2000115-Strengthening-Communities-with-Neighborhood-Data

350 Strengthening Communities with Neighborhood Data
experiencing fewer constraints on the housing market: the ethnic majority
and better-off households.
In the United States, the white flight theory has become the most influential
in explaining ethnic residential segregation. The theory explains
changes in ethnic composition through the “flight” of white inhabitants
when the share of black [or other minorities: see Clark (1992) and Pais,
South, and Crowder (2009)] residents reaches a critical tipping point
(Galster 1991; Clark 1992; South and Crowder 1997, 1998; Crowder
2000; Ellen 2000; Quillian 2002; Card, Mas, and Rothstein 2008). Proposed
reasons for this out-mobility of the white population are racism
(Farley et al. 1994) and a fear of dropping housing prices (Harris 1999).
White avoidance, a complementary theory explaining how ethnic minority
areas are reproduced (rather than come into being), emphasizes white
people’s unwillingness to enter neighborhoods with a certain share of
blacks or other minorities (Ellen 2000). 5 Similar discussions in the literature
focus on how poverty areas either come into being or are made even
poorer through selective moving patterns in which better-off residents
leave and are replaced by households with a socioeconomic status similar
to nonmovers (Wilson 1987; Friedrichs 1991; Skifter Andersen 2003;
Andersson and Bråmå 2004). A high turnover rate might speed up this
process and may also be perceived as a sign of low attractiveness, thereby
reinforcing the selective mobility patterns (Andersson and Bråmå 2004).
The process can of course be reversed, as in the gentrification example;
neighborhood investments in home rehabilitations or new construction
may cause housing prices to rise, forcing low-income groups to leave and
be replaced by better-off inhabitants.
The above theories of ethnic and socioeconomic selective mobility
suggest that moving patterns are affected by thresholds at which the share
of ethnic minority or low-income inhabitants affects aggregate moving
patterns as it exceeds a critical value [for a review, see Quercia and Galster
(2000)]. Though accepted as conventional wisdom for a long prior period
(Wolf 1963), a theoretical foundation for nonlinear change processes in
a neighborhood’s racial composition did not emerge until Schelling’s
tipping model (1971), which was subsequently extended by Taub et al.
(1984). Numerous empirical studies have indeed found that thresholdlike
relationships characterize neighborhood racial transitions, though
no universal tipping point exists (Giles 1975; Goering 1978; Galster 1991;
Clark 1991; Lee and Wood 1991; Crowder 2000; Card et al. 2008). Indeed,
an even wider range of neighborhood sociodemographic dynamics may