlation is less consistent and often negative. This is demonstrated clearly by the case of India, which clearly followed the general curve on all the other variables listed, yet the percent women in the work force decreases with GDP per capita. The data provides an interesting and concrete example of differing cultural opinions towards women.

Stephen Gu

I looked at the effects of urban population % on military budget %. The general trend seems to be that countries with lower urban population percentages have higher a higher military budget percentage. This seems to make sense because urban population percentage can give a general idea of the status/wealth of the country. It makes sense that developing countries spend a higher percentage of their GDP on the military because they fear unrest. However, it makes little to no sense for countries with high urban population percentages such as the United States, Russia, and Singapore to have such high military budgets while their urban counterparts, such as most countries in Europe, have very little. It seems ridiculous that a country such as Singapore would need to allocate such a large percentage of their GDP to the military when it could be used more efficiently elsewhere.

Victor Ho

I find it very interesting that life expectancy has varied so closely in line with carbon dioxide admissions. It is interesting because this is exactly what I would expect, yet it seems that people so often ignore the fact when it comes to polution. This is a notion that has become so popularized by the green movement that it almost seems to be some fad, rather than an outcome grounded in actual fact.

One thing I found surprising was that the number of girl compared to boys in school is completely uncorellated with women as a % of the workforce. I would thing that a strong corellation would exist, but no real noticeable pattern is discernable.

Elliot G

The correlation between mobile phones per 1000 of the population and the GDP per capita is interesting. Obviously you would expect there to be a positive relationship as richer people can afford to spend more on technology and mobile phones in particular whereas very poor people have to spend more on food, etc. However the strength of the correlation is what surprised me. They are extremely positively correlated. I expected poorer countries with massive recent growth in this mobile communication industry like India and Pakistan to have much more phone users per 1000 of population but then again these countries still have large percentages of the population earning under $1 a day. Furthermore you can see a shocking and personally disturbing related fact that the US and a group of other rich countries now have over 1 phone user (I am assuming mobile phone) to every member of the population, while large numbers of people in poorer countries can't afford to eat.

Another interesting relationship is the relationship between children per woman and the number of girls compared to boys in high school. You would not expect to find a relationship as more children should be evenly spread over boys and girls. If anything you would expect that in some countries more children means that you could afford to send some of your daughters to school while the others work to provide an income so you may expect a positive relationship. In fact there is a slightly negative relationship and more children seems to result in less girls to boys in high school. The only reason I can think for this is that with more children some of which will be boys, in some poor countries with male orientated cultures, with more boys, the extra girls and the existing girls in a family will not be able to attend school as they have to work so as to be able to give the boys an education. However I don't know how plausible this is.
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Konniam Chan

I looked at life expectancy versus urban population percentage. As we intuitively expect, urbanization allows people to attain a higher standard of living. This includes better living conditions and more convenient access to healthcare. Not surprisingly, this is what is observed in the graph for 2004. There is a positive correlation between life expectancy and urban population %.

An interesting trend from the Gapminder data is that while most countries move toward the upper right of the graph as time moves forward, some start to fall. Most of these nations are from Africa. Although many African nations are in the process of urbanization, life expectancy remains low and even worsens. This is a troubling statistic. I believe that this has to do with epidemics and wars being fought in Africa, but a more complete scrutiny of the situation many reveal more underlying problems.

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