Fall Curve


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Factors Behind the Environmental Kuznets Curve. Growth and the environment in Canada: an empirical analysis Kathleen M. Day , Rupert Quentin Grafton. Causality between income and emission: a country group-specific econometric analysis Dipankor Coondoo , Soumyananda Dinda. Explaining changes in global sulfur emissions: an econometric decomposition approach David I.

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Stern , Michael S. Does continued economic growth eventually lead to decreasing inequality?

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There is both evidence and explanation that bears him out. It shows a clear inverted-U, with an initial rise, a peak in , and an overall decline through Similar curves are found for most Western European countries, though their timing varies. Many developing countries see greater inequality than developed countries, hinting that inequality decreases as a country becomes developed.

From Emmanuel Saez, Kuznets called the reduction in inequality "a puzzle," since it seemed to counter forces that ought to increase inequality.


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First, there is a rich-get-richer phenomenon, as upper-income groups are able to save more and therefore invest more in income-earning assets. Second, increasing industrialization causes more of the population to move from low-income rural agriculture to high-income, higher-variance urban employment. Both trends ought to increase inequality.

So, what might cause inequality to decrease? Kuznets and others have offered a range of explanations.

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First, a dynamic economy may see more movement into and out of the higher income brackets, effectively eroding and diluting the richest households' share at the top. Second, industrial pay may saturate at the top, as more workers enter into it. Third, the greatest inequality may happen when a population straddles two sectors with differential income, so as the agricultural sector shrinks to nothing, inequality also declines. The explanations are plausible enough that the Kuznets curve has had a sturdy following.


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What about for these less symmetric distributions? Well let's think about it over here. Where would I have to put the fulcrum, or what does our intuition say if we wanted to balance this?

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Well, we have equal areas on either side, but when you have this long tail to the right it's going to pull the mean to the right of the median in this case. And so our balance point is probably going to be something closer to that. And once again, this is me approximating it, but this would roughly be our mean.

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It would sit, in this case, to the right of our median. Let me make it clear, this median is referring to that, the mean is referring to this. In this case, because I have this long tail to the left, it's likely that I would have to balance it out right over here. So the mean would be this value, right over there. And there's actually a term for these non-symmetric distributions where the mean is varying from the median.

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Distributions like this are referred to as being skewed. And this distribution, where you have the mean to the right of the median, where you have this long tail to the right, this is called right skewed. Now, the technical idea of skewness can get quite complicated, but generally speaking, you can spot it out when you have a long tail on one direction, that's the direction in which it will be skewed, or if the mean is to that direction of the median. So the mean is to the right of the median, so generally speaking, that's going to be a right skewed distribution.

So the opposite of that, here the mean is to the left of the median and we have this long tail on the left of our distribution, so generally speaking we will describe these as left skewed distributions. Density Curves. Up Next.

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