It’s clear that the Atlanta Region faces a housing affordability crisis, as do many other metros in this country. And the pandemic (as with so many other things) is turning bad (conditions) into worse. The Atlanta Regional Commission (ARC) in response has developed and intends to refine over time a Metro Atlanta Housing Strategy to grapple with the manifold issues around affordability. The ARC Research & Analytics Group will soon publish a Housing Regional Snapshot to delve into some the many aspects of the problem. Two of our recent blog posts began to present data that will contribute to that snapshot: Metro Atlanta Evictions Tracker and Housing Insecurity: Evidence from Two Surveys.
The map below shows the spatial spread of the problem. There are a great many census tracts in the region where well over half of households have to pay more than 30% of their income for housing. While the largest clustering of housing cost-burdened households are found to the south of the I-20 Corridor, there are also nodes of relative inaffordability along the I-85 corridor to the northeast part of the region.
Read on to see how we need to look at type of housing and level of household income to paint a clearer picture of the affordability crisis. Further, it becomes evident that affordability challenges are relative–as a very significant share of our residents have to pay over 50% of income for housing.
Map: Cost Burdened Households by Tract, 10-County ARC Region (Source: DataNexus)
Chart 1 below shows that nearly 7 in 10 of total households (either owning or renting) are able to pay their monthly housing costs usin less than 30% of their income. Not surprisingly, paying rent or mortgage gets more difficult the lower your income. At the lowest level of income (<$20,000) nearly 8 in 10 households have to pay 30% or more of their income for housing, and nearly 2 in 3 have to pay 50% or more of their income [IMPORTANT NOTE: “cost-burdened” here, and on charts 1 thru 4, is defined as paying between 30% and 49% of monthly income for housing costs; “extremely cost-burdened” equates to paying 50% or more of income for housing.]
Drilling down into tenure types by income level prepares us to get a much closer look at the affordability picture. Chart 2 illustrates that– across all income levels– 2 in 3 households own, and 1 in 3 rent. In the highest income class (of over $100,000) just over 80% own; in the lowest income group (less than $20,000) nearly 2 in 3 rent.
Chart 1: Cost Burden for Households, by Income Level. 10-County ARC Region (Source: American Community Survey)
Chart 2: Owner and Renter Shares by Income Level. 10-County ARC Region (Source: American Community Survey)
Chart 3 below presents a daunting fact: nearly half (47%) of renters in our area across all income levels are either cost burdened (paying 30-50%) or extremely cost burdened (50%+ of their income for their rentals). A roughly equal share (about 77%) of renter households across both the < $20,000 and $20,000 to $50,000 income groups are cost burdened or extremely cost-burdened, but in the < $20,000 classification, nearly 2 in 3 of renters are paying 50% or more of their income for their rented unit.
Owner cost burdens, as shown on Chart 4, are much less than renter cost burdens. 78% of owners (across all income levels) are not cost-burdened–meaning that only about 1 in 5 are paying more than 30 percent of income for their homes. Only at lower levels of income (under $50K) are more than a third of owners cost burdened (30-50%) or extremely cost burdened (50%+).
Chart 3: Renter Cost Burden Levels by Income, 10-County ARC Region (Source: American Community Survey)
Chart 4: Owner Cost Burden Levels by Income, 10-County ARC Region (Source: American Community Survey)
There are as such a large number of “layers to the onion” of housing costs, as there are as many complexities in the issues of housing supply, housing prices, and so forth. Again, we will be looking at a good number of these factors in our Housing Regional Snapshot coming out next week. If you would like to explore yourself in the meantime, we highly recommend the Regional Housing Data Explorer and Evictions Tracker, as well as (for housing data and much, much more) DataNexus.