Improving Housing Inspections with Predictive Modeling

Affiliated institutions: The Lab @ DC

Date created: | Last Updated:


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Category: Project

Description: Everyone wants a safe home. Housing codes are rules that are meant to ensure all homes in DC are safe to live in, but there are thousands of rental properties in the District and limited inspectors in the Department of Consumer and Regulatory Affairs (DCRA). Many properties are safe, so if we knew which rental properties were most likely to have a life-threatening violation, then inspectors could focus their efforts on those buildings. We developed a statistical model to predict how likely it was that a rental property would violate a housing code and compared our predictions to the results of actual inspections of building exteriors. Our model was not good at predicting where the DCRA inspectors would find housing code violations on inspections, but in creating the model, we also helped the agency streamline their process for selecting random properties to inspect. Based on the results of these inspections, DCRA is not currently using the model, but they are using the streamlined process we developed.


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