Posted: 20 Feb 2011 06:54 PM PST
I’ve now had debates in the ML comment section with both Jason Hopper and Andrew Goldstein over the importance of inequality, specifically income inequality, as an economic issue and a development goal. Some ways in which that question can be posed are wholly subjective: for example, a researcher or policymaker can choose to value inequality in and of itself, irrespective of any effects. However, our discussions mainly settled on whether inequality per se affects health outcomes, and that is an objective and empirical question. Strikingly, it was not one that was covered in my development class, even though my professor (David Lam) does lots work on income inequality.
On his recommendation I just looked at Angus Deaton’s excellent review of the literature on the inequality-health link. Deaton is probably the greatest of the old-school observational micro-development researchers (he literally wrote the book on it), so there’s nobody else I’d rather trust to survey this kind of empirical work. After reading his paper I see the major issues with this field of research as the following.
1) We have to be extremely precise with our language here. When I claim that inequality does not directly impact health that is not the same as saying that a mean-preserving spread of the income distribution will leave health unchanged. Like most things we spend money on, health has diminishing returns, so transferring money from the rich to the poor will improve aggregate health. The statement that inequality is per se important for health is equivalent to saying that holding the income of a poor person constant, increasing the income of a rich person in their society will damage their health.
2) Following closely from #1, the preponderance of studies that do find negative effects from inequality do not control for individual income. Many are conducted at the country or state level, so they cannot even do so in principle. Controlling for average income does not accomplish this; that implies we’re looking at shifting income from poor to rich, which is a clear negative and an entirely different issue.
3) The choice of inequality measure matters. The Gini isn’t terrible but it fails some basic ethical tests; many studies use measures that have even deeper flaws. If there’s interest I might provide a non-technical summary of different inequality measures in a future post.
4) Data quality is a serious problem for much of this work. The few studies that do find a meaningful result tend to break down when re-analyzed with better data.
The take-home message Deaton leaves us in his great one-page summary (Section 4, highly recommended) with is that as it currently stands there’s no compelling evidence to suggest a link between inequality and health outcomes – bearing in mind point #1 above; in sharp contrast the level of individual income matters a great deal, especially for the very poor. That’s not to say a relationship isn’t there, but no existing research has proven its existence.
|You are subscribed to email updates from MethodLogical |
To stop receiving these emails, you may unsubscribe now.
|Email delivery powered by Google|
|Google Inc., 20 West Kinzie, Chicago IL USA 60610|