thismeintiel said:
Helloplite said:
Okay, since many use GDP here: GDP is also just as unreliable a marker as GINI. The latter only looks at inequality at the two extreme ends, therefore missed several important qualitative characteristics. The first (GDP) either as an aggregate or per capita, does the opposite mistake of obscuring inequality. A high GDP per capita country with a low GINI is a far fairer society than a high GDP per capita with high GINI (because in the second case, GDP per capita is a fictional number that does not represent the experience of the average citizen).
Example 1: A state with low GDP, low GINI: Consistently poor population on average, but also no major presence of elites / oligarchs. Not many states fall into this category.
Example 2: low GDP / high GINI: Many Africa states have this where GDP is low as inequality dominates. Indicates a very poor population with a number of ultra rich individuals.
Example 3: High GDP / low GINI: Most Scandinavian countries are here: Wealth abound and distributed fairly. Also probably indicates a state where there is very high taxation on the rich (also Scandinavian countries).
Example 4: High GDP / high GINI: China is the most typical example. The high GDP here is not actually indicative of the average citizen who is likely to be very poor. Most money is concentrated into few hands, and while the country as a whole is seemingly prosperous, the average citizen earns less than the stated GDP per capita. |
Wait, you just said how both of those aren't very good markers, but then use them to try to make a point?
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It ought to make sense to you since I didn't say what you imply here. In separate they are unreliable markers. In combination they become more helpful, although still do not provide adequate insight into qualitative characteristics. Combining metrics is always a better way for aporoximating complexity so that makes what I said sensible. They describe different things, and separately are unreliable, but combined offered I improved insights. But generally speaking, using quantitative methods to analyze society or the economy can lead to many incorrect assumptions.
