In Ben’s interesting post from Thursday he mentions a project underway by some of his LSE colleagues to apply Amartya Sen’s capabilities framework to inequality in Britain. Here in the United States the Social Science Research Council has undertaken the “American Human Development Project,” adopting the United Nation’s Human Development Index (which is itself inspired by the capability framework) to the United States in order to provide a more detailed portrait of wellbeing across states, racial groups, and gender. Like the UN’s HD Index, the SSRC’s project focuses on three dimensions of wellbeing: education, income, and health.
In their eye-catching report “A Century Apart,” they compare the Human Development score by racial group and state that:
“Asian Americans in New Jersey are the group with the highest American HD Index scores. They currently experience levels of well-being that, if current trends continue, the country as a whole will reach in about fifty years. At the other end of the spectrum, Native Americans in South Dakota lag more than a half-century behind the rest of the nation in terms of health, education, and income, the three areas of human development that the American HD Index measures.”
To be sure, this is an interesting and compelling way of repackaging widely available indicators, and distilling them into a report that a journalist or a policymaker could pick up and understand.
There are a few things about the SSRC’s project, and how they display their results that I really like:
- They have assembled some of the most relevant indicators for each of their dimensions of wellbeing from a few widely available datasets and have put them into two easy to use spreadsheets broken out by state and congressional districts. All of the indicators could be cobbled together by a researcher willing to spend a few days doing so, but they are much more accessible here. You can pull together scatterplots, for example, showing the relationship between mortality for different racial groups across states, or the relationship between voter turnout and poverty. This is definitely one of my new favorite quick data resources.
- They do a lot to emphasize the importance of geography in their reports, showing for example how much variation there is within racial groups across states. For example, Latinos in New Jersey earn $7,000 more per year than Latinos in Alabama and live 11 years more on average. (Of course they don’t attempt to decompose geographic differences into their contextual and compositional components)
- They include historical time series going back to the 1960s, so it’s possible to use some of their data to look at convergences and divergences in different kinds of disparities.
- They include comparable data for five racial/ethnic groups (white, black, Hispanic, Asian, and Native American) whereas most data sources only look at the first three. That’s an obvious shortcoming, because despite comprising only six percent of the population, the latter two groups are very important to understanding the health of the population in certain areas of the country, and could be informative about some of the mechanisms that mediate differences in outcomes across the life-course.
If I have one quibble with the SSRC project, it is the heavy reliance on the HD measure, without much justification. Technical discussion of this measure, and its interpretation, is shunted to a more technical appendix. Even after reviewing the appendix, I feel that not enough is done to explain what motivates the weighting of different indicators. Critiques of the UN HD Index have rightly pointed out, there is no obvious way to weight the value of life expectancy versus income, even once you have adopted a capabilities framework. Sen has actually stressed in his writings that the evaluation of capabilities requires some mode of public deliberation, and that the same ordering of capabilities is not likely to be endorsed by all cultures at all times. This is a notable contrast to the work of Ben’s colleagues at LSE (I recommend reading their paper), who do much more to discuss the need for public deliberation.
All in all, this is a project well worth following. I think it will be interesting to see whether these kinds of statistics get the attention of policymakers in state and federal government. This should be a helpful way to come up with illuminating descriptive comparisons, but it is not a substitute for thinking carefully and critically about each of the indicators separately and for rigorously examining what policies are leading to these persistent gaps.