Abstract

Accounting for Life’s Ups and Downs: Using High-Frequency Experience Sampling Data to Explain Longitudinal Variability in Happiness
Presenter: Nick Powdthavee (Warwick Business School)

Despite significant advancements in the science of well-being over the last forty years, there has been virtually zero investigation into the determinants of the longitudinal variability of human feelings. Using a large sample of user-week variation in real-time happiness (N=248,678), we estimate one of the literature’s first happiness variability regression equations. Among our primary findings, we show that the rich are not only happier than the poor on average; they also experience significantly more emotional stability over time. Compared to being single, married people report significantly higher levels of both happiness mean and variance. Although parents and non-parents exhibit similar levels of average weekly happiness, having children, especially for women, generally comes with a substantially greater fluctuation in experienced well-being. While more research on causality is needed, we argue based on our findings that people may suffer less from affective forecasting error if they can focus more on the potential consequences of their choices on the happiness variability in the future rather than the mean.