The purpose of this research is to develop a measure of maintenance behavior that takes advantage of recent work by Ioannides (2002) and Helms (2012). We borrow from this idea of the influence of contextual effects on individual behavior by extending it beyond renovation expenditures to maintenance behavior. First we operationalize maintenance behavior using aggregate level data and then test how well this construction performs in predicting individual property claims. We argue that using aggregate level maintenance data as a proxy for individual maintenance behavior has multiple benefits. Foremost, the ease of access to aggregate level data make analyses more accessible especially when compared to the enormously high cost of collecting individual data. Second, given the contagion effect that exists when individuals are surrounded by other poor-/well- maintained properties, we can easily derive potential individual property risk by analyzing aggregate data.
Presented in Session 3. Population, Development, & the Environment; Data & Methods; Applied Demography