Read published research on what makes housing accessible to everyday destinations in Southern California?

Publication:

Kane, Kevin, John R. Hipp, and Jae Hong Kim. (2017). “Analyzing accessibility using parcel data: Is there still an access-space trade-off in Long Beach, California? The Professional Geographer 69:3, 486-503.

Abstract:

This article analyzes the impact of changing housing and neighborhood characteristics on the accessibility of neighborhood businesses using Long Beach, California, as a case study. Although advocates of smart growth and New Urbanism encourage land use mixing, aggregate-level analysis can be too coarse to pick up on fine-grained aspects of urban streetscapes. This study uses assessor parcel records and a point-based business establishment data set to analyze city-wide patterns of accessibility from individual dwelling units to thirty-one types of neighborhood businesses, including grocery stores, service shops, drug stores, doctor’s offices, and banks. Regression results compare parcel-level and neighborhood-level drivers of accessibility between 2006 and 2015 to gauge the aggregated effect of recent economic, demographic, and built environment changes on this aspect of urban spatial structure. Larger homes in older, multiunit buildings and higher income neighborhoods show substantial increases in accessibility to most establishment types, suggesting a trend toward both greater accessibility and larger dwelling units—despite the traditional trade-off between access and space. Although gradual increases in home and business density increased overall accessibility over this period, weaker neighborhood-level results indicate that this trend is less pronounced in high-poverty and non-white areas.

Read published research on neighborhood mixing and economic dynamism

Publication:

Hipp, John R., Kevin Kane, and Jae Hong Kim. (2017).  “Recipes for Neighborhood Development: A Machine Learning Approach toward Understanding the Impact of Mixing in Neighborhoods.” Landscape and Urban Planning.

Abstract:

Scholars of New Urbanism have suggested that mixing along various dimensions in neighborhoods (e.g., income, race/ethnicity, land use) may have positive consequences for neighborhoods, particularly for economic dynamism. A challenge for empirically assessing this hypothesis is that the impact of mixing may depend on various socio-demographic characteristics of the neighborhood and takes place in a complex fashion that cannot be appropriately handled by traditional statistical analytical approaches. We utilize a rarely used, innovative estimation technique—kernel regularized least squares—that allows for nonparametric estimation of the relationship between various neighborhood characteristics in 2000 and the change in average household income in the neighborhood from 2000 to 2010. The results demonstrate that the relationships between average income growth and both income mixing and racial/ethnic mixing are contingent upon several neighborhood socio-demographic “ingredients”. For example, racial mixing is positively associated with average income over time when it occurs in neighborhoods with a high percentage of Latinos or immigrants, high population density, or high housing age mixing. Income mixing is associated with worsening average household income in neighborhoods with more poverty, unemployment, immigrants, or population density. It appears that considering the broader characteristics of the neighborhood is important for understanding economic dynamism.