Modelling a Human Well-Being Indicator

This paper analyses the Happy Planet Index (HPI) as a new human well-being indicator, and its deterministic relationships with a range of macroeconomic, social, and political factors. In addition, this paper identifies any lead-lag relationships between the variables studied. This study employs a panel data comprising 25 OECD countries over a period of 16 years from 1994 to 2009. The deterministic relationships are modelled with Pooled Ordinary Least Square (POLS) regressions, and any lead-lag relationship is identified by applying Granger causality tests to the panel dataset. This study finds that conventional macroeconomic indicators such as GDP per capita, unemployment rate, and inflation rate are statistically significant in explaining HPI, though the relationship is negative. Overall, the selected variables are successful in explaining HPI. The study also finds significant causal relationships between HPI and some of the variables. This paper contributes to the literature by studying a relatively new human well-being variable, and by using a panel dataset which significantly increases the power of the tests.