Oswald and Wu obtained subjective well-being data for over 1.3 million US citizens using the United States Behavioural Risk Factor Surveillance System. This allowed them to arrive at average well-being or 'happiness' estimates for the different states in the US. They then compared these estimates with quality-of-life data published by Stuart Gabriel in 2003. He and his colleagues looked at about 25 factors, including weather, crime, and commuting time. Whereas a magazine might give these factors equal weighting and calculate a state's desirability by summing its scores across the 25 factors, Gabriel's team used average house prices and wages to ascertain the importance of each factor to potential residents. If a state's house prices and wages remained high despite a wet climate, for example, this would suggest that rain is less important than other factors. Crucially, the subjective data matched the economists' league table of states. People seem to be happier in those places that the economists have identified as having a high quality of life.
'The study's finding suggests that subjective well-being data contain genuine information about the quality of human lives,' the researchers concluded.
So, which states in the US were the most and least happy? Top of the happiness league were Louisiana and Hawaii. Bottom were Connecticut and New York. California didn't fare much better. Commenting on California and New York's dismal showing, Oswald said: 'Many people think these states would be marvellous places to live in. The problem is that if too many individuals think that way, they move into those states, and the resulting congestion and house prices make it a non-fulfilling prophecy.'
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AJ Oswald, & S Wu (2009). Objective confirmation of subjective measures of human well-being: Evidence from the USA. Science.
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