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Bold 2021 Predictions: A Stronger Housing Market Across the Board

Bold 2021 Predictions: A Stronger Housing Market Across the Board

The for-sale housing market showed incredible strength in 2020, and we expect 2021 will be even stronger.

Demand continues to stay high, and is expected to surge in cities as economies reopen. Annual home sales growth is expected to be the highest in almost 40 years as life and financial certainty brings more sellers into the market to meet the heavy demand and technology allows for faster connections with interested buyers. Even so, home prices, mortgage rates and rents are likely to rise, bringing affordability challenges that must be faced.

We expect 2021 will be a year unlike any other as the housing market responds to the challenges and changing preferences that emerged in 2020.

Here are our bold predictions for 2021:


Home sales growth will be biggest since the ‘80s

2020 has been a remarkably strong year for the housing market, with sales on pace to grow almost 6% from 2019 despite essentially pressing ‘pause’ for a few weeks in the heart of the spring shopping season. Zillow expects that mark will be shattered next year, forecasting 21.9% annual growth for a total of almost 6.9 million homes sold. That would be the biggest annual sales growth since 1983.

The optimistic outlook is due largely to the enduring strength of the market today, even through what is typically a slower season for home sales, and demographic factors that indicate demand will remain strong. Plus, about a third of homeowners considering selling in the next three years cited life and financial uncertainty as reasons they weren’t selling this fall. The COVID-19 vaccine rollout and expected subsequent economic recovery should pull many off the sidelines, adding more inventory to meet the heavy demand for homes and thus creating more transactions.


Demand for city living will surge in 2021

Dense, urban living got a bad rap this year because of the pandemic, but city living will almost certainly enjoy a renaissance in 2021.

With people pressed into using their homes as offices and classrooms, the age-old tradeoff between more space and proximity to local, urban amenities broke down when those amenities largely shuttered — leading many to believe the demise of cities was imminent. But Zillow research showed that while suburban housing markets did have a slight edge over urban ones, cities were far from dead. Competition for housing was fierce across the board in 2020, with days to pending, list prices and the share of homes selling above list price all rising at a steady clip in both urban and suburban areas.

In 2021, those that may have left cities temporarily during the pandemic will likely return as a vaccine becomes more widely available and local economies begin to open up again. Young adults moved back in with their parents at much higher rates this year than last, with nearly 2 million 18 to 25 years old still living at home in August. The majority of this age cohort tend to be renters and 46% of Gen Z renters tend to rent in urban areas, suggesting that when young people are ready to strike out again they will return to amenity-rich cities.

Rents in urban areas have declined relative to suburban areas, which will also help draw new and returning residents. In some places like New York City and the City of San Francisco, rents fell 12% and 5.1%, respectively. The softening of rents may open up more affordable opportunities for those who left due to deteriorating affordability, or for those who have always wanted to move to the city but shied away due to high rents.


Buyers will have a harder time affording homes, especially their first one

Home price appreciation will reach its fastest pace since the Great Recession, as the inventory crunch continues to pit buyers against each other, competing for a scarce number of homes for sale, and we expect home price appreciation to exceed 10% at points in 2021. Price gains are being driven by the fundamentals of supply and demand: Many would-be sellers are sidelined by anxiety and uncertainty, cumulative new home construction over the last decade has been low, and limited supply is being met by a surge in demand from aging millennials and a wave of other buyers reassessing their housing needs. The pandemic may have accelerated that move for some buyers, but that doesn’t mean a vaccine would send the trend into reverse.

Mortgage payments have become more affordable for homeowners over the past two years thanks to ultra-low mortgage rates. But we expect rapid price growth and slightly higher mortgage rates to reverse that trend in 2021. The anticipation of rising economic growth and rebounding inflation in a vaccinated world economy is already helping 10-year Treasury yields begin to rise out of the doldrums, and mortgage rates are likely to follow if that trend continues. Slightly higher rates would make the argument for ownership a little less compelling for some buyers, but in most of the country it will remain true that homeownership is an attractive financial bargain compared to renting. Don’t expect a few more basis points on 30-year mortgage rates to bring demand crashing to a halt, but it may end up pricing out some buyers already struggling to get onto the homeownership ladder — especially for first-time buyers who don’t have access to funds from the sale of their current home. 


Addressing housing vulnerability will be a top priority as rent prices rise

We expect a rental market resurgence in 2021, with rents increasing, concessions offered by landlords fading and demand for rental housing strengthening.

The rental market softened in 2020, with rents effectively unchanged nationwide from January 2020.  And in large metropolitan areas like New York, Boston, and San Francisco, rents for the typical renter actually dropped for the first time in recent memory.  COVID-driven anxiety about living in large, multifamily housing properties in dense urban centers was a primary driver of the rental market softening, but we expect this trend to reverse in 2021.  With a vaccine on the horizon and Gen Z continuing to graduate from college, we expect the cloud of uncertainty to lift and demand for rental units to surge.

In addition to increased demand, landlords may also attempt to make up for lost revenue by aggressively raising prices. Renters were disproportionately impacted by pandemic-related job losses and furloughs, and missed rent payments were certainly felt by landlords. In 2021, these payments could be capitalized into existing rental agreements, further goosing rent growth, with landlords increasing prices and effectively serving as private lenders to tenants while they work their way out of COVID rental debt. Almost 12 million renters will owe an average of $5,850 in back rent by January 2021, according to Moody’s Analytics.  If landlords allowed renters to repay that debt interest free over a period of 3 years by increasing monthly rents, these 12 million renters would pay an additional $162.50 in rent each month.  Typical renters paid $1,728 in rent in November 2020, according to the Zillow Observed Rental Index (ZORI).  Increasing rents by $162.50 would represent a 9.4% increase for the typical renter.

Increased cash flow for renters — whether in the form of employment income and/or federal stimulus — is needed to both keep renters in their homes and rental housing affordable. Addressing wide-spread housing vulnerability, rent affordability, and potential evictions will need to be a top housing priority for policymakers in 2021. 


Moving will be a digital-first experience

New technology rapidly adopted during the pandemic has made buying, selling, renting, and financing not only safer, but easier. We expect consumer demand will make a digital-first experience the new standard for real estate in 2021 and beyond. 

Take the home shopping experience: Virtual 3D home tours paired with interactive floor plans are allowing shoppers to winnow down their options without leaving their couch. A Zillow survey[1] finds a vast majority of select Zillow Premier Agents (72%) expect to continue using these virtual tools after the current coronavirus outbreak ends. When it comes time to tour a home in person, self-tour technology allows shoppers to tour a vacant Zillow-owned home on their own schedule.

Selling will also increasingly move online with high-tech options like Zillow Offers. The pandemic prompted 43% of people in a Zillow survey[2] to say they were more likely to sell a home entirely virtually.

Renters will also use pandemic-accelerated technology to search, find, apply for, and lease a home all digitally in a safer, easier, end-to-end online transaction.


The next home shopping season will be the hottest in recent memory…

Zillow expects a perfect storm of market conditions to create the hottest spring shopping season in recent memory, with sales happening quickly and often above list priceIt’s likely COVID-19 vaccine distribution will be well underway in the U.S. by the spring, and local economies and schools should be in the process of opening back up. Many will also have more certainty about whether their jobs will be performed remotely in the long term, adding buyers to the market who had been waiting for that to be settled. Add in expectations for mortgage rates to rise later in the year, and we could see a buyer frenzy as they look to lock in rates as low as possible.

… and it could be the last of its kind

Springtime has historically been the best time to list a home for sale, but homes have continued to sell quickly through the fall and into the winter this year in what could be a signal that typical seasonal trends may be fading somewhat. The increased adoption of real estate technology has given home buyers more tools to shop from the comfort of their home, which can be done just as easily during the warmer spring and summer months as it can in the dead of winter. That’s likely to lessen the traditional seasonality of home shopping as it reduces the impact inclement weather can have on things like in-person showings and open houses.

For more information from our partners at Zillow, check out their resources.

After Years of Decline, Household Formation Rates Were Improving Pre-Pandemic. Now What?

After Years of Decline, Household Formation Rates Were Improving Pre-Pandemic. Now What?

