A happiness Kuznets curve? Using model-based cluster analysis to group countries based on happiness, development, income, and carbon emissions

Abstract

This exploratory study uses model-based cluster analysis to group sixty-one countries based on statistical similarities in terms of happiness, development, income, and carbon emissions. Model-based cluster analysis is appropriate for an initial identification of a pattern that is worthy of further investigation. A key finding is that there may be a Kuznets curve for happiness. The Kuznets curve graphs the proposition that, as an economy develops, economic inequality first increases and then decreases. Similarly, the authors find that clusters of countries at the extremes of the lowest and highest average levels of development and income have the highest self-reported levels of happiness. Clusters of countries in the middle of the development and income spectrum have the comparatively lowest average levels of happiness. Further, carbon emissions are not perfectly associated with happiness. For example, between two clusters with the highest average levels of development, income, and happiness there is a 43 % difference in carbon emissions. A highly developed cluster has roughly the same mean carbon emissions as a cluster with 83 % less income, and the least developed cluster has 93 % of the happiness as the most developed cluster yet 86 % less carbon emissions. Despite limitations of both data and methodology, the overall pattern—that there may be a happiness Kuznets curve and that development, income, and carbon emissions are not associated lockstep with happiness—contributes to the literature on decoupling development from growth in emissions.