Panel Paper:
Effect of Rail Intra-Urban Transit Stations on the Neighborhood Life-Cycle
*Names in bold indicate Presenter
Atlanta has a racial history going back to before Martin Luther King Jr., and pre-Civil War times, and it remains economically polarized. Economic disparities create price gradients between urban neighborhoods that are exploited by gentrifiers. The period from 2010 to 2014 was vibrant from the housing market perspective, thus conducive for gentrification. Therefore, Atlanta during the 2010 to 2014 time-period is expected to have active changes in neighborhood characteristics.
The effect of public transportation stations on neighborhood change is evaluated using a robust matching methodology, adding to the existing literature on the methodology of transit evaluation. The treatment is rail intra-urban transit stations. The matching strategy compares census tracts with existing rail intra-urban transit stations, to similar census tracts without access to stations, on observable characteristics including historical patterns of neighborhood change. Neighborhood change is operationalized with a filtering/gentrification index, using 1970 to 2010 normalized census data from the Longitudinal Tract Database (LTDB). The evaluation utilizes 5-year American Community Survey (ACS) data 2010 and 2014. In 2010 foreclosure rates and unemployment began to decline in Atlanta for the first time since the great recession, creating an opportunity for a case study given the conditions of rapid neighborhood change.
Transportation infrastructure is a high cost investment for municipalities with a long service time, therefore understanding its long term impacts should be better understood. This study contributes to the scholarship on gentrification, and the methodology of studying neighborhood change. The long time frame of this study allows for the observation of neighborhood stability and long term patterns of change. Using neighborhood change over time as an observable characteristic in the matching strategy provides for a more robust match between the treatment and control groups, helping to reduce transit station selection bias. Additionally, stations are only new once, but could exist for many, many decades. However, much of the scholarship examines changes in neighborhoods over short time frames when new stations are put in place. Therefore, this study adds to understanding the effect of public transportation on neighborhoods, as well as the methodology of urban transit system evaluation, and should be of significance to both researchers and practitioners.