Month: April 2015
Why the world is getting weirder (and will get weirder yet)
It used to be that airliners broke up in the sky because of small cracks in the window frames. So we fixed that. It used to be that aircraft crashed because of outward opening doors. So we fixed that. Aircraft used to fall out of the sky from urine corrosion, so we fixed that with encapsulated plastic lavatories. The list goes on and on. And we fixed them all.
So what are we left with?
Sadly, we all know the answer to that question.
…And so, with more rules we have solved most of the problems in the world. That just leaves the weird events left like disappearing 777’s, freak storms and ISIS. It used to be that even minor storms would be a problem but we have building codes now (rules). Free of rules, we’d probably have dealt with ISIS by now too.
Ultimately, this is why the world is getting weirder, and will continue to do so. Now with global media you get to hear about it all.
That is from a very interesting mini-essay by Steve Coast, hat tip goes to The Browser.
How universal are rates of social mobility across time and societies?
Gary Solon, in a new survey paper, takes issue with the earlier results of Greg Clark, which had suggested social mobility was roughly constant across a wide spectrum of cases. Solon writes:
…the results reported by Clark do not reflect a universal law of social mobility. Quite to the contrary, other studies based on group-average data, even surnames data, frequently produce intergenerational coefficient estimates much smaller than Clark’s.
A second testable prediction of Clark’s hypothesis…is that instrumental variables (IV) estimation of the regression of son’s log earnings on father’s log earnings should yield a coefficient estimate in the 0.7-0.8 range if father’s long earnings are instrumented with grandfather’s log earnings. When Lindahl et al, estimated that regression with their data from Malmo, Sweden, the IV coefficient estimate was 0.15, considerably higher than their ordinary least squares (OLS) estimate of 0.303. They obtained a remarkably similar comparison of IV and OLS estimates when they used years of education instead of log earnings as the status measure. The pattern of IV estimates exceeding OLS estimates is consistent with Clark’s general story about measurement error in particular indicators as proxies for social status. It is equally consistent with all the alternative stories listed in section II for why grandparental status may not be “excludable” from a multigenerational regression. What the results are not consistent with is a universal law of social mobility in which the intergenerational coefficient is always 0.7 or more…
A third testable prediction…is that using an omnibus index that combines multiple indicators of social status should make the intergenerational coefficient estimate “much closer to that of the underlying latent variable.” [But]…The resulting estimate was not “much closer” to the 0.7-0.8 range.
In sum, when Clark’s hypothesis is subjected to empirical tests, it does not fare so well.
Here is an ungated version.