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Money doesn't buy happiness over the long term, the study found. The results apply to developed and developing countries worldwide, said study researcher Richard Easterlin, a professor of economics at the University of Southern California. 

 

"Happiness doesn't increase with the rate of economic growth even in less-developed countries or transitional countries," Easterlin told LiveScience. "We already know that to be true of developed countries, but now it's been extended to countries of lower levels of income."

 

Easterlin and his colleagues reported the results Dec. 13 in the journal Proceedings of the National Academy of Sciences.

 

Almost 40 years ago, Easterlin discovered a strange economic pattern in the United States: If you look at snapshot data, richer people are happier than poorer people, and wealthier countries have more satisfied populations than less well-off nations. But when you look at data collected over time, more income doesn't bring happiness.

 

"If you look across countries and compare happiness and GDP [gross domestic product] per capita, you find that the higher the country's income, the more likely it is to be happier," Easterlin said. "So the expectation based on point-in-time data is if income goes up, then happiness will go up. The paradox is, when you look at change over time, that doesn't happen." [US is Richest Nation, But Not Happiest]

 

The 'Easterlin paradox,' as it is known, has been the subject of much academic debate. The new study, Easterlin said, is the broadest finding about the paradox so far. The researchers gathered between 10 and 34 years of happiness data from 17 Latin American countries, 17 developed countries, 11 Eastern European countries transitioning from socialism to capitalism and nine-less developed countries. They found no relationship between economic growth and happiness in any case.

 

Even in a country like China, the researchers wrote, where per capita income has doubled in 10 years, happiness levels haven't budged. South Korea and Chile have shown similarly astronomical economic growth with no increase in satisfaction.

 

"With incomes rising so rapidly in these three different countries, it seems extraordinary that there are no surveys that register the marked improvement in subjective well-being that mainstream economists and policy makers worldwide would expect to find," the researchers wrote.

 

The paradox seems impossible on the surface, but there's good reason happiness and income could be linked in the short-term and not over many years, according to Easterlin. As people's incomes rise, he said, so do their aspirations. When incomes fall, he said, aspirations don't. No one wants to give up the standard of living they've grown accustomed to. So in the short term, an economic collapse is painful, while growth feels good.

 

But in the long run, Easterlin said, more wealth simply creates more want.

 

"The higher your income goes up the more your aspiration goes up," he said. "Over time, the change in aspirations negates the effect of changing income."

 

The results suggest that individuals and policy makers should focus on non-monetary factors, like health and family concerns, that influence happiness, Easterlin said.

 

"Economic growth may not be the way you get happier," he said. "There are other avenues that may produce more happiness."

 

Easterlin said he expects further controversy about his paradox — "Policy makers are generally very reluctant to accept this conclusion about economic growth," he said — and a counterargument came shortly after the paper's release. Writing for the New York Times' Freakonomics blog, University of Pennsylvania economist Justin Wolfers argued that the new study doesn't prove the Easterlin paradox exists.

 

"In putting together his dataset, he sort of picks and chooses what he wants to include," Wolfers told LiveScience. The surveys Easterlin and his colleagues analyzed asked questions about life satisfaction in different ways and can't be lumped together, Wolfers said.

 

"What he's got is noisy data," Wolfers said. "In noisy data, it can be hard to find a significant correlation, but that doesn't mean the result is zero."

 

 

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