The Ambrosini Critique

Mike D commented on this post:

Let’s think about two axes here. On the x axis, put altruism (the weight my assessment of your utility has in my utility function) and on the y axis, put respect (if I assess your situation using my utility function, respect = 0, if I assess your situation using what I think is your utility function, put respect =1, and interpolate between these two).

It seems obvious why altruism decreases with distance/dissimilarity. I would submit that respect is more subtle.
1) Proximity decreases respect, as I may suffer alleged externalities (real, pecuniary, or psychic) from your choices, so I have a selfish motive to override your preferences.
2) Proximity also increases respect, because your internal emotional life becomes more real and vivid to me, instead of a highly abstracted model.

So the utility function looks like this:

where big U is total utility for the individual, little u is his Robinson Crusoe utility, little v is the other person’s utility, x is the individual’s consumption and y is the other person’s consumption. According to Mike D, the parameter’s of that utility function behave like this:

There has to be some experiment, natural or otherwise, that would let us estimate these parameters and see how they vary with social distance.

An implication of Wilkinson’s theory is that intergenerational mobility should decrease over time. Wilkinson claims intergenerational mobility has decreased. It hasn’t (estimates from Lee and Salon 2009):

The “intergenerational elasticity” (the percentage kids’ incomes raise for every percentage increase in parents’ income) has stayed about the same over the last couple of decades. Other studies get contradictory answers and few find a statistically significant trend.

Which suggests the answer to the question posed in the title is: none of the above.

UPDATE: On rewatching, I see that Wilkenson isn’t trying to explain increasing inequality as I first thought, he’s trying to explain non-existent decreases in mobility.

esr speaks it:

All data, including primary un-”corrected” datasets, must be available for auditing by third parties. All modeling code must be published. The assumptions made in data reduction and smoothing must be an explicitly documented part of the work product.

These requirements would kill off AGW alarmism as surely as a bullet through the head.

Transparency would kill off AGW denialism, too.

Work with me here. In normal times, say 2004 through 2007, suppose 10% of the working population are looking for jobs while still employed (do you know of a better estimate?). This means about 13 to 14 million employed workers are “job seekers” in normal times.

“Quits” are voluntary separations from jobs and folks do that because they’re leaving the work force (e.g. retiring) or because they found another job. Now look at quit rates over the last couple of years:

Quits have declined by about 40% compared to normal times. From here, about 50% of quits are retirements. If the retirement rate has stayed the same, then quits due to job changes went from 1.1% to about 0.5%. This suggests the number of “job seekers” among the employed has gone down by at least half.

How many job seekers are there right now? Supposing all unemployed workers are “job seekers” then the total number is about 20 million people. In normal times, that number is about… 21 or 22 million people (unemployed plus 10% of the working population). By this measure, the job market now is less congested than usual!

Making the assumptions that I made above, I constructed a “job seekers” per job opening time series:

If you assume none of the currently employed workers are “job seekers” then the graph above looks like the one put up by EPI. If you assume 20% of the currently employed are “job seekers” then even the up-tick seen in the later part of the time series goes away.

Prof. Clark sits in the “what revolution?” camp among economic historians that try to date the industrial revolution. His data:

Why does this matter? Well, if there was no revolution, only evolution, to modern industrial society, you need an underlying evolutionary mechanism. Clark favors genes-based stories, but most other folks are more comfortable with culture-based stories. In either case, its hard to look at Clark’s data and pick a year before 1900 that would look like a revolution in efficiency.

In his latest post, he worries that his excellent series critiquing Libertarian Paternalism (start here) isn’t getting many comments.

If you’ve read a couple or all of these posts, leave a comment to let him know how great they are.

If not, drop whatever you’re doing and get reading.