Pittsburgh and Rust Belt, Part II

Recently constructed housing in Cleveland.  Source: Cleveland Foundation.

Not long after I wrote my last post, suggesting that Pittsburgh’s renaissance is not exactly replicable for the rest of the Rust Belt, I found a study recently completed by the Cleveland office of the Federal Reserve that might validate my thoughts.  Economist Daniel Hartley of the Fed compared socio-demographic data from 1970 and 2006 for four generally-accepted Rust Belt cities — Buffalo, Cleveland, Detroit and Pittsburgh.  In the study, Hartley suggests that neighborhood decline has much to do with proximity to adjacent low-income areas:

Recent research on population and income dynamics in four Rust-Belt cities shows that neighborhoods with the lowest housing prices are the ones that experience the steepest declines in population, but that income falls more sharply in neighborhoods with middle-tier house prices. These patterns are the reverse of a gentrification process. Both processes involve the borders of poor and rich neighborhoods. But where gentrification typically leads to an outward expansion of high-income neighborhoods into low-income neighborhoods, reverse gentrification involves an inward contraction of high-income neighborhoods, as the border areas become low-income.

 To which I agree.  Hartley demonstrates this in the table below:

Table 1. Comparison of Population, Income, House Prices, and Education in Cleveland, Detroit, Buffalo, and Pittsburgh in 1970 and 2006

Buffalo Pittsburgh
1970 2006 Change (%) 1970 2006 Change (%)
Population 462,783 257,758 −44 520,167 297,061 −43
Median household income (2009 dollars) 38,395 29,637 −23 37,477 33,818 −10
Median home value (2009 dollars) 71,477 64,702 −9 69,570 78,749 13
Fraction with college or higher degree 6.7 20.4 13.7 9.0 31.3 22.3
Cleveland Detroit
1970 2006 Change(%) 1970 2006 Change(%)
Population 751,046 406,427 −46 1,511,336 834,116 −45
Median household income (2009 dollars) 41,674 28,238 −32 46,438 30,184 −35
Median home value (2009 dollars) 92,826 92,477 0 86,108 93,966 9
Fraction with college or higher degree 4.4 12.0 7.6 6.2 11.3 5.1
Sources: U.S. Census Bureau, 1970 Census and 2006 American Community Survey.
But there are differences between the four cities, with Buffalo and Pittsburgh sharing some characteristics, and Cleveland and Detroit having similarities as well:

One area in which the cities have differed more is educational attainment—a measure of what economists call “human capital.” Cleveland and Detroit had the lowest proportion of residents over the age of 25 with a college degree or higher in 1970 (4 percent and 6 percent, respectively), and both experienced relatively small gains in this share by 2006, leaving both at about 12 percent. In contrast, Buffalo and Pittsburgh were slightly more highly educated in 1970 (7 percent and 9 percent, respectively) but are now much more highly educated (20 percent and 31 percent, respectively).

Hartley argues that higher educational attainment in Buffalo and Pittsburgh, combined with higher-income neighborhoods within the city, helped stem the spread of “reverse gentrification” in those two cities, despite similar economic challenges.

In my mind, however, there is a key element missing in the discussion of how low-income communities were created in each city — white flight and the implementation of de facto segregation policies in each city.  I argue that, while Buffalo and Pittsburgh have amenities that helped them to weather the economic collapse, neither had the same migration of African Americans that Cleveland or Detroit had, and neither employed the segregation tactics — blockbusting, redlining, Urban Renewal, racial steering, repressive policing policies, among others — that often defined the African American experience in large cities.

I’m a firm believer that the low-income African American neighborhoods of major cities are the result of intended and unintended policy decisions.  The cities that have less of that policy burden are better able to reverse their decline.  The cities that have more of that policy burden have a far greater hurdle to cross.

I’ll explore and define this more in future posts.

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