  • Americans of every age group and ethnicity are forming households at lower rates than before the Great Recession.
  • The trend of fewer households began to reverse in 2018 and 2019.
  • There would be 5.7 million more households if today’s demographic groups formed households at the same rate they did in 2006.
  • The group with the largest number of missing households relative to 2006 is white 25- to 29-year-olds, whose headship rate dropped from 46.1% to 41.3%. The groups with the largest fall since 2006 in the ability or tendency to form households are Black 25-to-29-year-olds, whose headship rate fell from 48.4% to 39.3%.
  • Even at today’s lower headship rates, there will be 6.4 million more households in 2025, because so many millennials are aging into their late 30s.

There would be some 5.7 million additional households today if Americans formed households at the same rate they did in 2006, a testament to widespread difficulties in securing affordable, accessible housing over the past decade-plus but also a potential indicator of enduring housing demand to come.

Home values nationwide plummeted between 2007 and 2013, taking the U.S. economy with them, but have since come roaring back over the better part of the last decade as the economy gradually recovered from the Great Recession. But this recent years-long housing recovery was missing an accompanying recovery in newly formed households, with the number of households headed by almost every demographic group steadily declining. That decline finally showed signs of leveling off and reversing by 2019, on the eve of the pandemic, but that progress may prove delicate and could delay millions of Americans from striking out and making a home of their own into the next several years.

The simplest explanation for why household formation fell much more quickly over the past decade or so is that for much of that time, Americans faced a handful of unique financial challenges. First, massive amounts of savings and equity were lost in the 2008 financial collapse and subsequent foreclosure crisis, impacting the ability of both older generations to retire and younger ones to shield their children from substantial college debt. At the same time, job opportunities and incomes fell precipitously from 2007-2011, which has long-lasting effects on individuals’ ability and confidence to start a new household. And finally, at points during the recovery (notably from 2015-2017), rapid growth in home prices widely outpaced income growth over the same period, making it difficult to save for a down payment or the often substantial upfront costs of renting. Either way, would-be household heads of virtually all ages remained entangled with other family or roommates instead of creating a household of their own.

By 2018 and 2019, the broadening economic expansion seemingly began to finally outweigh these effects, with most demographic groups — especially twenty- and thirty-somethings — beginning to get their own homes at higher rates closer to historic norms. But even after the turnaround of the past two years, young Americans especially remain much less likely than prior generations to have a place of their own. The effect is most dramatic for 20-to-34-year-olds: Only 35% of this group were household heads in 2019, down from 39.2% in 2006. In other words, only 22.72 million of the 64.5 million total individuals in this group succeeded in becoming heads of their own household.

If this age group had succeeded in creating newly headed households at the same rate as people their age did in 2006, there would be 12% more, or an additional 2,817,000, households on top of that 22.7 million — bringing the total number of 20-to-34-year-old householders to 26 million. To put that in perspective, that “shortfall” of 2.8 million households is more than twice the number of new homes built in the United States in 2019, when 1,386,000 new homes were completed.

Despite the fall in the rate of new household formation, the housing market has still seen significant gains in the number of households, and will soon see even more, largely because of the size of the maturing Millennial generation. Even at 2019’s low age-specific headship rates, the surge of Millennials moving from their low-headship 20s into higher-headship 30s will mean 6.4 million more households by 2025, an increase from 130.5 million to 137 million, using Census population projections.

A Symptom of Slow Building, Eroding Affordability

That the decline in headship rates is so widespread across virtually all groups is a central signal that the housing market is struggling to provide enough affordable homes for all. If the decline in headship was largely limited to just those in their early 20s, that might be explained in part by more people in this group choosing to pursue higher education. But the decline in headship also happened for Americans in their 30s, 40s, and 50s. And within age groups, it is not explained by a changing composition as the population grows more diverse.

The narrative that younger generations are and will be delayed in life’s major events includes the assumption that they will eventually catch up,  ultimately hitting the same milestones as previous generations. But the ever-falling headship rate across all ages changes that narrative, and signals that many more may never hit those milestones, that housing fundamentals have changed and that household formation and homeownership are more difficult. The Great Recession and financial collapse that cost U.S. homeowners roughly $6 trillion in home equity wealth simply sped up the process.

Want More Households? Build More Homes

Home building collapsed during the Great Recession and remained at depressed levels for several years. More new homes were completed in 2019 than in any other year of the past decade, and still there were far fewer homes built last year than in any other non-recession year in the postwar era. Particularly when adjusting for population size, which is key for predicting household formation, we are now building only about 2.6 single-family homes per 1,000 Americans, compared to a historical average of almost 4. Some of the challenges holding back new construction include a shortage of buildable land and the financing to acquire it; shortages of labor, as job openings for construction workers remain unfilled; and onerous permitting processes that add time and cost to the construction process.

On the eve of the pandemic, there were promising signs of a significant rise in new home construction, with new home starts exceeding 1.5 million (annualized) each month from December 2019 to February 2020. Those numbers came crashing down in March but builder confidence has come roaring back, and now October 2020 once again saw construction begin at an annualized pace above 1.5 million homes, suggesting a robust pipeline of expanded housing supply in the near future.

New households are formed by both renters and home buyers, but the first-time home purchase in particular has gotten harder as saving for a down payment in an environment in which home price growth rapidly outpaces income growth gets increasingly difficult. Higher student debt loads and rising rent burdens contribute to savings difficulties. But even if first-time buyers managed to save the same share of their income as their parents’ generation, thanks to rapidly rising home prices and the steady increase in price-income ratios,  it would still take them years longer to save an adequate amount.

Turnaround, interrupted?

Despite the difficulties, progress was being made. Among 25-to-29-year-olds (the age range with the largest shortfall in households in 2017 relative to 2006 rates), the headship rate rose from a low of 37.1% in 2016 to 38.1% in 2019. And the increase was fairly uniform across race: The headship rate for white, Black, Hispanic, and Asian Americans & Pacific Islanders in this age range rose by 1.1, 0.7, 1.0, and 1.3 percentage points, respectively. This suggests that when America experiences a long-enough economic expansion — like the record-long period of growth that ended abruptly in March — then the economic freedom to set out and head a household at 2006 levels may just be within reach.

If and when the economy begins recovering again once the pandemic has passed, it may very well be that the best outcome will show that the decline in headship was only temporary and that demand for homes that may have been satisfied this year will simply be pushed into next year and beyond. Even so, in only a few short months, the pandemic has proven how delicate progress can be. Millions of young adults moved back in with their parents in the early months of the outbreak, and while recent data suggest about half of them have already moved back out, big unanswered questions remain.

Will the rest of Gen Z be able to keep setting out on their own, or remain set back for years to come like Millennials were in the wake of the Great Recession?

Learn more about our partners at Zillow by checking out their blog.

Financial Anxiety, Ongoing Uncertainty Keeping Sellers on the Sideline

Financial Anxiety, Ongoing Uncertainty Keeping Sellers on the Sideline

  • About a third of homeowners who are considering selling in the next three years cite life being too uncertain right now (34%) and financial uncertainty (31%) as reasons they aren’t selling.
  • Nearly 40% of these potential sellers say they anticipate a higher sale price if they wait.

Despite a market tilted decidedly in their favor — with demand sky-high and inventory at rock bottom — potential home sellers are largely staying on the sidelines, citing a variety of personal financial, lifestyle and/or health concerns as major reasons.

Only 1% of homeowners recently surveyed by Zillow said their homes were currently listed for sale. Among the 99% whose homes are not on the market, more than a quarter (26%) said they were concerned they would not be able to find or afford a new home once their current home was sold, the most commonly cited reason for not selling. General life uncertainty (22%) was the second-most common reason, followed by anticipation of a more favorable sale price if they wait (21%).

Reasons for not selling vary by age group: More than a third (35%) of Gen Z and Millennial homeowners said their plans for or completion of a home renovation was a main reason to stay put, compared to just 21% and 14% of Gen X and older homeowners, respectively. Younger homeowners were also more likely to cite concern about COVID-19 (20% of Gen Z and Millennial and 18% of Gen X) as a reason for not selling than Boomer and Silent Generation homeowners (11%).

