New Options for Investigating Macro-level Variation in Segregation
The previous chapter established that the difference of means framework for measuring segregation makes it possible to investigate segregation in a single city using individual-level models of residential attainment. The discussion in this chapter reviews
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New Options for Investigating Macro-level Variation in Segregation
The previous chapter established that the difference of means framework for measuring segregation makes it possible to investigate segregation in a single city using individual-level models of residential attainment. The discussion in this chapter reviews how this approach can be extended to investigate ecological (i.e., aggregate- level) variation in segregation across cities and over time using multi-level models of individual residential attainments. The key is that ecological variation in segregation can be investigated by assessing how the effect of race on segregation-relevant individual residential outcomes is conditioned by time and/or city characteristics. A central advantage of this approach is that it permits researchers to also include relevant non-racial social and economic characteristics in the micro-model. This allows effects of community characteristics to be estimated at the “zero order” level or “net” of controls for non-racial factors. It also can help overcome the risk of errors of inference that are likely to occur in aggregate-level analyses that attempt to control for relevant individual-level social and economic characteristics using aggregate-level indicators of group disparity on these variables.
10.1 N ew Specifications for Conducting Comparative and/or Trend Analyses of Segregation Investigations of how segregation varies across metropolitan areas and over time are a staple of segregation studies. The new methods outlined here can be used to first exactly replicate earlier studies and then to extend them in new ways. Results from previous studies can be exactly replicated by estimating contextual and multi-level models where variation in segregation over time and across metropolitan areas is captured by assessing how the effect of race in individual-level models of residential attainment varies with time and/or the ecological characteristics of metropolitan areas. For example, consider the question of how White-Black segregation © The Author(s) 2017 M. Fossett, New Methods for Measuring and Analyzing Segregation, The Springer Series on Demographic Methods and Population Analysis 42, DOI 10.1007/978-3-319-41304-4_10
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10 New Options for Investigating Macro-level Variation in Segregation
measured by the index of dissimilarity (D) varies across cities based on city size (lnpop = the natural logarithm of total population) and relative minority size (rpb = the square root of proportion Black for the city population). Following the typical aggregate-level approach, cities are taken as units of analysis, D is calculated separately for individual cities, and scores for D then are taken as dependent variables (y) in a city-level OLS regression analysis that includes city size (lnpop) and relative minority size (rpb) as predictors as follows.
y i = a0 + a1 ( lnpop ) + a 2 ( rpb )
I estimated this equation using city-level data for the 201 metropolitan areas that had 50,000 total households and 2000 Black hou
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