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gini coefficient explained 2 Minute Economics
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As I said in my video on GDP, one of the reason it is an unreliable metric is because of its lack of dimensions and one of these dimensions is inequality, however economists have come up with a way to measure this also, so in today’s 2 minute video we are going to look at the GINI coefficient. • WHAT IS IT? • GINI coefficient measures the inequality of a society from 0 to 1, 0 being the most equitable and 1 being the most extreme. • COMMON MISCONCEPTIONS • It is not an end all be all, usually we need to pair this with gdp per capita to get the bigger picture or median income, why? Because ukraine has a gini coefficient of 0.261 and a GNI per capita of 9000$ while the U.S. has a gini coefficient of 0.465 but a GNI per capita of 63000$, Therefore if we were to look at simply the GINI coefficient ukraine would be much better but overall the U.S. is much better (don’t @me). • A couple of billionaires does not mean GINI coefficient is high, how? Because the gini coefficient increases rapidly if a small minority of lets say 10% control 50% of the wealth not if 1% control 5%, for an example we can look at south africa were the white-dutch ethnicities control most of the wealth therefore they have the worst gini coefficient in the world a whopping 0.63. • WHEN WAS IT INTRODUCED • It was developed by an Italian statistician named Corrado Gini in 1912. • ITS SHORTCOMINGS • It is very difficult to calculate the entire world’s gini, since such data is not scalable to the entire world, often as students of economics we forget that countries are a man-made construct. • Developing countries especially in Africa have huge informal economies that cannot be tracked and brought into the fold of modern economics hence this data may be even more skewed in Africa and sadly not in its favor since workers in the informal sector usually make less than the formal thus if there were theoretically no informal sector the GINI coefficients of developing countries would be even worse. • Tax havens are a big pain for those calculating gini coefficients since the influx of cash counts in GDP but doesn't really help the local population. • It does not show variation of income across sub-groups of the population but the entire population, for example in the U.S. the average Indian American makes 104,000$ a year and the average African American makes 35,000$ the gini coefficient cannot show us this since it tries to compact the data from the lorenz curve and the equality line into a single number. • CONCLUSION • GINI coefficient is an important term in economics and in statistical data. It allows us to better understand an economy, so in the next video shall be on the lorenz curve so that you can learn how to measure inequality at home. • ~-~~-~~~-~~-~ • Please watch: India's Smartphone Economy Is Booming • • India's Smartphone Economy Is Booming... • ~-~~-~~~-~~-~
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