Some homeowners realistically may simply enjoy their current home and have no need or desire to sell and move any time soon. But among homeowners considering selling within the next 3 years, 39% said they anticipate a better price if they wait. Among those who are not currently considering selling, but may be open to it after 3 years, 39% cite concern that they won’t be able to find or afford a new home.

Concern over finding or affording a new home among those more likely to sell in the near-term was a bit more muted, but still very real: Almost a third (31%) of homeowners considering selling in the next three years say their plans are paused because they are concerned about finding or affording a new home. The findings are a clear example that selling a home can sometimes cut both ways: According to the 2020 Zillow Consumer Housing Trends Report, almost two-thirds (63%) of sellers are also buyers. But while these dual-track homeowners may be able to sell their home for top dollar, they will also turn around and enter an extremely competitive buyers’ market where homes are going under contract in 12 days.

Given the historically low mortgage interest rates that many home buyers and homeowners can enjoy these days, it may come as little surprise that 15% of homeowners report a recent refinance as a reason for staying put — but their planned uses for their newfound financial flexibility are very different. Among respondents that cited a recent refi as a reason to stay put, a majority (54%) said they would use their savings to pay off debt. Exactly half said they would use the savings for home improvements or saving for retirement.

General life uncertainty, especially given the ongoing pandemic, high unemployment and volatile economic conditions, is a main factor keeping more than a third (34%) of those considering selling in the next three years out of the market. Among these homeowners hesitant to put their home on the market now, a quarter said they weren’t selling because they were concerned about their household’s health and safety during the pandemic.

Financial anxiety, again likely attributable at least in part to the pandemic, is another big factor keeping those that might sell sooner on the sidelines: 31% of homeowners considering selling in the next three years said a currently uncertain or precarious financial situation is a reason to stay put. More than a quarter of these would-be sellers (27%) reported a recent change in employment with a decrease in hours or pay, and 17% said they or their spouse/partner were laid off or involuntarily unemployed. Among sellers who may be considering putting their home on the market in the next three years, 6% said they are currently taking advantage of mortgage forbearance programs that allow them to delay or defer monthly mortgage payments.


In this brief, “homeowners” refer to household decision makers who own their primary residence and have not moved in the past year.

Zillow Group Population Science collected a nationally representative sample of more than 1,000 homeowners (household decision makers that own their home and did not move in the past year). From September 29th to October 5th, 2020 the survey asked homeowners questions about their plans to sell and recent life events. Among those who did not have their home listed for sale (99% of the sample), the survey also asked why they were not currently selling.

To achieve national representativeness, quotas for age, ethnicity/race, education, income, region, relationship status, and sex limited oversampling of any given demographic group. In addition to quotas, ZG Population Science used statistical raking to weight the sample to the US Census Bureau American Community Survey 2018 sample of homeowners. Weighting used the same variables as the quotas. Margins of error are at a 95% confidence interval.

For more information from our partners at Zillow, check out their blog.

What are the Top Affordable U.S. Suburbs With a City Feel?

What are the Top Affordable U.S. Suburbs With a City Feel?

Increased opportunities to work remotely are pushing more Americans to rethink how and where they want to live. But even if there’s less of a need to live as close to urban job centers, traditional urban amenities — think restaurants, nightlife, museums and sports venues — remain a big draw and demand for city living remains high. As a result, many buyers may seek places that balance the space and affordability of the suburbs, while still maintaining that big-city feel.

A new “Cityness Index” created by Zillow and Yelp Inc. helps identify the U.S. suburbs that best strike that balance. Key metrics include housing affordability compared to the nearest big cities and to the country at large, housing availability, the mix and diversity of businesses — including restaurants, nightlife and the arts — and consumer reviews and check-ins.

Zillow data shows extremely strong housing demand driven both by incredibly low mortgage interest rates and more millennials and Gen Zers reaching prime home buying age. This desire to move is also reflected in a recent Zillow survey of people newly working from home because of the pandemic, with almost two-thirds of respondents saying they would consider moving if they had the flexibility to work from home occasionally. The opportunity to telework could also give almost 2 million current renters an opportunity to relocate and buy a home in a more affordable area. There very well may be a “Great Reshuffling” on the horizon.

“At Yelp, we’re seeing consumer interest and requests for quotes for categories like movers, packing services and mortgage lenders increase in major metro areas, compared to the same time period last year,” said Yelp Trend Expert Tara Lewis. “For city dwellers who don’t want to sacrifice great amenities like restaurants, art galleries and nightlife, but are dreaming of a little more space and a more affordable lifestyle, these suburbs offer a similar variety of great local businesses.”

This demand is also driving up prices and depleting inventory. But using this data, it is possible for young people looking to buy and find space for their expanding families to bid farewell to big city premiums without giving up the feel of a city in amenity-rich suburbs.

Hundreds of suburbs nationwide were scored on the index, and we identified the highest scorer in each of the 50 largest U.S. metros. Waterbury, Conn., near New Haven and Hartford, topped our list, beating out Lowell, Mass. for the top spot. Filling out the top five are Joliet, Ill.; Sunrise, Fla.; and Pasadena, Texas.

Zillow and Yelp’s top 10 affordable suburbs with a city feel:

10 affordable suburbs with a city feel

1. Waterbury, Connecticut

  • Cityness Index Score: 67.6
  • Typical home value: $139,304

Nestled between New Haven and Hartford, Waterbury has a quintessential New England feel. Downtown Waterbury boasts the historic Palace Theater, the Mattatuck Museum for art lovers and a University of Connecticut satellite campus.

Housing affordability in Waterbury is another advantage — the typical Waterbury home is 30% less expensive than the typical home in New Haven, and 46% less expensive than the typical U.S. home.

2. Lowell, Massachusetts

  • Cityness Index Score: 64.7
  • Typical home value: $323,576

Located near the New Hampshire border about 25 miles northwest of Boston, Lowell offers a great balance of city-like amenities with suburban conveniences. Residents can immerse themselves in the history of America’s Industrial Revolution at Lowell National Historical Park or take a casual stroll along the Merrimack River, which winds through downtown Lowell.

Home values in Lowell are about half those in Boston. Brockton, Mass., also scored highly in our Cityness Index, demonstrating the number of affordable, livable city/suburb options available in the Boston area.

3. Joliet, Illinois

  • Cityness Index Score: 63.8
  • Typical home value: $155,018

Joliet is perhaps best known for being home to the Chicagoland Speedway, but there’s plenty more to this Chicago suburb.

Nearby Aurora almost made the list, but Joliet’s housing affordability advantage gave it the edge. The typical home in Joliet is about 40% less expensive than the typical Chicago home.

4. Sunrise, Florida

  • Cityness Index Score: 60.7
  • Typical home value: $243,078

Minutes away from the beach and the Everglades, natural beauty is never far when you’re in Sunrise. For sports fans, Sunrise is home to the NHL’s Florida Panthers and several golf courses.

Multiple Miami suburbs scored well in our Cityness Index, including Delray Beach and Boca Raton, but none beat Sunrise’s mix of affordability and city-like amenities. The typical home in Sunrise is 36% less expensive than in the city of Miami.

5. Pasadena, Texas

  • Cityness Index Score: 60.5
  • Typical home value: $168,080

About 15 miles southeast of downtown Houston you’ll find Pasadena, home to one of the largest urban wildlife preserves in the U.S.

Pasadena offers an affordability edge over Houston, with the typical home value 14% lower.

6. Lancaster, California

  • Cityness Index Score: 59.3
  • Typical home value: $320,494

Lancaster is located near the north edge of the greater Los Angeles area, within the Antelope Valley. Tens of thousands of visitors flock to the area each year for the California Poppy Festival to view more than 1,700 acres of the state’s official flower.

Housing affordability relative to the area shot Lancaster into the top 10 — the typical Lancaster home value is less than half that in the city of Los Angeles.

7. Hampton, Virginia

  • Cityness Index Score: 58.6
  • Typical home value: $188,373

With the Chesapeake Bay to the north and east and the busy harbor at Hampton Roads to the south, Hampton residents have plenty of options for water and beach activities.

Typical home values in Hampton are almost 60% less than the nearby city of Virginia Beach and 36% less than the U.S.

