To Evaluate the Age-Happiness Relationship, Look Beyond Statistical Significance

The persistent contentiousness of research on the age-happiness relationship is puzzling; it should be possible to gain clarity and consensus about how to address the question effectively. In this paper I show that a key reason for the lack of clarity consists of overreliance on statistical significance as a means of evaluating empirical results. The statistical significance of a quadratic specification (age plus age-squared) is often taken as evidence in support of a 'u-shaped' relationship between age and happiness. But statistical significance on its own cannot tell us whether the age-happiness relationship is 'u-shaped' (nor indeed whether it takes any other shape). On the contrary, statistical significance can mislead us about it: a set of quadratic age coefficients can be 'significant' even when the relationship is obviously characterised by a different shape. When we have clarity on how to construct the analysis so that we can 'see' the underlying patterns in the data, it becomes obvious that the age-happiness relationship in European countries commonly shows other patterns; a u-shape is evident only in a minority of countries.