On Wed, 24 May 2006, Jobst Heitzig wrote: > a week ago I suggested using social welfare functions (such as the Gini > welfare function) to evaluate election methods.
I have also been trying to run simulations that count up the social welfare, but my initial results caused me to doubt my implementation. The equation I got from this discussion of the form f_ave - (big cross comparison term) gave me results which seemed to just be f_ave minus a relatively constant factor. It didn't seem to change the relative positions of the election methods versus their plain average social utility. I was also unable to reconcile the equation from this forum with the wikipedia version here: http://en.wikipedia.org/wiki/Gini_coefficient But maybe that's just because my algebra is rusty. Anyway, I'll take any equation with anyone's name on it if the equation can be well characterized and shown to measure the properties we want to measure. In my previous simulations I measured the standard deviation of happiness within an election. I got data like this: http://bolson.org/voting/graph/cv1000/e0_00.png I'm still interested in a better measure than standard deviation if we can find one. What's the qualitative difference between Gini and standard deviation? (both in one way or another measure how widely distributed the population is) What exactly is the right thing to measure? I guess I'm still thinking about it. Brian Olson http://bolson.org/ ---- election-methods mailing list - see http://electorama.com/em for list info
