Introduction

Click here to view the World Press 2008 photo of the year which depicts a Cuyahoga County Sheriff searching through a foreclosed house, making sure that the previous owner has vacated and that no squatters have taken shelter. In the run-up to the 2008 financial crisis the effects of sub-prime lending were becoming apparent in the number of foreclosures that continued to escalate as the crisis became widespread. This image became a symbol of American decay.

 

I use this project as an attempt to understand the victimized demographics of predatory mortgage lending and the negative spatial manifestations within Cleveland. I hope to identify some of the most at-risk demographic groups through the use of regression techniques and to explore the spatial variation of these groups in relation to their probability of foreclosure. In so doing I wish to identify specific neighbourhoods where at-risk groups have a low and high probability of foreclosure.

 

I will be using a dataset of over 65,000 foreclosures between 2000 and 2012. With this amount of points it will be necessary to cluster them in order to make meaningful observations. To do so I will use a risk-adjusted nearest neighbour hierarchy technique within CrimeStats 3.

 

ArcGIS will be used to analysis 2010 census data and interpret the influences of different demographics which will be incorporated into a geographically weighted regression (GWR). These GWR results will also be used to predict probability of foreclosure for the different demographics.

 

If you have any questions about my project I can be reached at mart…@gmail.com.

 

Thank you.