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Fannie Mae economist questions affordable housing data

Do big numbers demand better attention?

Fannie Mae economist Nuno Mota just published a blog on the Fannie Mae Commentary site asking some pretty pressing questions on the way housing affordability metrics are measured and interpreted.

Fannie Mae today introduced the “Housing Affordability Primer,” which examines the effectiveness of common housing affordability metrics used in the industry.

The research analysis focuses on housing affordability in terms of households' ability to cover costs at given income levels, as opposed to households' ability to access mortgage credit.

Mota even goes a bit further, offering some interesting, data-driven solutions.

Mota writes:

The U.S. Census Bureau's American Community Survey indicates that some 18.3 million homeowner households and 20.7 million renter households experienced housing affordability problems in 2014 as measured by the percentage of households that were "cost burdened." A household is considered cost burdened if it spends more than 30 percent of its gross income on housing costs. These are big numbers that demand our attention.

However, considering that there are a number of affordability metrics currently used throughout the industry, are these numbers providing the most accurate view of the overall affordability picture, or are we only getting a partial view?

Importantly, is there a way to better use the metrics available to accurately assess housing affordability problems?

For his answers, click here.

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