It has been a while since I last discussed a paper from econophysics, where it appears there is a substantial literature trying to describe the distribution of income. It turns out to be quite difficult, because the goal is to do this with a single equation. What one would want to do with that equation is not clear to me, but anyway.
Maciej Jagielski and Ryszard Kutner claim success with this endeavor by essentially dividing up the distribution in three parts, fitting each to a different distribution function, and then rejoining them into a single equation. But what income are they taking about, you may ask? They look at European income in 2006 and 2008, and take the data from the SILC EU project. That still does not determine what income they are considering, as the dataset allows multiple different ways to define income. It is not even clear whether this is income before or after taxes and whether it includes capital gains.
One problem the authors realized is that they need oversampling for to incomes. To take care of this, they look at the European billionaires on the Forbes list of the richest people over several years, conclude that changes in wealth must be "income" and take that, dropping all negative incomes along the way. Then they notice a large discontinuity from merging the two dataset and decide to divide the top incomes by 100 to make the joint distribution continuous. Oh boy. And this is the dataset they used for their study, believe it or not.
Maciej Jagielski and Ryszard Kutner claim success with this endeavor by essentially dividing up the distribution in three parts, fitting each to a different distribution function, and then rejoining them into a single equation. But what income are they taking about, you may ask? They look at European income in 2006 and 2008, and take the data from the SILC EU project. That still does not determine what income they are considering, as the dataset allows multiple different ways to define income. It is not even clear whether this is income before or after taxes and whether it includes capital gains.
One problem the authors realized is that they need oversampling for to incomes. To take care of this, they look at the European billionaires on the Forbes list of the richest people over several years, conclude that changes in wealth must be "income" and take that, dropping all negative incomes along the way. Then they notice a large discontinuity from merging the two dataset and decide to divide the top incomes by 100 to make the joint distribution continuous. Oh boy. And this is the dataset they used for their study, believe it or not.
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