8. Marietta, Georgia

  • Cityness Index Score: 58.4
  • Typical home value: $318,069

Marietta is about 20 miles northwest of Atlanta, and offers residents easy access to Interstate 75 and everything Atlanta has to offer. This suburb’s spot in the top 10 is due in large part to its affordability. Although typical home values in Marietta are slightly higher than the city of Atlanta, it’s still relatively affordable compared to other nearby suburbs including Canton and Smyrna.

Known for its abundance of nature and parks, the culinary scene rivals that of Atlanta, according to Yelp.

9. Norman, Oklahoma

  • Cityness Index Score: 58.2
  • Typical home value: $180,833

Home to the University of Oklahoma, Norman offers a small-town atmosphere with a vibrant nightlife and plentiful coffee shops and parks. Yelp users also give the local restaurant scene high marks. Homes in Norman are generally more expensive than those in Oklahoma City, but remain more affordable than the typical U.S. home.

10. Tempe, Arizona

  • Cityness Index Score: 57.9
  • Typical home value: $327,963

Just east of Phoenix and home to Arizona State University, Tempe is known for a bustling performing arts scene. Locals and tourists alike also enjoy soaking in the surrounding scenery while kayaking and paddleboarding at Tempe Town Lake.

Tempe home values are up 10% from last year, indicating a strong housing market. Listings are also up nearly 3%, offering extra housing options available on the market.


The Cityness Index is designed to highlight cities with vibrant amenities and relatively affordable housing, which result in a city-like environment in a more-affordable suburban region. Any city not included in the official name of a metropolitan area, as defined by the U.S. Census, were counted as a suburb in this analysis. The highest-scoring suburb in 50 of the largest U.S. metro areas were considered, with the highest scores among those making it into the final top 10 list of the most city-like suburbs.

There were four individual Yelp indicators evaluated for each suburb to determine its cityness.

  1. A mix of businesses similar to major cities
  2. A diversity of restaurant and nightlife businesses
  3. A diversity of arts businesses
  4. A high level of consumer activity

Among these, the mix of businesses indicator was given most weight.

The mix of businesses were found by comparing the distribution of open businesses across its major business categories, such as home services and restaurants, in each candidate city with the average distribution in several of the largest U.S. cities. Diversity of business type was measured across two sectors: (1) restaurants, food, and nightlife; and (2) the arts. Suburbs were compared by how many unique types of businesses, such as piano bars or diners, are present. Consumer activity was measured as the number of page views, reviews, and photos per business.

Zillow analyzed five main variables. The most impactful variables were targeting affordability of these suburbs compared to the principal cities in the metropolitan area and the US overall:

  1. Ratio of typical home values in the suburb compared to the principal cities, defined as those named in the official Census MSA name (e.g., Dallas, Fort Worth and Arlington home values were used for comparison in the Dallas-Fort Worth-Arlington metro)
  2. Ratio of typical home values in the suburb compared to the national median

The other housing related variables were targeting the availability of for sale, new for sale, and rental inventory:

  1. Ratio of new for sale inventory in the suburb compared to the principal cities
  2. Ratio of rental inventory in the suburb compared to the principal cities
  3. Ratio of existing for sale inventory in the suburb compared to the principal cities

In each of the Zillow variables, multi-unit housing was given extra weight in calculating inventory to emphasize housing availability in more dense, city-like parts of town.

The collection of Yelp indicators and Zillow variables were each given 50% of the overall weight for the final index. Scores reflect data from June 2020 to August 2020.

Freedom to Telecommute Could Add Almost 2 Million Potential Buyers to the Market

Freedom to Telecommute Could Add Almost 2 Million Potential Buyers to the Market

  • A switch to more telework could give 1.92 million U.S. renters (4.5% of renter households) the option to leave the metropolitan areas where they currently live and buy a starter home in a cheaper locale.
  • Starter homes are more expensive than the nation as a whole in 37 of the 50 largest U.S. metros.
  • Fleeing from a metro’s central city to it’s suburbs is not as broadly beneficial. The markets where the largest share of renters in the center city would gain the power to buy if they looked outside city limits are San Francisco, Seattle, Washington, D.C., and Boston.

Almost 2 million U.S. renters that currently can’t comfortably afford to buy an entry-level home in their current metro area could potentially afford the nation’s typical starter home if they took advantage of increased telework options and moved to a less-expensive locale.

Zillow analyzed renter households for whom monthly payments on a starter home in their metro are unaffordable, but would be affordable on the typical U.S. starter home. Those households were then assigned a probability of being able to telecommute based on income, the worker’s industry and occupation. Millennials, between 26 and 40 years old, represent almost half of the 1.92 million renter households who could afford homeownership if given the flexibility to work from home, the largest generational group to potentially benefit from these new options.

Nationwide, the typical starter home is currently valued at $131,740. But similar starter homes in 37 of the nation’s 50 largest metro areas — home to the lion’s share of the country’s jobs — are more expensive than in the country at large, often by a wide margin. As a result, owning even a modest home (and taking advantage of the wealth-building opportunities that can bring) is out of reach for many households as long as they need to be within commuting distance of a physical workplace.

Rethinking the Relationship Between Work & Home

Close to half (43.6%) of U.S. workers are in occupations in which teleworking is at least theoretically feasible, though less than a quarter of these workers actually telework. But the ongoing pandemic has shaken up how workers and their employers alike think about the relationship between work and home. Over the past six months, many companies have found that their workforce can function better remotely than originally thought.  If telework becomes more of a norm, and businesses allow it where possible, this could give millions of Americans more choice over their home and home finances.

Among the country’s largest metros, the San Francisco Bay Area is home to the most renters who could maybe leave and buy a home elsewhere if telework became the norm — perhaps unsurprisingly, given how expensive the area is relative to both the U.S. and most other large metros. In the San Francisco and San Jose metro areas, 22% and 25.2% of local renters, respectively, would be able to leave the area and buy a home in a cheaper local if telework were an option — almost a quarter million renters total. Los Angeles (17.2% of renters could leave and buy a starter home elsewhere), San Diego (15.4%) and Denver (14.6%) round out the top 5 list of large markets in which the largest share of renters could afford a home elsewhere.

But while homes in most of the nation’s largest 50 metros are more expensive than the U.S. at large, home values for starter homes in 13 of these areas are less than the U.S. median — leaving residents in those areas little incentive to leave and buy a starter home elsewhere.

From the City to the Suburbs

Still, despite whatever financial advantages may be in play, many renters may rightly choose not to move for any number of personal reasons — they simply might prefer to rent in a bustling city like New York, rather than own in a sleepier rural area in another state. And while it may make sense on paper to move far from a given area to be able to afford homeownership, practically speaking it can be very difficult to completely uproot and move away from family, friends and valued local cultural institutions (sports teams, schools, museums etc.).

As such, in many cases, it may be far more likely that current residents can’t or won’t flee and cut the cord with their hometown entirely, and instead exchange it for an extension cord — moving from the commute-friendly center city to farther-flung suburbs, but still maintaining ties. But the affordability benefits in moving from the city to the suburbs, rather than from one metro area to an entirely new, cheaper one, are less-pronounced.

A starter home is worth more in a metro’s namesake city than it is in the metro as a whole in only 20 of the nation’s 50 largest metropolitan areas (and in just 11 of the 27 metros where income data was available on occupations at the city level). In cities including Minneapolis, Phoenix and Denver, a starter home is more affordable than in the larger metro area, leaving city residents with no real price incentive to leave for the suburbs. And relatively affordable starter homes (within the context of the metro) are what separate Los Angeles and San Jose from San Francisco, and Portland from Seattle. In San Francisco and Seattle a large share of renters currently living in the city could telework and buy a starter home outside the city (10.4% and 8.4% respectively). In Los Angeles and Portland it’s a much smaller share (0.8% and 1.6% respectively).


A home is assumed to be not affordable for those households in which expected monthly payments on a starter home (assuming a 30-year, fixed-rate mortgage with a 3.0% interest rate and 20% down, plus estimated taxes, insurance, HOA dues) are greater than 30% of household income. We compared the bottom-tier (referred to here as “starter/entry-level”) Zillow Home Value Index for the United States and for individual large metros. Many cities are not identified in ACS microdata and were excluded from the city-level analysis.

