Using Spatial Factor Analysis to Measure Human Development

In this paper, we propose a Bayesian factor analysis model with the purpose of serving as an alternate approach to calculating the UNDP's Human Development Index, as well as providing a general methodology which can be used to augment existing indices or build new ones. In addition to addressing several potential issues of the official HDI, we also estimate an alternative “green HDI” index by adding a new environmental variable, and build a novel MDG index as an example of constructing a new index with a more complex variable structure. Under our methodology, we find the “living standard” dimension provides a greater proportional contribution to human development than it is assigned by the official HDI while the “longevity” dimension provides a lower proportional contribution. The results also show considerable levels of general disagreement when compared to the ranks of the official HDI. We show that incorporating an environmental variable increases the amount of disagreement between model based ranks and the official HDI, but decreases the amount of uncertainty associated with model ranks. In addition, we report the sensitivity of our methods to the choice of functional form and data imputation procedures