John M. Quigley, who died last week, was a pioneering economist who helped change the way we think about housing. He devised statistical models of housing quality and the risks inherent in mortgage-backed securities, documented the discrimination that restricted the housing choices of African-Americans, and wrote about the impact of housing wealth on consumption.
“Calibration is less optimistic about what your theory can accomplish because you’d only use it if you didn’t fully trust your entire model, meaning that you think your model is partly misspecified or incompletely specified, or if you trusted someone else’s model and data set more than your own. My recollection is that Bob Lucas and Ed Prescott were initially very enthusiastic about rational expectations econometrics. After all, it simply involved imposing on ourselves the same high standards we had criticized the Keynesians for failing to live up to. But after about five years of doing likelihood ratio tests on rational expectations models, I recall Bob Lucas and Ed Prescott both telling me that those tests were rejecting too many good models. The idea of calibration is to ignore some of the probabilistic implications of your model but to retain others. Somehow, calibration was intended as a balanced response to professing that your model, though not correct, is still worthy as a vehicle for quantitative policy analysis.”
Paul Krugman writes:
OK, several correspondents have weighed in on the story I’d heard about the economics department that abandoned econometrics because it was rejecting its models. It wasn’t quite as alleged, but close enough.
The department in question was the University of Minnesota. For those readers new to this discussion, “freshwater-saltwater” was a distinction originally due to Bob Hall, who noted that the economics departments that had rejected Keynes and anything reminiscent of Keynes were inland schools like Minnesota, Chicago, and Rochester, whereas the places that retained a belief in the usefulness of monetary and fiscal policy were places like MIT, Princeton, and Berkeley.
So the story as I now have it was that there was harsh conflict between the macroeconomic theorists at UMinn, especially Prescott, and the econometricians who had the nasty habit of showing that those models didn’t work. And for at least some period econometrics was dropped as a required course for the Ph.D. — I don’t know whether it has been restored.
The happiest countries and happiest U.S. states tend to have the highest suicide rates,… The happiest countries and happiest U.S. states tend to have the highest suicide rates,… States with people who are generally more satisfied with their lives tended to have higher suicide rates than those with lower average levels of life satisfaction.
The researchers then also tried to make their comparison between States even fairer and yet more homogeneous by adjusting for clear population differences between the states including age, gender, race, education, income, marital status and employment status. Even with these adjustments. This still produced a very strong correlation between happiness levels and suicide rates although some states shifted their positions slightly. Hawaii then ranks second in adjusted average life satisfaction but has the fifth highest suicide rate in the country.
“Discontented people in a happy place may feel particularly harshly treated by life. Those dark contrasts may in turn increase the risk of suicide. If humans are subject to mood swings, the lows of life may thus be most tolerable in an environment in which other humans are unhappy.”
“This result is consistent with other research that shows that people judge their well-being in comparison to others around them. These types of comparison effects have also been shown with regards to income, unemployment, crime, and obesity.” more
And my conclusion is: Don’t pretend to be happier that what you actually are. That may make those around you feel worse in comparison!