The most interesting thing here (I think) is the proposal to measure inequality by computing a Gini coefficient on log incomes rather than raw incomes. This seems like a fairly natural thing to do and it seems plausible that it produces a metric that does a better job of identifying actually-harmful inequality. But isn't the fact that scaling all incomes by a constant factor -- hence adding a constant to all the log-incomes -- changes the metric a fatal objection?
Does anyone have a reasonable argument for when inequality is worse than absolute poverty, and what decisions one should make based on a dispersion measure in the first place? IMO, the fatal objection is that it's pointless to pick a measure without being able to describe its use.
edit: this model should also include a reasoning that it makes ANY sense to measure by national boundary, as opposed to globally, by language group, by age cohort, or some other natural grouping.