African poverty is falling…much faster than you think
voxeu.org
voxeu.org
For example if more people live in big cities, is this growth enough ? (1$ can mean something different : in New York $400 certainly makes you poor…). Is this growth compensating former hidden markets, like self food producing and local non monetary exchanges ? (you can sell cotton and have more money, while still having it harder to buy food). Do their subsistance depend more or less on external factors like speculation ? Are there less wars/civil wars ?
(In other words, there are at least a few statisticians working for the UN and the World Bank, and they tend not to be “basically innumerate”.)
http://www.salaimartin.com/media/pdf/Africa_Poverty_NBER.pdf
And criticism of their results from someone working on producing similar numbers for the World Bank:
http://blogs.worldbank.org/africacan/is-african-poverty-fall...
I must say that it irks me that they would use such a easy-to-understand-and-wrong ($1/day, when they mean "below the international poverty line") unit in writing without specifically qualifying it.
I didn't think so.
1) People who use guilt trips as a technique will always find new fodder with which to guilt trip you. They will never say "Oh, ok, that's been resolved so we're done now"
2) (Sadly,) There will always be a child starving somewhere
I'd prefer to give money to something like Child's Play for Toronto Sick Kids than give it to somewhere in Africa and I know many people will disagree with me for it, but IMO it sucks greater being the 1 in 100 kid that is gravely ill rather than the 1 in 2 kid that is starving. Throwing money at a norm isn't going to resolve it, but throwing money at the abnormal can indeed resolve it.
However, if you're an orangutan I'll donate to help you wherever you are - I like them much better than people.
http://lesswrong.com/lw/z2/another_call_to_end_aid_to_africa...
For instance, I have no idea what the metrics in Figs 2 and 3 are exactly, but I can see that the inequality metric in Figure 2 has reduced itself to approximately 1970 levels and that, since 1995, the welfare metric in Figure 3 has increased by (very roughly) twice the standard deviation of the past 30 years' measurements.
Of course scale is important, but it is folly to trot out the same argument every time a graph does not include the origin. Without knowing something about the y-axis variable we cannot make this type of claim.
I don't think "the bottom of the Y-axis isn't zero" is a guaranteed bad graph, especially considering some of the horrendous graphs out there. These ones are not that bad.
Suppose we want to show changes in temperature---unless you use the Kelvin scale, showing percentage changes is going to be bogus. Showing change relative to recent volatility seems useful.