Households were assigned a probability of being able to telecommute by income weighting individual earner probabilities. Individual probabilities were derived from an intersection of the probabilities by worker’s industry and occupation presented in this BLS analysis of American Time Use Survey data. The denominator is the total number of renter households.

Urban Rent Slowdown May Signal Renters are Edging Toward the Suburbs

Urban Rent Slowdown May Signal Renters are Edging Toward the Suburbs

  • U.S. rent growth has slowed this spring as heavy unemployment hit renters harder than homeowners.
  • Rent price growth in urban ZIP codes has slowed more than those in suburban areas since February, one outcome of unemployment affecting urban renters particularly hard and a possible signal that preferences are shifting in favor of the suburbs.
  • The split between urban areas and the suburbs is largest in Dallas-Fort Worth, Sacramento, San Francisco and the greater New York metro.
  • Conversely, urban rent growth has been stronger than the suburbs in several metros, led by Kansas City, Detroit, Baltimore and Riverside.

While the for-sale market has shaken off the early impact of the coronavirus pandemic and resumed its torrid pre-pandemic pace, rent growth hit the brakes this spring. Rent prices in urban areas have slowed more than those in suburban areas, a possible signal that renters’ preferred location is tilting toward the suburbs.

Rents were chugging along at a stable pace into the early part of this year, but the spike in unemployment has hit renters more severely than homeowners, and millions have moved back in with parents or grandparents, impacting demand for rentals. That’s caused the rate of rent growth to slow from February to June.

During that period, rent price growth has slowed more in urban ZIP codes than in the suburbs — annual rent growth has slowed two percentage points in urban areas, compared to 1.4 percentage points in suburban areas. That is a subtle split, but it goes against the trend seen just before COVID-19 hit the U.S., indicating the shift was influenced by the pandemic. Contributing to this are urban renters who have lost their jobs, are missing rent payments or are moving home in greater numbers than their suburban counterparts, and suburban rentals may now be more appealing for renters who no longer need to commute or are temporarily unable to enjoy some of the amenities of urban living.

Renters usually have more flexibility than homeowners given their relatively short lease terms, and rent prices are often quicker to move as a result. Search traffic data does not yet show home shoppers are more interested in suburban homes than in past years, and both areas are seeing similar home-value growth, time on market, sales above list price and rate of newly pending sales. Survey results, however, indicate working remotely is causing many to reconsider their options. If this early shift in the rental market is indicative of a more widespread change in preferences, similar changes to the for-sale market could follow, but the economic impact on urban renters may be playing a larger role.

It’s important to separate how much of the trend is coming from shifting tastes as opposed to the economic reality that renters face. It may be tempting to conclude that urban renters who have been cooped up without outdoor space and unable to visit their favorite local bar are ready to commit to suburban life, and that is likely true for many. But that narrative ignores the fact that urban areas have been affected by job loss more so than suburban and rural areas, particularly renters who are disproportionately employed in the industries most affected.

This split between urban and suburban rent growth was present in more than half of large U.S. metros studied. The biggest gaps were in Dallas-Fort Worth, Sacramento, San Francisco and the greater New York metro.

Not all markets are following this pattern. Urban rent growth has been stronger than suburban growth in some metros, and that difference is biggest in Kansas City, Detroit, Baltimore, Riverside and St. Louis. Rents in both urban and suburban areas of Kansas City are accelerating, but urban rents are to a greater degree. Baltimore rent growth was softening before the pandemic, and has continued on that trajectory.

United States 1.60% -2.00% 2.40% -1.40% -0.60%
New York, NY 0.10% -3.80% 2.00% -1.30% -2.50%
Los Angeles-Long Beach-Anaheim, CA 1.20% -2.50% 1.20% -2.10% -0.40%
Chicago, IL 1.40% -1.30% 1.30% -1.70% 0.40%
Dallas-Fort Worth, TX 0.00% -3.70% 2.50% -0.50% -3.20%
Philadelphia, PA 2.20% 0.10% 1.80% -1.10% 1.20%
Houston, TX 0.00% -1.90% 0.40% -0.90% -1.00%
Washington, DC -0.10% -3.00% 1.00% -1.80% -1.30%
Miami-Fort Lauderdale, FL 1.80% -0.90% 2.30% -0.90% 0.00%
Atlanta, GA -0.50% -2.00% 4.20% 0.00% -2.00%
San Francisco, CA -2.20% -3.90% 0.80% -1.30% -2.70%
Detroit, MI 4.40% 1.40% 2.00% -0.80% 2.20%
Riverside, CA 4.90% 1.00% 3.80% -0.80% 1.80%
Phoenix, AZ 6.30% -3.20% 6.00% -2.80% -0.40%
Seattle, WA 1.90% -4.30% 2.00% -3.40% -1.00%
Minneapolis-St Paul, MN 2.30% -1.50% 1.70% -2.30% 0.70%
San Diego, CA 2.80% -1.90% 1.50% -2.20% 0.40%
St. Louis, MO 4.20% 0.80% 3.20% -0.90% 1.70%
Tampa, FL 2.20% -2.10% 3.70% -0.90% -1.20%
Baltimore, MD 1.40% -0.20% 0.50% -2.30% 2.10%
Denver, CO 0.50% -3.30% 0.80% -2.60% -0.70%
Pittsburgh, PA 1.60% -3.80% -1.60% -2.40% -1.50%
Portland, OR 2.30% -1.10% 2.60% -1.90% 0.80%
Charlotte, NC 3.40% -0.70% 3.00% -1.60% 0.90%
Sacramento, CA 3.50% -2.70% 3.80% 0.30% -3.00%
San Antonio, TX 1.50% -2.00% 1.90% -1.30% -0.70%
Orlando, FL 0.40% -3.60% 1.50% -2.40% -1.20%
Cincinnati, OH 4.20% -0.80% 3.00% -1.80% 1.00%
Cleveland, OH 4.90% 1.70% 2.80% 0.10% 1.70%
Kansas City, MO 3.70% 1.20% 2.50% -1.20% 2.40%
Las Vegas, NV 2.40% -3.90% 2.00% -3.40% -0.40%
Columbus, OH 3.80% 0.20% 2.90% 0.10% 0.10%
Indianapolis, IN 5.40% -1.00% 3.60% -0.70% -0.30%
San Jose, CA -0.90% -4.20% -0.70% -3.80% -0.40%
Austin, TX -0.10% -3.20% 1.80% -2.80% -0.40%
No Bargains in Sight as Home Prices Show Little Impact from Coronavirus

No Bargains in Sight as Home Prices Show Little Impact from Coronavirus

  • The median sale price was up 4.6% year-over-year in May, to $263,408.
  • Most major metros saw a slight deceleration in sale price growth from April to May
  • A resurgence of more-expensive listings, low price cuts, and record-low days on market are all expected to sustain upward pressure on sales prices.

The median price of U.S. homes sold in May was $263,408, up 4.6% year-over-year. But May was also the second straight month in which annual growth was slower than the month prior — definitively snapping an almost year-long period of continuous acceleration that began in April 2019 and peaked in March at 5.5%.

Annual growth in median sale price was slower in May than in April in 31 of the nation’s 50 largest metros, though the deceleration was generally small. The biggest slowdown was in Providence, down 2 percentage points in May from April (from almost 9.2% to just slightly more than 7.1%). San Jose was at the opposite end — annual growth in the heart of Silicon Valley was 2.1 percentage points faster in May than in April (to 5.3% from 3.2%).

The data make clear that despite the nationwide shockwaves generated by the coronavirus pandemic, home prices haven’t been hit to the same degree as other sectors of the economy — at least for now. And because closed sales obviously lag active listings, we can expect sales prices to reflect the relative stability and growth of median list prices that we’ve seen over the past few months. Sale prices increased year-over-year in May in all 50 of the nation’s largest metros.

Still, the pandemic has had a small but noticeable impact on prices. In mid-April, inventory of available homes to buy hit its low-point as stay-at-home orders temporarily paused home transaction activity. Initially, listings of the most-expensive homes fell the most, skewing the distribution of homes actually available for sale toward those in lower price ranges. It’s likely we’re seeing the impact of the closed sales of those lower-priced homes reflected in May’s deceleration in the median sale price.

