Location
SU 217
Start Date
15-11-2019 12:00 PM
Presentation Type
Podium
Department
Economics
Session
Session 6
Description
Milwaukee’s 53206 ZIP code, located on the city’s near North Side, has drawn considerable attention for its poverty and incarceration rates, as well as for its large proportion of vacant properties. As a result, it has been the subject of academic studies, considerable news reporting, and even a documentary; it has benefited from targeted policies at the city level. Targeting specific ZIP codes, rather than other types of geographic area can raise certain issues, however. In particular, these areas were created for mail delivery rather than to facilitate socieoeconomic analysis, and they often aggregate diverse urban areas that sometimes cover suburban areas as well. This study examines the 53206, as well as the other 26 ZIP codes within the city of Milwaukee, using Geographic Information Systems and statistical analysis to focus on the distributions for the much smaller block groups within each postal subdivision. The 53206 lies on the extreme end of most rankings for set of eight socioeconomic indicators, including poverty rates, race, and homeownership, but these are shown to vary widely among the block groups within each ZIP code. The poorest block groups outside the 53206, for example, have poverty rates that exceed this ZIP code’s median value, highlighting the argument that ZIP-code-specific policy might exclude equally deserving geographic areas. Using Principal Components Analysis, five of the indicators are combined to create a “53206 Index,” which exceeds even the top 25 percent of block groups in all other ZIP codes except the 53233 immediately west of downtown. This area therefore is identified as an additional candidate for targeted investment. The index is also calculated using similar methods for Chicago and Detroit; Milwaukee’s 53206 would rank near the middle of Detroit’s ZIP codes and near the most extreme in Chicago. This study therefore develops a useful set of tools to compare urban conditions across cities nationwide. This newly created index is compared to a standard economic deprivation index, commonly used in the literature, using both standard and spatial regression techniques. Results show that the model’s performance improves when spatial correlation is taken into account, confirming that poverty and other socioeconomic stresses are clustered, both in the 53206 ZIP code and across Milwaukee. The method can be further extended when discussing targeted policy across, as well as within, cities across the country.
Included in
How Unique is Milwaukee’s 53206? An Examination of Disaggregated Socioeconomic Characteristics Across the City and Beyond
SU 217
Milwaukee’s 53206 ZIP code, located on the city’s near North Side, has drawn considerable attention for its poverty and incarceration rates, as well as for its large proportion of vacant properties. As a result, it has been the subject of academic studies, considerable news reporting, and even a documentary; it has benefited from targeted policies at the city level. Targeting specific ZIP codes, rather than other types of geographic area can raise certain issues, however. In particular, these areas were created for mail delivery rather than to facilitate socieoeconomic analysis, and they often aggregate diverse urban areas that sometimes cover suburban areas as well. This study examines the 53206, as well as the other 26 ZIP codes within the city of Milwaukee, using Geographic Information Systems and statistical analysis to focus on the distributions for the much smaller block groups within each postal subdivision. The 53206 lies on the extreme end of most rankings for set of eight socioeconomic indicators, including poverty rates, race, and homeownership, but these are shown to vary widely among the block groups within each ZIP code. The poorest block groups outside the 53206, for example, have poverty rates that exceed this ZIP code’s median value, highlighting the argument that ZIP-code-specific policy might exclude equally deserving geographic areas. Using Principal Components Analysis, five of the indicators are combined to create a “53206 Index,” which exceeds even the top 25 percent of block groups in all other ZIP codes except the 53233 immediately west of downtown. This area therefore is identified as an additional candidate for targeted investment. The index is also calculated using similar methods for Chicago and Detroit; Milwaukee’s 53206 would rank near the middle of Detroit’s ZIP codes and near the most extreme in Chicago. This study therefore develops a useful set of tools to compare urban conditions across cities nationwide. This newly created index is compared to a standard economic deprivation index, commonly used in the literature, using both standard and spatial regression techniques. Results show that the model’s performance improves when spatial correlation is taken into account, confirming that poverty and other socioeconomic stresses are clustered, both in the 53206 ZIP code and across Milwaukee. The method can be further extended when discussing targeted policy across, as well as within, cities across the country.