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Here’s how HUD’s new housing voucher rule affects recipients

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Data from NYU shows that in most of the 24 metro areas impacted, voucher recipients would have more and better options

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When Ben Carson and the U.S. Department of Housing and Urban Development (HUD) announced its intention to delay by two years an Obama-era anti-segregation measure called the Small Area Fair Market Rent (SAFMR) rule, they cited, among other things, results from the rule’s pilot program. The findings showed that, in aggregate, the rule led to Section 8 voucher recipients having fewer overall affordable housing options.

But a new report from New York University’s Furman Center estimates the effects of the SAFMR rule on the 24 metro areas where the rule will be implemented—and contradicts the conclusion from the pilot program. It shows that, in aggregate, the number of units affordable to voucher recipients will increase by more than 9 percent, in addition to providing options outside of high-poverty, low-rent areas, an outcome which the rule was designed to achieve.

The district court of Washington, D.C., overruled HUD’s attempt to delay the rule last week, and the department is now working to implement it. Here’s how the rule is designed to work:

Section 8 housing voucher recipients pay roughly 30 percent of their income on rent, and the rest of the rent is covered by the voucher. But the voucher will cover only up to “fair market rent,” which currently is calculated by averaging an entire metro area’s rent.

This often includes the outer rims of a metro area where rent is cheaper. This drives down the fair market rent calculation and thus the value of the voucher. Voucher recipients are then stuck with homes and apartments in low-rent, high poverty areas.

The SAFMR rule recalculates the fair market rent by averaging rent within a zip code instead of an entire metro area. This means in high-rent areas, the voucher is worth more and can thus be an option for a voucher recipient. It also means that in low-rent areas, the voucher is worth less because it doesn’t take into account high-rent areas within the larger metro area.

The balance between more options in high- and medium-rent zip codes and fewer options in low-rent zip codes is what determines whether the voucher recipient has more or fewer housing options in aggregate. Zip codes with higher concentrations of low-rent housing can lead to fewer overall options for voucher recipients, even if the options they have are better.

This was the case in the pilot program, which included public housing authorities (PHAs) in Laredo, Texas; Chattanooga, Tennessee; Long Beach, California; Cook County, Illinois; Mamoroneck, New York; Plano, Texas; and Dallas, Texas. Available housing options dropped 3.4 percent in aggregate across the seven areas. In Long Beach, where rental housing is highly concentrated in low-rent zip codes, the reduction was 12 percent.

But the numbers vary across metro areas. According to NYU’s study, the total units available to voucher recipients increases in 20 of the 24 metro areas where the SAFMR rule will take effect, in addition to having options in high-rent zip codes, which again is ultimately the point of the rule.

Below is NYU’s data that estimates the gains or losses from each of the 24 metro areas. San Antonio showed the highest gain in total units available to voucher recipients, at a whopping 28.3 percent increase, while nine others saw double-digit gains. Gary, Indiana; Hartford, Connecticut; Monmouth, New Jersey; and North Port-Sarasota-Bradenton, Florida, were the metro areas that saw a decline in total units.

Rental units affordable to housing voucher recipients

Metro area Total Units FMR affordable units SAFMR affordable units Difference Percentage difference
Metro area Total Units FMR affordable units SAFMR affordable units Difference Percentage difference
All SAFMR Areas 6,400,441 2,502,534 2,730,817 228,283 9.12%
Atlanta, GA 584,755 240,664 267,765 27,101 11.26%
Charlotte, NC 214,574 86,395 94,177 7,783 9.01%
Chicago, IL 870,900 324,163 343,921 19,758 6.10%
Gary, IN 63,166 27,636 26,386 -1,250 -4.52%
Colorado Springs, CO 71,519 25,781 28,470 2,689 10.43%
Dallas, TX 564,569 218,961 246,297 27,337 12.48%
Fort Worth, TX 240,719 98,612 111,475 12,863 13.04%
Hartford, CT 121,203 49,104 48,484 -621 -1.26%
Jackson, MS 50,227 20,724 21,217 493 2.38%
Jacksonville, FL 145,936 58,417 64,203 5,787 9.91%
Fort Lauderdale, FL 213,688 79,774 87,294 7,520 9.43%
West Palm Beach-Boca Raton, FL 136,643 51,030 60,476 9,447 18.51%
Bergen-Passaic, NJ 170,781 57,675 64,867 7,192 12.47%
Monmouth-Ocean, NJ 75,795 30,634 29,135 -1,499 -4.89%
North Port-Sarasota-Bradenton, FL 76,418 32,035 31,087 -948 -2.96%
Palm Bay-Melbourne-Titusville, FL 51,246 18,925 22,381 3,456 18.26%
Philadelphia, PA 581,531 240,731 245,718 4,987 2.07%
Pittsburgh, PA 220,210 87,734 88,737 1,003 1.14%
Sacramento, CA 229,769 93,206 97,528 4,323 4.64%
San Antonio, TX 242,058 84,650 108,635 23,986 28.34%
San Diego, CA 429,988 168,800 179,547 10,747 6.37%
Tampa Bay, FL 330,210 135,180 142,669 7,489 5.54%
Urban Honolulu, HI 102,358 36,398 43,200 6,802 18.69%
Washington, DC 612,177 235,311 277,153 41,842 17.78%
NYU Furman Center

The report comes with a few caveats. First, the analysis doesn’t take into account HUD strategies to counter a reduction in the value of vouchers used in low-rent areas. The estimates don’t consider where voucher users currently live, barriers to mobility other than how fair market rent is currently calculated, or a landlord’s willingness to accept vouchers. The analysis simply replicates that of the pilot program report.