Does the House or Neighborhood Matter More? Predicting Abandoned Housing Using Multilevel Models

Multilevel models are important to use when data are nested. To demonstrate this point, an example is given where the probability of a house being abandoned is predicted using house-and neighborhood-level variables. The example illustrates the types of findings that are possible when different spatial scales are carefully considered. The final model indicates that for stable neighborhoods, house-level characteristics have a greater impact on the probability than do neighborhood-level characteristics; however, for more distressed neighborhoods, neighborhood characteristics matter more. Without the use of multilevel modeling techniques, this relationship might not have been found.