A study posted on Tim Taylors blog finds:
“To paint an accurate picture of how health care cost growth is affecting the finances of a typical American family, RAND Health researchers combined data from multiple sources to depict the effects of rising health care costs on a median income married couple with two children covered by employer-sponsored insurance. The analysis compared the family’s health care cost burden in 1999 with that incurred in 2009. The take-away message: Although family income grew throughout the decade, the financial benefits that the family might have realized were largely consumed by health care cost growth, leaving them with only $95 more per month than in 1999. Had health care costs tracked the rise in the Consumer Price Index, rather than outpacing it, an average American family would have had an additional $450 per month—more than $5,000 per year—to spend on other priorities.”
Full post can be found here.
Commenting on the mobility/inequality link, Jim Manzi writes:
But what about all the other potential reasons, beyond what their Gini Coefficient was in 1985, for varying levels of social mobility between countries as diverse as Japan, France, and New Zealand?
The most obvious example is just the size of the countries. It’s at least plausible that much bigger countries contain more variety. In fact, if you do something as simple as recreate the Great Gatsby Curve, but use the population of each country as the X-axis, you get a very strong a statistical relationship (log-linear R2 = .64). Big countries have higher IGE. Call it the Moby Dick Curve.
Alternatively, we might see that some countries tend to specialize more than others. As a practical example, part of the reason that a country like Finland can have so much equality and social mobility versus America might be that many more of the relatively poorer farmers who trade food for Finnish mobile phones live and reproduce in other countries. If so, then we might see that if we replace the X-axis with exports as a % of GDP, there could be another statistically significant relationship with IGE. Check (R2 = .48).
Full article here.