Realtor.com® Monthly Housing Report: September is No Longer the Best Time to Buy a Home
Homes sold faster in September than in August for the first time since 2016
- The number of homes on the market is down 39% year-over-year in September equating to 529,000 fewer home listings
- Homes sold 12 days faster than last year and three days faster than last month
- Median home price was $350,000, up 11.1% year-over-year
SANTA CLARA, Calif., Oct. 1, 2020 /PRNewswire/ -- September is typically the best time of year to buy a home because there are usually more homes for sale, less competition from other buyers, and lower home prices -- but that is not the case this year, according to realtor.com®'s September Monthly Housing Trends Report. Instead, a pandemic-fueled buying spree has led to an unusually competitive fall homebuying season where typical buyers are paying roughly $20,000 more for a home and face 25% more competition than at the start of the year.
"Many buyers tend to put their home search on hold after the start of the school year, but remote learning and the desire for more space continued to fuel buyer interest in September," said Danielle Hale, chief economist, realtor.com®. "Unseasonably high buyer interest coupled with historically low inventory and favorable mortgage rates are creating a perfect storm in the housing market. While this is good news for anyone looking to sell their home, it has created tremendous competition among buyers."
September is not the best time to buy in 2020
Last year the best time to buy a home was the week of Sept. 22-28 and if 2020 was following the same pattern, it would have been Sept. 20-26. During this week, the housing market has typically cooled down, but this year:
- Listings are down 21% compared to the start of the year. Typically, there are 17% more homes available in September than at the start of the year.
- Homes cost about $20,000 more than expected. Home prices are usually up about 10% in September, but this year they are up 17% compared to the start of the year.
- Homes are selling 12 days faster than expected. Homes usually sell 25% faster than the start of the year, but in 2020 they sold 39% faster.
- There are 25% more buyers in the market compared to the start of the year. Usually, there are only 9% more buyers in the market compared to the start of the year.
Homes sold faster in September than August for the first time since 2016
- The typical home sold in 54 days in September, 12 days faster than the same time last year, and three days faster than last month.
- In the 50 largest U.S. metros, the typical home sold in 44 days in September, 10 days faster than last year.
- Properties in the Northeast now typically spend 13 fewer days on the market than last year, followed by those in the South (11 days faster), the Midwest (9 days faster), and the West (7 days faster).
Buyers face high home prices everywhere
- All 50 of the nation's largest metros saw increasing home prices compared to last year.
- Among those, prices are increasing the most in the Northeast which is seeing an average price acceleration of 12.8% over last year, compared to 10.9% in Midwestern metros, 8.6% in Western metros and 7.2% in Southern metros.
- The metros seeing the highest year-over-year price growth are:
- Cincinnati, Ohio-Ky.-Ind. (+16.9%);
- Boston-Cambridge-Newton, Mass.-N.H (+16.4%); and
- Philadelphia-Camden-Wilmington, Pa-N.J.-Del.-Md. (+15.6%).
Buyers have limited number of homes to choose from
- The number of newly listed homes on the market in September decreased by 13.8% compared to last year, even more significant than the 11.8% loss in August.
- None of the largest 50 metros saw an increase in the number of homes on the market compared to last year and most (35 out of 50) saw greater inventory declines than in August.
Metros With the Largest Increases in Home Prices
Metro | Median Listing Price YoY | Median Listing Price | Median Days on Market Y-Y | Median Days on Market | New Listing Count YoY | Active Listing Count YoY |
Cincinnati, Ohio-Ky.-Ind. | 16.9% | $318,000 | -11 | 39 | -23.1% | -46.6% |
