Analysis

We computed a number of economic and real estate market indicators for each community in Chicago:

• Affordability: uses income and housing prices to determine the percentage of residents who can afford to buy homes in the area.

• Stability: Based on an analysis by Walker and Winston, we used HMDA data, transactions, low-value transfers, etc. to assess the stability of communities within the county.

• Vacancy: We ranked neighborhoods based on the percentage of addresses reported vacant by the USPS, and based on the number of 311 vacant building complaints per housing unit.

• Income, crime, owner occupancy, crowding, low-value transactions, mortgages, foreclosure rate, etc.: We took a variety of useful indicators from our data sets and ranked neighborhoods from 0 to 100 based on where they stood relative to their peers.

We also implemented a simple hedonic pricing model to assess the affect of foreclosures and demolitions on nearby housing prices. We used a spatial auto-regressive model that took into account community and property characteristics, distance from the Loop, and other variables. We found that foreclosures negatively impacted housing prices in the surrounding 1/8 mile by approximately 2% (no effect was ruled out at 95% significance), but measured no significant price decline for demolitions, indicating a possible option value for distressed vacant buildings.

Finally, we also ran a spatiotemporal correlation analysis, finding that a foreclosure within 1/8 mile and 3 months was a statistically significant predictor of future foreclosures, even when purely spatial (high- versus low-demand neighborhoods) and purely temporal (seasonal variations) correlations were taken into account.