Well-Being and Ill-Being: A Bivariate Panel Data Analysis

The aim of this paper is to estimate in a multivariate context the factors associated with wellbeing and ill-being without making the assumptions that they are opposite ends of the same continuum, and that the factors uniformly affect both well-being and ill-being. Using the first five waves of panel data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, we jointly model positive and negative well-being in a two-equation dynamic panel data model. We found that while past ill-being had significant effect on current wellbeing there was no support for a reverse relationship (i.e. lagged effect of well-being on current ill-being). In addition, we also found support for asymmetry in how certain factors affect well-being and ill-being. The implication of the findings in this paper for the happiness literature is that for future empirical work, it would perhaps more prudent to begin with the notion that well-being and ill-being are distinct dimensions, that the unobservables that affect well-being and ill-being are correlated, and to specify econometric models that allow for these concepts to be reflected.