Webinar: ATTOM’s COVID-19 Impact Ranking of Vulnerable U.S. Housing Markets
As part of our commitment to provide housing market updates and real world solutions to understand and address the challenges presented by the crisis we are facing in the wake of the Coronovirus pandemic, ATTOM Data Solutions presented a webinar on what the future of housing will look like based on the data driving the decisions.
Unlike other webinars popping up around this topic, ATTOM’s COVID-19 Webinar leverages our Special Report spotlighting the U.S. housing markets vulnerable to the Coronavirus impact.
Click here to listen to this webinar offering a detailed look at the data behind this analysis, which also reveals unique insights into why certain regions are more at risk, what this means for those distressed markets and how this will affect industry businesses and solution providers.
In this webinar, ATTOM’s Chief Product Officer, Todd Teta, and our General Manager of RealtyTrac, Ohan Antebian, provide a brief introduction about ATTOM Data Solutions, including the various data products and solutions that ATTOM offers, before diving into the data behind our COVID-19 impact ranking of vulnerable U.S. housing markets.
ATTOM Data Solutions is your one-stop shop for premium property data with flexible delivery solutions. Our mission is to power real estate transparency and to fuel innovation across various industries with the most comprehensive property data. The ATTOM Table of Data Elements illustrates how we organize our data into four main categories:
- Property & Owner – This is our bread-and-butter data. We track a lot of information about individual properties, including property characteristics, mortgages, transactions, listing information, and ownership. We also offer complete nationwide coverage of foreclosure data (which includes current and historical data). The primary focus of this webinar features data from this category.
- Neighborhood – This category is more about the area surrounding a property rather than the property itself. It includes demographics, crime, and schools. Since location is everything in real estate, when you couple this data with property data, the picture is even more complete.
- Boundaries – This is spatially oriented data, including parcel boundary, neighborhood boundaries, and area boundaries. A common usage of this data is for identifying which elementary, middle and high school are assigned to a particular property, or identifying which neighborhood a property is located in.
- Analytics/Derived – This category encompasses the analytics derived from our other data. This includes our AVM values, equity values, and more.
In preparing our special report spotlighting county-level housing markets around the U.S. that are more or less vulnerable to the impact of the Coronavirus pandemic, we looked as several metrics we traditionally think of as potential factors of distress in real estate. This webinar reveals the methodology we used in developing this report.
First, we looked at foreclosure filings, which simply tracks the number of current foreclosures. This is a lagging indicator of distress in that the homeowners are already having trouble paying their mortgages. Then we looked at homes with underwater mortgages. These homes have negative equity, where the mortgage is greater than the home is worth. We consider this to be a short-term distress indicator because when things change economically homeowners are more likely to go into foreclosure if they owe more on their home than it is worth. The last metric we looked at was affordability, which we measure are the percent of wages allocated to key housing costs like mortgage payments, property taxes and insurance. In highly unaffordable areas, demand can decrease quickly when an external event such as COVID-19 happens, and prices can decline along with that demand. We see this as a mid-term indicator because supply and demand dynamics don’t move as fast as job loss and foreclosure do.
Without a doubt, these aren’t the only factors that could impact local real estate markets from this pandemic – add in things like job loss, infection rates, and other local dynamics, and the methodology gets complicated quickly. But, setting aside highly localized conditions, we feel these three metrics are a good indicator of how risky various markets are over the next year. With these key metrics, we created a composite ranking at the county level and ranked all major counties in the nation.
So, with that methodology in place, what did we learn? Well, the results were somewhat staggering.
Click here to hear the entire webinar, which also takes a look at the underlying trends and implications for home sales, the distressed market, the real estate ripple effects, and what that means for the future of the housing industry.
Please contact us if you have questions about the underlying data referenced in this article, or would like to have access to that data in the form of custom reports, API, Bulk File or DaaS.