Recent data point to continued stability in sales prices. By early June, as inventory recovered from April lows, listings at more expensive price points surged back to levels close to last year’s, while lower-priced listings remained depressed. Sellers are also consistently holding firm on their asking prices — just 4.1% of active listings in the last week of June had undergone a price cut, compared to 5.6% of listings a year earlier. And with homes typically selling just 20 days after hitting the market — the lowest level ever recorded by Zillow — sellers have little incentive to slash prices. All of these upward pressures on list prices will likely carry through to sales prices in the coming months.

As spring turns to summer, buyers currently in the market and expecting to score a bargain from desperate sellers may be in for a rude surprise. Zillow listing metrics clearly point to the fact that, despite challenges posed by the pandemic, it remains a very competitive homebuying season — ever-low inventory is no match for buyers’ pent-up demand. Steady sales prices are a final confirmation of this trend.

Experts: Spring’s Missing Home Sales Will be Added to Coming Years

Experts: Spring’s Missing Home Sales Will be Added to Coming Years

  • In a survey of 106 economists and real estate experts conducted by Pulsenomics and Zillow, 41% of panelists expect the U.S. recovery will follow a ‘U’ shape, with the recession lasting several quarters before returning to growth.
  • Once the pandemic begins to subside, experts agree, there will be an increase in demand for suburban and rural living.
  • On average, panelists expect home values to decrease 0.3% in 2020, a sharp decline from expected growth of 3.3% when surveyed three months before.

When coronavirus turned the economy upside down, anxiety and uncertainty about the future initially kept many homebuyers and sellers at bay. Inventory and sales have picked up over the past month, though, and a panel of housing experts and economists say the U.S. housing market hasn’t lost those missing springtime transactions for good.

The Zillow Home Price Expectations Survey, sponsored by Zillow and conducted quarterly by Pulsenomics LLC, asks more than 100 economists, investment strategists and real estate experts for their predictions about the U.S. housing market. The Q2 survey focused on the impact of coronavirus on the market and expected recovery patterns, and also asked for predictions on how the pandemic will shape home-buying decisions in the future.

Coronavirus and subsequent stay-at-home orders resulted in lower-than-expected transaction volume during what was primed to be a busy spring home shopping season. While it was thought the spring buying season could shift to the fall, the pandemic effects are poised to continue into summer and only 10% of the survey panelists said they believe those transactions will materialize later in 2020. More than twice as many experts (22%) said they expect a “double up” during next spring’s shopping season, and the vast majority predicted that recovery will be spread out over the next several years.

ZHPE results, Q2 2020 coronavirus

This prediction is in line with how the experts expect the U.S. economy to recover overall. Forty-one percent said they think economic recovery will follow a ‘U’ shape, and 33% say it will be a bumpy, multi-year return back to trend growth. Both patterns are characterized first by a sharp decline and then match how experts see transaction volume recovering, with the consensus generally being a more gradual journey back to normal.

Prices nationally are now projected to fall 0.3 percent this year according to the panel-wide average forecast — down from an expected increase of 3.3 percent just three months ago.

“This is the first time since 2012 that the panel-wide price outlook has turned negative, and the quarter-to-quarter swing in expectations is the largest we’ve seen in more than a decade,” said Terry Loebs, founder of Pulsenomics. “Longer term, the outlook for home values nationwide is mixed — price projections for 2022 and beyond actually inched higher from levels recorded prior to the Covid-19 outbreak. However, nearly seven in ten experts now indicate that their five-year forecast has downside risk. Last quarter, fewer than four in ten panelists foresaw downside — of course, that was before the Covid-19 crisis, its economic devastation and unprecedented government response.”

Zillow’s own forecast calls for a 1.8% drop in home prices by October 2020, expecting home prices to return to Q4 2019 levels by the Q3 2021. While predictions on home prices continue to steepen, the outlook on pending home sales continues to become more optimistic, and Zillow now shows sales hit bottom in April with a 44% drop, and are on their way back up, compared to the original forecast of a 60% dip.

Experts’ forecasts on the future of housing vary widely at this early stage of the recovery. Zillow’s own forecast has become more optimistic as we ingest new data and watch pending sales pick up faster than expected. What does seem more consistent in this wisdom of crowds is that full recovery is a couple years away — much faster than in the last housing downturn — and remote work will eventually work its changes on the housing market.

Experts also said that where people choose to live will look a little different once the pandemic subsides. Panelists predict future homebuyers will show more interest in suburban and rural areas, at the expense of urban density. Previous Zillow research has indicated that a future that sees more people working from home could make the suburbs more appealing, and the panelists echoed the likelihood of this demand. Although panelists believe there will be a shift in location preference after coronavirus, they also say buyers will want larger homes equipped with home offices moving forward. Stay-at-home orders quickly emphasized the need for more space while stuck at home, and panelists think more space will be a determining feature for future home-buyers.

Even with lower sales volumes compared to 2019, the U.S. housing market has shown resilience during the pandemic and has already begun to rebound. Pending sales are up 40.8% in the past month, and new home sales in April were up 0.6% from March.

Year      Average Home Value Growth Expectations – Q1 2020 Survey Average Home Value Growth Expectations – Q2 2020 Survey
2020 3.3% -0.3%
2021 2.7% 0.9%
2022 2.7% 2.9%
2023 3.0% 3.3%



This edition of the Zillow Home Price Expectations Survey surveyed 106 experts between April 28, 2020 and May 15, 2020. The survey was conducted by Pulsenomics LLC on behalf of Zillow, Inc. The Zillow Home Price Expectations Survey and any related materials are available through Zillow and Pulsenomics.

Web Visits to For-Sale Listings Rebounding as Spring Unfolds

Web Visits to For-Sale Listings Rebounding as Spring Unfolds

  • Page views on for-sale listings on Zillow fell as much as 19% year-over-year in mid-March, but have rebounded sharply since then.
  • Traffic on listings in some metros have recovered more quickly, including Los Angeles, Houston, Dallas and Atlanta.

Web traffic to for-sale home listings on Zillow fell off dramatically in mid-March as the U.S. coronavirus outbreak began in earnest and stay-at-home orders were expanded, effectively shuttering large parts of the economy. But by mid-April, overall visits to for-sale homes had rebounded to levels — perhaps surprisingly — that are actually slightly higher than a year ago.

In early March, the market was still looking forward to the impending busy spring home shopping season. Market fundamentals were largely strong, and traffic to for-sale listings was higher than it was at the same time a year ago. But starting March 11, web traffic began to slide. Even in a month jam-packed with bad news, that date stands out. On March 11, the World Health Organization officially classified the coronavirus outbreak as a global pandemic; President Trump announced a travel ban from Europe as part of a televised national address; and the National Basketball Association cancelled the rest of its season. Over the next week and a half, culminating on March 22, traffic to homes listed for sale on Zillow dropped by almost a fifth compared to the comparable week in 2019.

But not every market dropped in tandem. In Seattle, home to Zillow headquarters and site of some of the first known U.S. cases of community transmission of the novel coronavirus, traffic was below-normal as early as February.

The New York metro area, now home to the nation’s biggest outbreak, has experienced some of the biggest daily traffic declines: It fell more than 30% for the 7-day period ending March 22, and remained down about 24% in the first week of April. The most recent available data, for the 7 days ended April 13, show New York still down about 8%. Late-March/early-April traffic to listings in the Boston area, also currently grappling with one of the nation’s largest outbreaks, fell more than 20% by the week ending March 20 and remained below that depressed level through April 8, when it began to recover toward normal levels.

San Francisco experienced a more acute drop than Boston, down about 28% for the week ending March 22 and subsequent 7-day windows through March 26. But it recovered steadily soon after that, and in the week ending April 13 verage traffic was higher than the same week in 2019.

The traffic dropoff was less severe in Los Angeles, with a nadir 20% lower than 2019 for the week beginning March 16, the same day the LA Department of Public health issued an order prohibiting gatherings of 50 or more. But traffic to Los Angeles-area listings on Zillow subsequently rebounded quickly, and has actually been substantially higher year-over-year through the first two weeks of April.

