User feedback is essential to the HomeKeeper National Data Hub project, and also to the ongoing improvement of HomeKeeper itself, as we continually make changes to increase the transparency, legibility, and accuracy of our analyses. This case study is an example of how important it is to hear from program staff working on the ground.
The National Data Hub is a central database that compiles data from HomeKeeper users all over the country. Its purpose is to analyze the performance of affordable homeownership programs using standardized metrics and peer-groupings to customize comparisons across the industry.
These analyses are distributed to users in a Social Impact Report for their program – a series of 27 charts with data on homebuyer demographics, affordability, resale formula performance, subsidy growth, homeowner returns on investment, etc. Here’s an example of a Social Impact Report for an individual program, and here is an aggregated report for all the programs in the Hub.
The “Foreclosure Rescue” story
We needed a way to assess whether or not a transaction resulted in the home being lost from the program’s portfolio. So we defined a binary variable called “Lost Unit” that was false if the home was resold to another eligible buyer, or to the program itself. If sold to an ineligible buyer or foreclosed, “Lost Unit” was true.
We released the new field in a HomeKeeper update, and immediately heard from HomeKeeper users wanting to improve the definition. Emily Higgins and Jaclyn Marcotte of Champlain Housing Trust, a Community Land Trust in Burlington VT and one of the largest shared-equity programs in the country, pointed out that the distinction we had created between “lost” and “non-lost” units was simplistic. We were failing to tell the story of one of the most important stewardship functions a good shared-equity program performs for the community – the ability to “rescue” a home so that the public investment is retained for future buyers, even if the homeowner was not spared from foreclosure.
Since the “Lost Unit” binary variable depended on another field, “Resale Type,” the solution was simply to add a new possible value for “Resale Type” that would identify these “rescues.” This value was released in version 1.10. It allows us to track the foreclosure without calling the home lost, and it allows users to tell this important stewardship story.
Ultimately it’s up to individual programs to distinguish between rescues and foreclosures that are indeed considered lost from the portfolio. However, it may be useful to define a minimum threshold of subsidy retention to assist the decision – e.g. “a foreclosure can be considered rescued by the program if at least 60% of the subsidy invested in the home is retained and passed on to the next buyer.”
What do you think the right threshold would be, and on what conditions should the definition depend?
We invite you to comment on this particular issue and others in the user forums. Your feedback is essential to make HomeKeeper work!