New NBER paper Beyond GDP? Welfare across Countries and Time by Charles Jones and Peter Klenow looks interesting.  They propose a new summary statistic for a nation’s flows of welfare that combines data on consumption, leisure, inequality, and mortality.  They do not include welfare gains from ecosystem services.

The authors explain their index:

… High hours worked per capita and a high investment rate are well known to deliver high GDP, other things being equal. But these strategies have associated costs that are not reflected in GDP. Our welfare measure values the high GDP but adjusts for the lower leisure and lower consumption share to produce a more accurate picture of living standards.

This paper builds on a large collection of related work. … We try to incorporate life expectancy and inequality and make comparisons across countries as well as over time, but we do not attempt to account for urban disamenities. The World Bank’s Human Development Index combines income, life expectancy, and literacy into a single number, first putting each variable on a scale from zero to one and then averaging. In comparison, we combine different ingredients (consumption rather than income, leisure rather than literacy, plus inequality) using a utility function to arrive at a consumption equivalent welfare measure that can be compared across time for a given country as well as across countries. Fleurbaey (2009) contains a more comprehensive review of attempts at constructing measures of social welfare.

They discover that while their index is highly correlated with GDP/capita (.95) there are still important differences among countries using this new measure.  They also find welfare growth is less correlated with GDP (0.82), and exhibits even larger differences among individual countries.  According to their index, welfare is being substantially increased by recent increases in life expectancy worldwide (with the major exception of sub-Saharan Africa).

Using this index many developing countries are poorer than GDP/capita alone suggests due to inequality, poor health and lack of leisure.