It’s a similar story in Minneapolis, which was experiencing strong year-over-year growth in traffic in the days prior to March 11, before dropping off sharply. Minneapolis’ biggest one-week drop in traffic also came on the week starting March 16, the day Minnesota Governor Tim Walz ordered restaurants, bars and other public gathering areas closed. But by mid-April, Zillow traffic was up by double-digits in the twin cities.

While traffic to listings in some markets still remains down from a year ago, the national total has rebounded significantly, up 13% year-over-year for the week ending April 13. In fact, in 30 of the 35 largest metro areas, web traffic to for-sale listings was up year-over-year during the second week of April. Of those large markets, only the Pittsburgh, Detroit, Philadelphia, Boston, and New York City metro areas continue to show depressed traffic.

It’s impossible to know precisely what’s driving this recent spike in traffic: It could be coming from optimistic buyers hoping to get an early jump on their plans as soon as restrictions are lifted, or simply from aspirational viewers stuck at home and seeking an escape through real estate. Early data on home sales show significant drops in mortgage purchase applications in March, so one simple explanation could be that many of the home shoppers who would have bought in March are still on the sidelines, keeping tabs on the market alongside everyone who began eyeing Zillow listings in April.

We do know this April turnaround does not reflect positive economic news. In the four weeks from March 15 through April 11, roughly 22 million Americans filed claims for unemployment assistance, or almost 15% of all workers who were otherwise employed as recently as the middle of March. The total scale of the economic slowdown is not yet clear, but it is almost certain that more people will soon be out of work for an indeterminate period of time.


All page view events of for-sale homes on and the Zillow app are tabulated by day and the listing’s ZIP code, and then aggregated to day and MSA. Figures are presented as rolling 7-day trailing averages to smooth out daily noise. Page views exclude real estate agents and other professional users on Zillow. Year-over-year comparisons are done after offsetting 2019 data by 2 days, in order to compare the same days of the week, e.g. we compare Sunday, March 29, 2020 with Sunday, March 31, 2019.


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Information From Past Pandemics, And What We Can Learn: A Literature Review

Information From Past Pandemics, And What We Can Learn: A Literature Review

The United States has officially entered a bear market, with major financial indices falling by more than 20% since the beginning of the year. The market has fallen in response to a mix of information, including global community spread of the Novel Coronavirus COVID-19, a travel ban for Europeans into the US, and general uncertainty about a fiscal response to the virus.

Zillow Research conducted a deep dive into past research and data on the economic effects of global pandemics to help provide perspective on what the future could hold under various scenarios. We found the following main quantitative patterns:

  • During epidemics such as the 1918 influenza or the 2003 SARS outbreaks, economic activity fell sharply during the epidemic (a 5-10% temporary hit to GDP or industrial production over the course of the epidemic) but snapped back quickly once the epidemic was over.
  • This pattern differs from a standard recession, which is a situation in which economic activity falls for 6-18 months and then recovers more slowly.
  • During SARS, Hong Kong house prices did not fall significantly, but transaction volumes fell by 33-72% as customers avoided human contact (“avoidance behavior” like avoiding travel, restaurants, and public gatherings). After the epidemic was over, transactions snapped back to normal volumes.
  • During the current episode in China, early news reports indicate that home prices have so far not fallen but transactions have nearly ceased.
  • During standard recessions, home prices and transaction volumes may fall but this is not always the case (e.g. the 2001 recession).
  • Before February 2020, leading economic indicators (job openings, the yield curve, interest rate spreads, and sentiment indicators) were giving mixed signals about the risk of a standard recession this year, with betting markets (PredictIt, 2020) giving probabilities ranging from 30% in December 2019 to 15% in January 2020, rising to 44% as of March 1. PredictIt defines a recession as at least two consecutive quarters of falling GDP.
  • It is difficult to precisely forecast the probability of an epidemic-related downturn and/or how such a downturn could provoke a standard recession because this depends on how COVID-19 progresses and how this progress interacts with preexisting recession risks and policy responses (ranging from doing nothing to shutting down entire cities for months at a time).

Digging Deeper – Insights From Historical Data and From the Literature

Empirical research into the SARS and 1918 influenza pandemics both indicate a significant loss in output during the time of the pandemic. Hong Kong lost 5.1% of monthly output during the 5 months of the SARS epidemic (or 1.75% of annualized GDP) and the US lost between 7% and 9.5% of monthly industrial production during the 1918 influenza epidemic, with an effect on annual GDP of 0.5%. The effects vary by sector–the epidemics led to people curtailing unnecessary social activities and curtailing human contact, which led to larger falls in services and (semi-)durable goods, while the effect on manufacturing is influenced by trade spillovers.

Since consumers wish to avoid nonessential human contact, the 2003 SARS pandemic led to a temporary fall in monthly real estate transactions from 33% to 72% vs. baseline for the duration of the epidemic, while real estate prices held steady.

Meanwhile, during the current episode in China, news reports and early data provided by Goldman Sachs (2020) indicate a near-shutdown in the volume of Chinese real estate transactions, although there is not yet a clear effect on real estate prices.

Zillow Economic Research (2020) Hong Kong, SARS, 2003 Aggregated macro data 1.75% loss in annualized GDP, or 5.1% monthly loss at peak. Quick recovery to trend after end of pandemic. 1.3% increase in unemployment; unemployment recovered within 3 quarters. Statistically insignificant 1.9% fall in home prices, count of transactions down by an average of 33% for duration of pandemic.
Lee and McKibbin (2012) Multiple countries, SARS, 2003 Theoretical model 2.63% loss in annualized GDP for Hong Kong, 1.05% loss for China. Size of loss depends on policy response.
Wong (2008) Hong Kong, SARS, 2003 Micro data on 44 housing estates 1.6% fall in home value, 2.8% in infected areas. 72% fall in transactions volume.
Siu and Wong (2004) Hong Kong, SARS, 2003 Disaggregated macro data Shift to at-home consumption, away from travel, restaurants, and entertainment. Trade was mainly unaffected.
James and Sargent (2006, 2006a) Canada and US mild flu pandemic Aggregated macro data Loss of Canadian industrial production of 1.2% at peak of epidemic (Oct 1957). 0.3% to 1.1% of annualized GDP. Coincided with a recession.
CBO (2006) US, mild flu pandemic Theoretical model 1% loss of annualized GDP.
Keogh-Brown et al. (2010) UK, mild flu pandemic Theoretical model 0.6%-2.5% loss of annualized GDP, depending on how customers shift their consumption behavior.
James and Sargent (2006) US, severe flu pandemic Aggregated macro data 1918 flu saw annual GDP impact of 0.5%, with loss of 7% of monthly industrial production at peak (Oct 1918). Coincided with drawdown surrounding end of World War I and a recession.
CBO (2006) US, severe flu pandemic Theoretical model 4.25% loss of annualized GDP.
McKibbin and Sidorenko (2006, 2006a) US, severe flu pandemic Theoretical model 5.5% loss of annualized GDP.
Cooper (2006) US, severe flu pandemic + trade disruption Theoretical model 6% loss of annualized GDP, of which 1.75% is due to trade disruption.
Zillow Economic Research (2020) US, severe flu pandemic, 1918 Aggregated macro data 9.5% loss in industrial production in October 1918 (peak of epidemic) vs. July 1918, but less reliable data on other sectors.
Kennedy, Thompson, and Vujanovic (2006) Australia, severe flu pandemic Theoretical model 6% loss of annualized GDP.
Douglas, Szeto, and Buckle (2006) New Zealand, severe flu pandemic Theoretical model 5-10% loss of annualized GDP.
Keogh-Brown et al. (2010) UK, severe flu pandemic Theoretical model 4.5%-6% loss of annualized GDP, depending on how customers shift their consumption behavior.

Case study: SARS in Hong Kong (2003)

The SARS epidemic began in the Guangdong province of China in November 2002. In February 2003, the first confirmed cases appeared in Hong Kong. The epidemic peaked in March and April 2003 and trailed off during May and June, until Hong Kong was removed from the WHO’s list of affected areas on June 23.

The chart below shows how real GDP and unemployment evolved before, during, and after the SARS epidemic. GDP data are shown as a percent relative to a Q4 2001 baseline. Both datasets are obtained from the Hong Kong Monthly Digest of Statistics, various issues.

