Pfuffnick’s Nobel Economics Prize triumph hailed by many
LONDON — The surprise choice of first-year graduate student Quintus Pfuffnick for the Nobel Prize in Economics drew praise from much of the world Friday even as many pointed out the youthful economist has not yet published anything in scholarly journals.
The new PhD candidate was hailed for his willingness to tackle difficult problems, his commitment to improving the economic system, and his goal of bringing efficiency and equality into harmony.
Professor Paul Krugman of Princeton, who won the prize in 2008, said Pfuffnick’s award shows great things are expected from him in the coming years.
“In a way, it’s an award coming near the beginning of the first year in grad school of a relatively young economist that anticipates an even greater contribution towards making our economy a better place for all,” he said. “It is an award that speaks to the promise of Mr Pfuffnick’s message of hope.”
He said the prize is a “wonderful recognition of Pfuffnick’s essay in his grad school application.”
The Daily Mail writes,
More than 100 top doctors have signed an open letter to U.S. senators to counter ‘lies’ about the National Health Service.
…The doctors, including former president of the Royal College of Physicians Sir George Alberti and Professor Alan Maryon-Davis, president of the UK Faculty of Public Health, and patient groups, used their letter to point out that life expectancy is longer in the UK than the U.S. – showing, they claimed, it is a better system.
Pointing to a relatively lower American life expectancy as proof of a flawed health care system is a false argument. “The problem with such international comparisons, Greg Mankiw explains, “is that there are a lot of differences among nations beyond their health systems. To make comparisons in health outcomes, you need to control for other variables. Without such controls, the simple correlations have little meaning.”
The WHO judged a country’s quality of health on life expectancy. But that’s a lousy measure of a health-care system. Many things that cause premature death have nothing do with medical care. We have far more fatal transportation accidents than other countries. That’s not a health-care problem. Similarly, our homicide rate is 10 times higher than in the U.K., eight times higher than in France, and five times greater than in Canada. When you adjust for these “fatal injury” rates, U.S. life expectancy is actually higher than in nearly every other industrialized nation.
National differences in life expectancies are a highly imperfect indicator of the effectiveness of health delivery systems. For example, life styles are important contributors to health, and the US fares poorly on many life style indicators, such as incidence of overweight and obese men, women, and teenagers. To get around such problems, some analysts compare not life expectancies but survival rates from different diseases. The US health system tends to look pretty good on these comparisons.
A study published in Lancet Oncology in 2007 calculates cancer survival rates for both men and women in the United States, the United Kingdom, and the European Union as a whole. The study claims that the most important determinants of cancer survival are early diagnosis, early treatment, and access to the best drugs, and that the United States does very well on all three criteria. Early diagnosis helps survival, but it may also distort the comparisons of five or even ten-year survival rates. In any case, the calculated five-year survival rates are much better in the US: they are about 65% for both men and women, while they are much lower in the other countries, especially for men. These apparent advantages in cancer survival rates are large enough to be worth a lot to persons having access to the American health system.
Several measures of the quality of life also favor the US. For example, hip and knee replacements, and cataract surgery, are far more readily available in the US than in Europe.
For even more on this, I highly recommend reading Greg Mankiw’s New York Times Op-Ed ‘Beyond Those Health Care Numbers.’
…there is our inefficient and inequitable system of tax-advantaged, employer-based health insurance. While the federal tax code promotes overspending by making the majority unaware of the true cost of their insurance and care, the code is grossly unfair to the self-employed, small businesses, workers who stick with a bad job because they need the coverage, and workers who lose their jobs after getting sick.
This employer-based system arose not by thoughtful design but as an unforeseen result of price controls during World War II and subsequent tax policy. How this developed and persisted despite its unfairness and maladaptive consequences is a powerful illustration of the law of unintended consequences and the fact that government can take six decades or more to fix its obvious mistakes.
HT: Greg Mankiw
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).
Professor Greg Mankiw writes,
The NY Times Economix blog offers us the above graph, showing that kids from higher income families get higher average SAT scores.
Of course! But so what? This fact tells us nothing about the causal impact of income on test scores. (Economix does not advance a causal interpretation, but nor does it warn readers against it.)
This graph is a good example of omitted variable bias, a statistical issue discussed in Chapter 2 of my favorite textbook. The key omitted variable here is parents’ IQ. Smart parents make more money and pass those good genes on to their offspring.
Suppose we were to graph average SAT scores by the number of bathrooms a student has in his or her family home. That curve would also likely slope upward. (After all, people with more money buy larger homes with more bathrooms.) But it would be a mistake to conclude that installing an extra toilet raises yours kids’ SAT scores.
It would be interesting to see the above graph reproduced for adopted children only. I bet that the curve would be a lot flatter.
Click here to read Greg Mankiw’s argument in favor of raising the gas tax. When someone like him argues in favor of any increased tax, it is especially worth a read.
Greg Mankiw on ‘How to Write Well‘:
When I was CEA chair, I sent the following guidelines to my staff as they started drafting the Economic Report of the President. A friend recently emailed me a copy, and I thought I would share them with blog readers. They are good rules of thumb, especially for economists writing for a general audience.
The IMF’s Olivier Blanchard writes the following:
The historical evidence is worrisome, however. The IMF’s forthcoming World Economic Outlook presents evidence from 88 banking crises over the past four decades in a wide range of countries. While there is large variation across countries, the conclusion is that, on average, output does not go back to its old trend path, but remains permanently below it. The possible good news is that the trend itself appears to be unaffected: on average, crises permanently decrease the level of output, but not its growth rate. So, if past is prologue, the world economy likely will return to its past growth rate. But, especially in advanced countries, the period of above-average growth, characteristic of normal recoveries, may be short-lived or nonexistent.