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.
a reasonable argument for when inequality is worse than absolute poverty
Rather seldom, I’d think. I would expect serious attempts to measure when one is worse than the other to fall foul of the usual problems around interpersonal utility comparisons etc., and if any econometric measure has been dealt with rigorously enough to make those problems go away, I haven’t heard of it.
I think one can at least make a reasonable argument for why inequality is (sometimes) bad; then figuring out whether any given instance of it is worse than any given instance of absolute poverty “only” has those usual problems to contend with. Inequality is (sometimes) bad for at least the following reasons.
Empirically, even after reasonable attempts to avoid confounding with absolute poverty, inequality at the country level has been found to correlate with all manner of social ills. See e.g. Pickett & Wilkinson, The Spirit Level. (I make no claim that everything in that book is right, but it makes a reasonable argument.)
Human brains (non-human brains too, I think) operate by comparisons. Someone who feels worse off than others around them will almost always feel bad as a result. Greater inequality means more people feeling more worse-off than others. This doesn’t operate only at the country level, but within-country comparisons tend to be more salient than cross-country ones because of e.g. media with national scope. (I don’t claim that country-level inequality is the only sort that matters; it may well not be the sort that matters most. But it’s one sort that matters, and it has the dubious advantage of being somewhat measurable because relevant statistics are available.)
Some resources are approximately fixed in quantity for quite fundamental reasons. One example (whose scope happens to be that of a single country) is influence over lawmaking. In so far as these resources are tradeable for money (political influence isn’t formally, but is to a great extent in practice) inequality in money translates into inequality in access to these resources, which (because the total amount is fixed) more or less implies absolute poverty. So, e.g., most people have very little political influence. (Democracy can be thought of as a sort of UBI for political influence. Unfortunately it often doesn’t work very well for that purpose, e.g. because with first-past-the-post elections many people are in “safe” constituencies and their vote has negligible effect.)
For the avoidance of doubt, (1) the existence of adverse consequences of (some) inequality does not imply that measures to reduce inequality are always a good idea (because they may themselves have other adverse consequences) and (2) the existence of such adverse consequences doesn’t mean that any particular measure of inequality exactly tracks their severity. (In particular, Jacob may well be right that something like his “logini coefficient” tracks them better than the Gini coefficient does.)
So, what decisions should one make based on a dispersion measure? Probably none, directly. Rather, if you see that (say) your Gini coefficient is high, or that it’s increasing, that should be a cue to look for the sort of effects described above and see whether they’re bad or whether they’re getting worse. What to do if so will vary from case to case.
You’re getting at some interesting things which mostly support my argument against Gini, not necessarily for Logini. I agree that what we should be doing is minimizing those social ills you mentioned, not trying to move numbers on a chart. Unfortunately, making people more secure, providing cheap housing for poor people and ensuring that democracy is more representative would have no impact on Gini which to a large extent is driven by how much the top 1% makes.
I think the top 1% basically have their own economy. They make their money from capital gains and global corporations, they spend their money on luxury goods and zero sum things like Park Avenue penthouses. Besides taxes, most things that would affect normal people (minimum wages, public services, housing markets, employment shifts) don’t affect the 1% and don’t really move Gini.
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.
Rather seldom, I’d think. I would expect serious attempts to measure when one is worse than the other to fall foul of the usual problems around interpersonal utility comparisons etc., and if any econometric measure has been dealt with rigorously enough to make those problems go away, I haven’t heard of it.
I think one can at least make a reasonable argument for why inequality is (sometimes) bad; then figuring out whether any given instance of it is worse than any given instance of absolute poverty “only” has those usual problems to contend with. Inequality is (sometimes) bad for at least the following reasons.
Empirically, even after reasonable attempts to avoid confounding with absolute poverty, inequality at the country level has been found to correlate with all manner of social ills. See e.g. Pickett & Wilkinson, The Spirit Level. (I make no claim that everything in that book is right, but it makes a reasonable argument.)
Human brains (non-human brains too, I think) operate by comparisons. Someone who feels worse off than others around them will almost always feel bad as a result. Greater inequality means more people feeling more worse-off than others. This doesn’t operate only at the country level, but within-country comparisons tend to be more salient than cross-country ones because of e.g. media with national scope. (I don’t claim that country-level inequality is the only sort that matters; it may well not be the sort that matters most. But it’s one sort that matters, and it has the dubious advantage of being somewhat measurable because relevant statistics are available.)
Some resources are approximately fixed in quantity for quite fundamental reasons. One example (whose scope happens to be that of a single country) is influence over lawmaking. In so far as these resources are tradeable for money (political influence isn’t formally, but is to a great extent in practice) inequality in money translates into inequality in access to these resources, which (because the total amount is fixed) more or less implies absolute poverty. So, e.g., most people have very little political influence. (Democracy can be thought of as a sort of UBI for political influence. Unfortunately it often doesn’t work very well for that purpose, e.g. because with first-past-the-post elections many people are in “safe” constituencies and their vote has negligible effect.)
For the avoidance of doubt, (1) the existence of adverse consequences of (some) inequality does not imply that measures to reduce inequality are always a good idea (because they may themselves have other adverse consequences) and (2) the existence of such adverse consequences doesn’t mean that any particular measure of inequality exactly tracks their severity. (In particular, Jacob may well be right that something like his “logini coefficient” tracks them better than the Gini coefficient does.)
So, what decisions should one make based on a dispersion measure? Probably none, directly. Rather, if you see that (say) your Gini coefficient is high, or that it’s increasing, that should be a cue to look for the sort of effects described above and see whether they’re bad or whether they’re getting worse. What to do if so will vary from case to case.
You’re getting at some interesting things which mostly support my argument against Gini, not necessarily for Logini. I agree that what we should be doing is minimizing those social ills you mentioned, not trying to move numbers on a chart. Unfortunately, making people more secure, providing cheap housing for poor people and ensuring that democracy is more representative would have no impact on Gini which to a large extent is driven by how much the top 1% makes.
I think the top 1% basically have their own economy. They make their money from capital gains and global corporations, they spend their money on luxury goods and zero sum things like Park Avenue penthouses. Besides taxes, most things that would affect normal people (minimum wages, public services, housing markets, employment shifts) don’t affect the 1% and don’t really move Gini.
Oh, the use is simple: convince other people of the need to forcefully redistribute wealth.
Cheap cynicism is cheap.
Cheap and surprisingly useful—I’ll take two!
:-P