Can “happiness data” help evaluate economic policies?

“Happiness data” may help assess the welfare effects of a new labor market policy, like a change in benefit generosity

University of Auckland, New Zealand

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Elevator pitch

Imagine a government confronted with a controversial policy question, like whether it should cut the level of unemployment benefits. Will social welfare rise as a result? Will some groups be winners and other groups be losers? Will the welfare gap between the employed and unemployed increase? “Happiness data” offer a new way to make these kinds of evaluations. These data allow us to track the well-being of the whole population, and also sub-groups like the employed and unemployed people, and correlate the results with relevant policy changes.

Average life satisfaction of the employed
                        and unemployed in Europe, 1975–2009

Key findings

Pros

By measuring the welfare effects of a policy change directly, “happiness data” may lessen reliance on theories; they can capture all of the costs and benefits of a policy that otherwise may be hard to determine and aggregate.

“Happiness data” can provide estimates of the welfare effects of a policy on different sub-groups.

“Happiness data” may offer a better way to estimate costs and benefits than “willingness-to-pay” surveys that are notoriously unreliable.

Cons

It is difficult to determine the best questions to pose to measure well-being accurately.

It is unclear whether people’s happiness scores can be compared as different groups may self-report the same level of well-being differently.

There is uncertainty over the short- versus long-term impact of shocks on happiness and some studies show strong adaptation to income.

Author's main message

Estimating the welfare effects of a new policy, like a cut in unemployment benefits, is difficult. Economists lack dependable methods to measure all of the costs and benefits of potential policy changes. As a result, politicians often end up relying on their own discretion when making key decisions. “Happiness data” can be used to measure the overall welfare effect of a change in benefits directly, considering whole populations as well as relevant sub-groups. This provides additional, comprehensive data that can be used when evaluating potential policy options.

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