Hong Kong GDP growth during the SARS outbreak

Until the onset of SARS in February, GDP was growing and unemployment was falling, consistent with an economic expansion. Then, GDP fell precipitously throughout the duration of the epidemic (by our estimation, 5-6% below trend in April and May), and unemployment rose from 7.4 percent to 8.7 percent, for a 1.3 percent increase. Once the epidemic subsided, GDP snapped back to its pre-epidemic trend, while unemployment took until the winter to recover. Altogether, the total gap between actual and trend GDP during this period is consistent with a loss of 1.75% of annual GDP as a result of SARS, which when spread over 4 months instead of 12, represents a fall in monthly GDP of 5.1%.

This loss is slightly smaller than (but of the same order of magnitude as) the model-based projections of Lee and McKibbin (2012), who predict a larger effect of the disruptions to economic activity caused by the epidemic. Lee and McKibbin simulate such an epidemic using a theoretical model (the “G-cubed” model), and they predict a loss of 2.63% of annual GDP for Hong Kong as a result of the SARS epidemic, versus a loss of 1.05% of annual GDP for China. Lee and McKibbin find that their larger loss prediction is driven by the behavior of macro policy in their model. If macro policy responds effectively to an epidemic, then the loss in output would be smaller than if it did not respond.

We also have data on the behavior of real residential real estate prices and the volume of secondary residential transactions. The chart below shows a real residential real estate price index compiled by the Bank for International Settlements (BIS) (2020), as a percent relative to a Q4 2001 or November 2001 baseline. It also shows raw transaction counts of secondary residential real estate transactions, not seasonally adjusted, from Midland Realty (2020).

Hong Kong real estate market during the SARS outbreak

By the time that SARS hit in February 2003, the Hong Kong real estate market had already experienced a downward trend in transactions and in a real residential price index. Between February and May 2003, transactions were 33% below their January 2003 value, before returning to normal by July. We note that this fall is difficult to distinguish from the preexisting downward trend. Meanwhile, real property prices fell to 1.9% below trend in May and then recovered, although this fall is difficult to distinguish from other real estate price swings that are unconnected with SARS.

Elsewhere in the literature, Wong (2008) comes to similar conclusions with respect to house prices. She finds, based on transactions data covering 44 housing estates, that the onset of SARS coincides with a 1.6% decrease in house prices versus a pre-SARS trend (which is comparable with our 1.9%). Importantly, she also finds that the onset of the SARS epidemic coincides with a 72% reduction in transaction volumes for these estates. She explains this pattern (small price reductions coincided with a large reduction in volume) as customers adopting a “wait and see” approach, whereby they avoid nonessential interactions with other people, instead waiting until the end of the epidemic to defer their transactions. This avoidance behavior is noted by Jonas (2013) as a major transmission mechanism from pandemics to economic risk.

Looking beyond real estate, Siu and Wong (2004) examine disaggregated macro data from the SARS episode, and they find that the travel, tourism, durable and semi-durable retail, and entertainment sectors were strongest hit, while production and exports were less affected. This pattern is also consistent with customers avoiding nonessential interactions, although the effect of the crisis on production and exports depends on the extent of the crisis in trading partners, and whether or not that crisis affects supply chains.

Theoretical and Empirical Evidence from the Influenza Literature

Beyond the SARS literature, there is an extensive literature on the past and likely effects of an influenza epidemic. The Congressional Budget Office (CBO) (2006) summarizes much of this literature, giving a predicted loss caused by a severe flu epidemic (similar to 1918) of about 4.25% of annual GDP and an estimated loss caused by a mild epidemic (similar to 1957 or 1968) of about 1%. In both cases, the CBO predicts that economic activity would snap back quickly after the epidemic ended, which is consistent with the data from the SARS epidemic in Hong Kong. However, since these theoretical models are mainly constructed using annual aggregates, the models do not make any specific predictions about monthly or quarterly aggregates.

Theoretical studies of influenza pandemics mostly land at losses in excess of 5% of annual GDP. For instance, a study by Kennedy, Thompson, and Vujanovic (2006) simulates a pandemic with ⅓ the mortality rate of the pandemic using a theoretical model. They find a reduction to Australian GDP of about 6%. Similarly, Douglas Szeto and Buckle (2006) predict that a severe pandemic would reduce New Zealand GDP by 5-10%. Meanwhile, McKibbon and Sidorenko (2006) predict that a severe pandemic would reduce US GDP by 5.5%, while Cooper (2006) simulates the CBO’s scenario but with disruptions to trade, and finds a 6% decline instead of a 4.25% decline in GDP. For the UK, Keogh-Brown et al. (2010) simulate mild and severe pandemics and find GDP losses of 0.6% to 2.5% for the mild scenario and 4.5% to 6% for the more severe scenario.

Contrasting with the theoretical studies, the empirical study of James and Sargent (2006) predicts that a severe flu pandemic would reduce Canadian GDP by 0.3 percent to 1.1 percent. James and Sargent base their estimates on macro data from US flu pandemics in 1918, 1957, and 1968. They find that the severe 1918 pandemic reduced annual GDP by 0.5% in 1918, with smaller effects from the other two mild pandemics. James and Sargent also cite data from the SARS outbreak, finding that while SARS severely affected tourism, travel, and services in the short run, it did not harm Hong Kong’s productive capacity in the medium run. In a similar vein, Garrett (2007) documents severe localized effects of the 1918 pandemic in places such as Little Rock, where merchants reported a 40-70% decrease in sales during the pandemic, and Memphis, where a pandemic-induced labor shortage disrupted operations. Altogether, these disruptions corresponded with a fall in a monthly industrial production index from 123.4 in July 1918 to 112.2 in October 1918 (-9.5%). The underlying data are reported by Persons (1931) and would correspond with a 2.4% fall in annual GDP for a three-month pandemic, given that industrial production is ordinarily more volatile than GDP. In addition, the Federal Reserve Bulletins from the time report significant disruptions to retail trade (up to one-third of the workforce out at any specific time) and especially to nonessential gatherings.

Altogether, the theoretical literature on influenza has given somewhat larger output losses than historical data, although the empirical literature and historical data indicate that output losses vary according to geography (harder-hit areas have higher output losses) and sector (nonessential services being hardest hit). Furthermore, trade disruptions can make the impact of the epidemic larger than it would otherwise have been.

Early Indications from the COVID-19 Outbreak in China

While official data are still not yet ready for January or February 2020, unofficial data reported by Brown (2020) at Marketwatch indicate that Chinese house prices remained stable from December to January (+0.27%) although the volume of transactions has fallen by 90 to 98% from normal. This episode illustrates a particularly strong “wait and see” pattern similar to what happened during the SARS outbreak–customers are not going to walk-throughs or closing on transactions in person. Data in upcoming weeks will tell us how long this outbreak lasts in China.

Additionally, a report by Hatzius et al. (2020) at Goldman Sachs shows detailed activity data from China during the current episode. The Hatzius report corroborates the Brown report–property transactions and transportation have nearly ceased due to avoidance behavior (some of it driven by a public policy response) while the consumption of coal fell by only 30% year over year, since people still need to heat their homes.


Appendix: Data Sources for Hong Kong Analysis

  • Monthly GDP: GDP is officially measured on a quarterly basis–we took seasonally adjusted growth rates from the Hong Kong Monthly Digest of Statistics, various issues. We first took logarithms and then interpolated it to a monthly basis using our own interpolation algorithm based on Fernandez (1981). We therefore urge caution in interpreting month-to-month movements.
  • Monthly unemployment: We took seasonally adjusted unemployment rates from the Hong Kong Monthly Digest of Statistics, various issues. The unemployment rate is presented in the Digest as a 3-month centered moving average.
  • Monthly real residential real estate prices: We took quarterly unadjusted real residential real estate prices from the St. Louis Fed’s FRED website. The original source of these data is the Bank of International Settlements (2020). We seasonally adjusted these data ourselves, took logarithms, and then interpolated it to a monthly basis using our own interpolation algorithm. We therefore urge caution in interpreting month-to-month movements.
  • Monthly real estate transactions: We took raw secondary transactions volumes directly from the online datasets published by Midland Realty (2020).


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