I'm a little confused by these 2 plots from Chetty et al 2014: http://www.equality-of-opportunity.org/assets/documents/mobility_geo.pdf
>From the ranked plot, it seems like an equitable leveling/redistribution is at >work. But from the raw income plot, it simply seems like children make less >money than their parents (an absolute reduction in quality of life). These >seem paradoxical to me, meaning that perhaps I haven't grokked all the data, >or the particular data being plotted is inadequate to express the trend. I >confess I'm motivated by stories from Pinker and Shermer about absolute >improvements in the world (considered massively, not particularly), which >leads me to the leveling interpretation. On 12/9/20 5:25 AM, David Eric Smith wrote: > To continue to try to add raw material to the discussion that EricC took up > on this when I made some overly-simple claims earlier, here is a Brookings > summary article on work by Raj Chetty (cited in the earlier thread as well): > https://www.brookings.edu/blog/social-mobility-memos/2018/01/11/raj-chetty-in-14-charts-big-findings-on-opportunity-and-mobility-we-should-know/ > > <https://www.brookings.edu/blog/social-mobility-memos/2018/01/11/raj-chetty-in-14-charts-big-findings-on-opportunity-and-mobility-we-should-know/> > A thing I find striking in Chetty’s output is how many compilations he can > produce that make statistical analysis superfluous. There are data that are > so close to a perfect line that there is little for a regression to do, or > that are so consistent with time-constancy that there is no suggestion of a > signal to look for other than stasis. A lot of it seems to come from finding > good conditions on which to bin data, though the bin categories do not seem > highly artificial or cherry-picked, to me. -- ↙↙↙ uǝlƃ
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