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This paper describes a fundamental and empirically conspicuous probleminherent to surveys of human feelings and opinions in which subjectiveresponses are elicited on numerical scales. The paper also proposes a solution.The problem is a tendency by some individuals -- particularly those with lowlevels of education -- to simplify the response scale by considering only asubset of possible responses such as the lowest, middle, and highest. Inprinciple, this ``focal value rounding'' (FVR) behavior renders invalid eventhe weak ordinality assumption often used in analysis of such data. With``happiness'' or life satisfaction data as an example, descriptive methods anda multinomial logit model both show that the effect is large and that educationand, to a lesser extent, income level are predictors of FVR behavior.  A model simultaneously accounting for the underlying wellbeing and for thedegree of FVR is able to estimate the latent subjective wellbeing, i.e.~thecounterfactual full-scale responses for all respondents, the biases associatedwith traditional estimates, and the fraction of respondents who exhibit FVR.Addressing this problem helps to resolve a longstanding puzzle in the lifesatisfaction literature, namely that the returns to education, after adjustingfor income, appear to be small or negative. Due to the same econometricproblem, the marginal utility of income in a subjective wellbeing sense hasbeen consistently underestimated.

The econometrics of happiness: Are we underestimating the returns to education and income?