Clusters of Attributes and Well-Being in the US.

Using ARIMA models and entropy, the dynamic evolution of several functions of aggregate income and other attributes of well-being is analyzed for statistical "similarity" in order to determine potentially distinct dimensions in multidimensional analysis of welfare and quality of life in the US. The entropy metric compares entire distributions and is more general than principal components and other correlation-based techniques for clustering. To help macroeconomic policy makers, we compare the distribution of several composite measures of well-being, including income, with the distribution of some common measures of aggregate income over the period 1915-1995.