Abstract

We investigate a novel approach to reduce measurement error in subjective well-being (SWB) data. Using a between-subject design, half of the subjects are asked to promise to answer the survey questions truthfully to make them commit to truth-telling. We find a statistically significant difference between mean stated well-being between the two samples (with and without a promise). People are consistently found to exaggerate their happiness and for several different aspects of life, without a promise. We then investigate to what extent the differences in stated well-being also affect the inference from regressions models on the determinants of SWB. The effect on the covariates are only weakly statistically significant and only for a few variables, if we compare the samples with and without the promise. Thus, this means that the policy implications based on an SWB study only marginally depends on whether we include a truth-telling question or not.

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