Metro Home Prices Increase in 91% of Metro Areas in Second Quarter of 2019

WASHINGTON (August 7, 2019) – Most metro areas saw price gains under marginal inventory growth in the second quarter of 2019, according to the latest quarterly report by the National Association of Realtors®. Single-family median home prices increased year-over-year in 91% of measured markets in the second quarter, with 162 of 178 metropolitan statistical areas1 showing sales price gains. That is up from the 86% share in the first quarter of 2019. The national median existing single-family home price in the second quarter was $279,600, up 4.3% from the second quarter of 2018 ($268,000).

The metro areas where single-family median home prices declined included the high-cost areas of San Jose-Sunnyvale-Santa Clara, Calif., (-5.3%), San Francisco-Oakland-Hayward, Calif., (-1.9%) and Urban Honolulu, Hawaii (-1.2%). Ten metro areas experienced double-digit increases, including the moderate-cost metro areas of Boise City-Nampa, Idaho; Abilene, Texas; Columbia, Mo.; Burlington-South Burlington, Vt. and Atlantic City-Hammonton, N.J.

Lawrence Yun, NAR chief economist, said home builders must bring more homes to the market. “New home construction is greatly needed, however home construction fell in the first half of the year,” he said. “This leads to continuing tight inventory conditions, especially at more affordable price points. Home prices are mildly reaccelerating as a result.”

Ninety-three out of 178 metro markets under study have price growth of 5% or better. “Housing unaffordability will hinder sales irrespective of the local job market conditions,” Yun said. “This is evident in the very expensive markets as home prices are either topping off or slightly falling.”

Notable Takeaways

The five most expensive housing markets in the second quarter were the San Jose-Sunnyvale-Santa Clara, Calif., metro area, where the median existing single-family price was $1,330,000; San Francisco-Oakland-Hayward, Calif., $1,050,000; Anaheim-Santa Ana-Irvine, Calif., $835,000; Urban Honolulu, Hawaii $785,500; and San Diego-Carlsbad, Calif., $655,000.

The five lowest-cost metro areas in the second quarter were Decatur, Ill., $97,500; Youngstown-Warren-Boardman, Ohio, $107,400; Cumberland, Md., $117,800; Binghamton, N.Y., $119,300; and Elmira, N.Y., $119,400.

In expensive metro areas where the median prices were $500,000 and above, the single-family median prices declined when compared to the levels of one year ago. The most costly area, San Jose-Sunnyvale-Santa Clara, Calif., saw a 5.3% drop. Next in line was San Francisco-Oakland-Hayward, Calif., whose decline was 1.9%. Homes in Urban Honolulu, Hawaii dropped by 1.2%, followed by Boulder, Colo., which saw a 0.9% slide. Bridgeport-Stamford-Norwalk, Conn., recorded single-family housing prices that were slightly down (0.6%) from last year, possibly due to limits on property tax deductions.

In addition, in other expensive metro areas, prices rose, albeit at a lukewarm pace, including in Anaheim-Santa Ana-Irvine, Calif., which rose only 0.6%. Home prices in Los Angeles-Long Beach-Glendale, Calif., saw a 1.8% gain, while San Diego-Carlsbad, Calif., saw a 1.6% price increase.

Second Quarter Affordability Declines

National family median income is estimated to have risen to $78,3662 in the second quarter, but greater home price growth contributed to an overall decrease in affordability from last quarter. A buyer making a 5% down payment would need an income of $62,192 to purchase a single-family home at the national median price, while a 10% down payment would necessitate an income of $58,918, and $52,372 would be required for a 20% down payment.

In the most expensive metro areas in the West, families seeking to avoid paying no more than 25% on mortgage payments saw steep requirements for median household income. San Jose home buyers would need $295,832, while buyers in San Francisco would need $233,552.

At the end of 2019’s second quarter, 1.93 million existing homes were available for sale,3 which is about equal to the total inventory at the end of 2018’s second quarter. Average supply during the second quarter of 2019 was 4.4 months – up from 4.3 months in the second quarter of 2018.

Yun says housing sales should improve, but cautions of greater economic uncertainty. “The exceptionally low mortgage rates will help with housing affordability over the short run. But if the low interest rates are due to weakening economic confidence, as reflected from a correction in the stock market, then the low rates will not help with job growth and will eventually hinder home buying and home construction.”

The National Association of Realtors® is America’s largest trade association, representing more than 1.3 million members involved in all aspects of the residential and commercial real estate industries.

# # #

NOTE: NAR releases quarterly median single-family price data for approximately 175 Metropolitan Statistical Areas (MSAs). In some cases the MSA prices may not coincide with data released by state and local Realtor® associations. Any discrepancy may be due to differences in geographic coverage, product mix, and timing. In the event of discrepancies, Realtors® are advised that for business purposes, local data from their association may be more relevant.

Data tables for MSA home prices (single family and condo) are posted at If insufficient data is reported for a MSA in particular quarter, it is listed as N/A. For areas not covered in the tables, please contact the local association of Realtors®.

1Areas are generally metropolitan statistical areas as defined by the U.S. Office of Management and Budget. NAR adheres to the OMB definitions, although in some areas an exact match is not possible from the available data. A list of counties included in MSA definitions is available at:

Regional median home prices are from a separate sampling that includes rural areas and portions of some smaller metros that are not included in this report; the regional percentage changes do not necessarily parallel changes in the larger metro areas. The only valid comparisons for median prices are with the same period a year earlier due to seasonality in buying patterns. Quarter-to-quarter comparisons do not compensate for seasonal changes, especially for the timing of family buying patterns.

Median price measurement reflects the types of homes that are selling during the quarter and can be skewed at times by changes in the sales mix. For example, changes in the level of distressed sales, which are heavily discounted, can vary notably in given markets and may affect percentage comparisons. Annual price measures generally smooth out any quarterly swings.

NAR began tracking of metropolitan area median single-family home prices in 1979; the metro area condo price series dates back to 1989.

Because there is a concentration of condos in high-cost metro areas, the national median condo price often is higher than the median single-family price. In a given market area, condos typically cost less than single-family homes. As the reporting sample expands in the future, additional areas will be included in the condo price report.

The seasonally adjusted annual rate for a particular quarter represents what the total number of actual sales for a year would be if the relative sales pace for that quarter was maintained for four consecutive quarters. Total home sales include single family, townhomes, condominiums and co-operative housing.

2Income figures are rounded to the nearest hundred, based on NAR modeling of Census data. Qualifying income requirements are determined using several scenarios on downpayment percentages and assume 25% of gross income devoted to mortgage principal and interest at a mortgage interest rate of 3.9%.

3Total inventory and month’s supply data are available back through 1999, while single-family inventory and month’s supply are available back to 1982 (prior to 1999, single-family sales accounted for more than 90% of transactions and condos were measured only on a quarterly basis).

Seasonally adjusted rates are used in reporting quarterly data to factor out seasonal variations in resale activity. For example, sales volume normally is higher in the summer and relatively light in winter, primarily because of differences in the weather and household buying patterns.