Krugman writes: “Belgium is politically weak because of the linguistic divide; Italy is politically weak because it’s Italy. If these countries can run up debts of more than 100 percent of GDP without being destroyed by bond vigilantes, so can we.”
I would interpret this evidence differently. A high deficit often is an unfavorable symptom of bad politics, even if you think the high deficit is economically OK on its own terms. It’s a sign that you have dysfunctional institutions and decision-making procedures, as indeed they do in Belgium and Italy. I believe that the not-always-swift American voter in fact understands high deficits — correctly — in this light. They don’t hold theories about “crowding out,” rather they sense something in the house must be rotten. And so they rail against deficits, as do some of their elected representatives. It’s a more justified reaction than the pure economics alone can illuminate.
When water regularly overflows from your toilet, you want the toilet fixed, whether or not the water is doing harm.
Chris Blattman writes:
Using a high-speed camera that photographed people flipping coins, the three researchers determined that a coin is more likely to land facing the same side on which it started. If tails is facing up when the coin is perched on your thumb, it is more likely to land tails up.
How much more likely? At least 51 percent of the time, the researchers claim, and possibly as much as 55 percent to 60 percent — depending on the flipping motion of the individual.
The original research is here.
Chance a U.S. household that owns a Prius also owns an SUV: 1 in 3 (Harper’s Index, October issue).
From Marginal Revolution:
Economix posted a graph showing a strong positive correlation between SAT score and parental income. Greg Mankiw pointed out that the effect is unlikely to be purely causal because there may be an omitted variable bias, IQ for example. Paul Krugman and Matt Yglesias both attack Mankiw and point to graphs showing that income matters for college completion and enrollment, respectively, holding various achievement scores constant. Brad DeLong crunches the numbers on IQ and income correlation to estimate that half the effect is due to IQ and half to something else.
All this is good but none if it gets at the heart of the matter because there are a lot of way that heredity/genes could explain the income/education correlation; IQ is only one possible mechanism, personality (e.g. conscientiousness) is another possibility.
The type of evidence that we need to resolve this question is adoption studies. Fortunately, such studies have been done and indeed I have presented the data before in my post Nature, Nurture and Income. Let’s do so again.
The graph below is from What Happens When We Randomly Assign Children to Families?, by Bruce Sacerdote. Holt’s International Children’s Services places children, primarily Koreans, with families in the United States. Holt has an interesting proviso to their adoption contract, conditional on being accepted into the program, children are randomly assigned. Sacerdote has collected data from children who were adopted between 1970-1980, and thus who today are in their mid 20′s or 30′s, and their adoptive parents.
The graph shows how parent income at the time of adoption relates to child income for the adopted and “biological” (non-adopted) children. The income of biological children increases strongly with parental income but the income of adoptive children is flat in parent income. What does this mean?
The graph does not say that adopted children necessarily have low income. On the contrary, some have high and some have low income and the same is true of biological children. What the graph says is that higher parental income predicts higher child income but only for biological children and not for adoptees.
Now what about education? Sacerdote looks at that as well. He doesn’t have a child SAT-score, parent-income correlation but he does find:
Having a college educated mother increases an adoptee’s probability of graduating from college by 7 percentage points, but raises a biological child’s probability of graduating from college by 26 percentage points.
The effect for father’s years of education is even larger; about a ten times larger effect on biological children than on adoptees. Similarly, parent income has a negligible effect, small and not statistically significant, on an adoptee completing college but an 8 times larger and statistically significant effect on a biological child completing college (Table 4, column 3).