Redfin Housing Demand Index Methodology - Redfin Real Estate News

Redfin Housing Demand Index Methodology

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Updated on October 6th, 2020

The Redfin Housing Demand Index is the industry’s first and only measure of housing activity prior to purchase. It is based on thousands of Redfin customers requesting home tours and writing offers in 15 major metro areas. The Demand Index is  seasonally adjusted, with 100 representing the baseline level of homebuyer demand posted in January 2014. All periods thereafter can be compared to one another in a relative sense. For example, a Demand Index reading of 116 in January 2015 implies that homebuyer demand in that month was 16 percent higher than it was in January 2014. Similarly, a level of 120 in June 2018 means that demand was 20 percent higher than it was in January 2014, and roughly 3 percent higher than in January 2015.

Demand Index Timing

Redfin will publish its Demand Index on the last Tuesday of each month at 8 a.m. Eastern time.  The Demand Index will use available information at the time it’s run (the middle of the following month), but due to the smaller sample sizes and variable reporting times from different Metros, the latest Demand Index value for each Metro may be revised on the subsequent release.

Why Redfin

Redfin is the only U.S. real estate brokerage that can track every tour and offer at scale because its agents are employees of the company who all use the same technology platform to track their work and client activity.

Details and Methodology

Tours are weighted by averaging the number of tours per written offer. The index adjusts for Redfin market share growth by taking the raw number of tours and offers in a given month and dividing by an exponentially weighted sum of Redfin’s share of sales over the prior six months. Sales activity outside of the portions of the market in which Redfin operates are accounted for by assuming demand follows a lognormal distribution with respect to price. The undersampled parts of the distribution are filled in using Redfin’s offer and tour information from the well sampled portions, and utilizing a maximum likelihood estimation approach to calculate the parameters of the whole lognormal distribution. This allows us to calculate the shape of the entire demand distribution using our available tour and offer data. Finally, we employ a statistical technique to estimate and remove statistical noise and the predictable seasonal patterns in the data to arrive at a seasonally-adjusted demand series.
15 Metro Areas: Atlanta, GA; Austin, TX; Baltimore, MD; Boston, MA; Chicago, IL; Denver, CO; Los Angeles, CA; Oakland, CA; Orange County, CA; Phoenix, AZ; Portland, OR; San Diego, CA; San Francisco, CA; Seattle, WA, Washington, D.C.
About Redfin
Redfin (redfindevelop.wpengine.com) is the next-generation real estate brokerage, combining its own full-service agents with modern technology to redefine real estate in the consumer’s favor. Founded by software engineers, Redfin has the country’s #1 brokerage website and offers a host of online tools to consumers, including the Redfin Estimate, the automated home-value estimate with the industry’s lowest published error rate for listed homes. Homebuyers and sellers enjoy a full-service, technology-powered experience from Redfin real estate agents, while saving thousands in commissions. Redfin serves more than 80 major metro areas across the U.S. The company has closed more than $60 billion in home sales.
For more information or to contact a local Redfin real estate agent, visit redfindevelop.wpengine.com. To learn about housing market trends and download data, visit the Redfin Data Center. To be added to Redfin’s press release distribution list, subscribe here. To view Redfin’s press center, click here.

For further information

Redfin Journalist Services

Phone: 206-588-6863

Email: press@redfin.com

Sheharyar Bokhari

Sheharyar Bokhari

Sheharyar’s research focuses on better understanding the housing market for audiences inside and outside of Redfin. Prior to joining Redfin, he created commercial real estate sale and rental price indices at the MIT Center for Real Estate. He has also done research on consumer decisions and behavioral biases in real estate pricing. Sheharyar holds a PhD from MIT in Urban and Real Estate Studies.

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