Boston-Cambridge-Newton, Mass.-N.H. | 16.4% | $677,000 | -18 | 34 | -3.3% | -33.4% |
Philadelphia-Camden-Wilmington, Pa.-N.J.-Del.-Md. | 15.6% | $344,000 | -20 | 43 | -0.5% | -42.6% |
Indianapolis-Carmel-Anderson, Ind. | 15.2% | $286,000 | -10 | 46 | -16.8% | -58.5% |
Buffalo-Cheektowaga-Niagara Falls, N.Y. | 15.0% | $230,000 | 0 | 43 | -12.5% | -43.3% |
Austin-Round Rock, Texas | 14.8% | $408,000 | -15 | 45 | -13.8% | -47.9% |
Riverside-San Bernardino-Ontario, Calif. | 14.0% | $468,000 | -15 | 41 | -10.1% | -55.6% |
New York-Newark-Jersey City, N.Y.-N.J.-Pa. | 13.5% | $625,000 | -13 | 58 | -1.1% | -10.3% |
Kansas City, Mo.-Kan. | 13.2% | $340,000 | -5 | 49 | -25.2% | -50.3% |
Detroit-Warren-Dearborn, Mich | 12.8% | $273,000 | -8 | 38 | -27.0% | -45.9% |
New Orleans-Metairie, La. | 12.3% | $325,000 | -10 | 64 | -27.8% | -38.5% |
Memphis, Tenn.-Miss.-Ark. | 11.3% | $262,000 | -12 | 47 | -19.5% | -52.0% |
Richmond, Va. | 10.9% | $355,000 | -8 | 48 | -18.2% | -46.0% |
St. Louis, Mo.-Ill. | 10.9% | $250,000 | -8 | 58 | -15.5% | -39.1% |
San Francisco-Oakland-Hayward, Calif. | 10.8% | $1,037,000 | 3 | 35 | -0.2% | -12.1% |
Atlanta-Sandy Springs-Roswell, Ga. | 10.3% | $355,000 | -11 | 45 | -25.7% | -45.5% |
Sacramento--Roseville--Arden-Arcade, Calif. | 10.1% | $544,000 | -10 | 35 | -3.4% | -51.2% |
Virginia Beach-Norfolk-Newport News, Va.-N.C. | 10.0% | $330,000 | -22 | 39 | -4.8% | -45.5% |
Providence-Warwick, R.I.-Mass. | 9.3% | $412,000 | -14 | 41 | -16.5% | -53.2% |
Washington-Arlington-Alexandria, DC-Va.-Md.-W. Va. | 9.1% | $519,000 | -16 | 28 | -3.7% | -40.4% |
Cleveland-Elyria, Ohio | 9.1% | $216,000 | -10 | 49 | -14.0% | -50.6% |
Milwaukee-Waukesha-West Allis, Wis. | 8.8% | $326,000 | -4 | 41 | -11.5% | -42.5% |
Chicago-Naperville-Elgin, Ill.-Ind.-Wis. | 8.3% | $349,000 | -7 | 42 | -14.3% | -34.4% |
Charlotte-Concord-Gastonia, N.C.-S.C. | 8.3% | $368,000 | -14 | 42 | -17.1% | -47.9% |
Las Vegas-Henderson-Paradise, Nev. | 7.8% | $345,000 | -10 | 39 | 11.1% | -7.8% |
Hartford-West Hartford-East Hartford, Conn. | 7.5% | $300,000 | -22 | 43 | 1.1% | -31.8% |
Oklahoma City, Okla. | 7.4% | $269,000 | -2 | 50 | -12.3% | -39.2% |
Portland-Vancouver-Hillsboro, Ore.-Wash. | 7.4% | $505,000 | -6 | 44 | -21.1% | -44.8% |
Tampa-St. Petersburg-Clearwater, Fla. | 7.2% | $300,000 | -10 | 50 | -15.5% | -43.5% |
Nashville-Davidson--Murfreesboro--Franklin, Tenn. | 7.2% | $400,000 | -5 | 32 | -29.8% | -40.5% |
San Diego-Carlsbad, Calif. | 7.1% | $776,000 | -7 | 35 | -5.7% | -42.9% |
Houston-The Woodlands-Sugar Land, Texas | 7.0% | $332,000 | -7 | 52 | -6.5% | -32.6% |
Birmingham-Hoover, Ala. | 6.9% | $271,000 | -12 | 52 | -7.8% | -38.1% |
Rochester, N.Y. | 6.7% | $223,000 | -14 | 29 | -8.3% | -40.9% |
San Antonio-New Braunfels, Texas | 6.6% | $309,000 | -15 | 52 | -13.2% | -44.5% |
Phoenix-Mesa-Scottsdale, Ariz. | 6.4% | $414,000 | -8 | 37 | -3.7% | -40.9% |
San Jose-Sunnyvale-Santa Clara, Calif. | 5.5% | $1,199,000 | -7 | 35 | 18.8% | -24.9% |
Raleigh, N.C. | 5.5% | $391,000 | -9 | 48 | -22.8% | -44.4% |
Denver-Aurora-Lakewood, Colo. | 5.0% | $522,000 | -7 | 36 | -16.3% | -40.0% |
Seattle-Tacoma-Bellevue, Wash. | 4.8% | $628,000 | -8 | 35 | 15.9% | -25.9% |
Columbus, Ohio | 4.7% | $300,000 | -13 | 31 | -12.7% | -47.2% |
Dallas-Fort Worth-Arlington, Texas | 4.5% | $360,000 | -10 | 46 | -18.9% | -43.9% |
Minneapolis-St. Paul-Bloomington, Minn.-Wis. | 4.3% | $355,000 | -7 | 36 | -6.1% | -31.9% |
Jacksonville, Fla. | 4.1% | $323,000 | -12 | 59 | -23.3% | -43.0% |
Baltimore-Columbia-Towson, Md. | 3.2% | $340,000 | -20 | 35 | -6.4% | -51.5% |
Louisville/Jefferson County, Ky.-Ind. | 2.9% | $268,000 | -11 | 35 | -26.7% | -48.9% |
Miami-Fort Lauderdale-West Palm Beach, Fla. | 2.5% | $410,000 | -6 | 93 | -5.3% | -14.0% |
Orlando-Kissimmee-Sanford, Fla. | 1.5% | $325,000 | -8 | 58 | -6.0% | -19.1% |
Pittsburgh, Pa. | N/A* | $250,000 | -10 | 54 | -13.8% | -35.0% |
Los Angeles-Long Beach-Anaheim, Calif. | N/A* | $995,000 | N/A* | 49 | -11.4% | -28.6% |
*Some data points for Los Angeles and Pittsburgh have been excluded due to data quality.
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