But here's the good part: a version of that wonderful software shown in the video is available online, complete with a tutorial. I decided to look at Zimbabwe (the "software link" should take you straight to that graph. It worked for me in Safari, but not in Firefox). Robert Mugabe is widely believed to be destroying his country, so I wanted a better look. I decided to take a look at two key indicators, child mortality and economic growth. (Chart reproduced in case the "software" link doesn't work for you).
Obviously, you want a lower child mortality and a higher economic growth. From 1965, when Southern Rhodesia (as Zimbabwe was then known) declared independence, to 1970, declaring itself the "Republic of Rhodesia", the child mortality and economic growth indicators generally improved. But as you can see from the chart, there was a sharp downturn in both indicators starting in 1970 and lasting until 1977. What happened?
Around this time period, Ian Smith, the prime minister of Rhodesia, led a white government that did not want to share power with the black minority and there was a constant civil war. In 1978 an accord was signed with black leaders and open elections were held, bringing blacks into power. After an initial strong spurt of economic growth, the growth slowed down, but generally remained positive until 1990. Child mortality dropped significantly during this period. Around 1990, everything fell apart. Infant mortality skyrocketed and economic growth plummeted.
Robert Mugabe, first elected in 1980, decided in 1991 to institute an austerity program which was a disaster and to this day, he's still all over the news for how well he's single-handedly destroying his country.
What's interesting is that I sound mildly educated about this topic, but it only took me a few minutes to learn all of that. Most of the time was spent writing this post and editing that graphic. I think the Gapminder software can be a fantastic tool for people to dig for information that was previously not available. The downside, of course, is that correlation is not causation. Merely because major events mark turning points on the Zimbabwe graph does not mean that the data and events are related. I suspect they are, but it's a useful caveat to keep in mind.
PS: If you really want to have fun, compare life expectancy and physicians per 1000 people and watch life expectancy drop like a rock starting in 1987. I was also startled to note that the US had a significant drop int the percentage of women using contraceptives, starting in 1995. It appeared to drop 12% over 4 years.