Monday, July 20, 2009

Neighborhood Tipping Points: New Evidence

Bill Easterly in his blog previews one of his latest studies, which delves into the issue of racial composition of communities cited by Malcolm Gladwell in his book The Tipping Point in referrence to the work of Nobel Laureate Thomas Schelling to describe the phenomenon of “white flight” in racially integrated neighborhoods. For those of you who would demand a demonstration of how this famous model works, this video prepared by Tim Harford, a member of the Financial Times editorial board, should do the trick.

The key insight is that peer effects, aka herd mentality affects individuals who may not necessarily agree strongly with the views of those whose behaviour they are mimicking. So, in the case of neighborhoods with mixed racial composition, the first to leave under Schelling’s model are the ones with the strongest preference for racial homogeneity, followed by those with weaker preferences. This approaches a tipping point and leads to an equilibrium in which integrated neighborhoods become segregated.

The model would have some fascinating applications in areas of interest to human development specialists such as improving educational attainments. Given the same peer effects, a growth in the number of individuals with an above average level of educational attainment would lead to a tipping point for the broader population in its preference for higher education.

Easterly’s work has been quite contrarian in a number of ways. He has argued that the implementation of IMF stabilisation policy in developing states has not materially improved their situation (a case of “policy does not matter”) and that development assistance is actually counterproductive (a form of “dutch disease”) as exemplified here.

His work in this area is no exception. His findings are that homogenous “white” neighborhoods in the US are more unstable than mixed ones (there is a higher level of movement in and out of these neighborhoods). In other words, there is no evidence to back up the tipping point concept. He serves these findings with a caveat though: they are based on single period observations (multiple periods might produce different results).

The punchline that he provides is worth quoting:

Think twice and check for evidence before you accept popular stories like the Tipping Point.
That is good advice for those who are working in public policy in any area.

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