78 Finance & economics The Economist November 13th 2021
Homeicide
T
he timingwas apt. On November 2nd, just two days after
Americans celebrated their scariest annual holiday, news of a
suspicious death shocked the stockmarket. Zillow, a giant proper
ty and technology firm, said it would shut down its huge instant
buying, or ibuying, business, which uses big data and algorithms
to make offers on homes in dozens of cities in America and then
swiftly sells them on. The firm expects to lose in excess of $500m
in the second half of 2021 after it overpaid for thousands of homes.
It will lay off a quarter of its 8,000 employees. It seemed like a
business that should be in rude health. By and large it has been a
fantastic time to buy a home almost anywhere in America—if you
can only snag one: house prices have climbed between 16% and
25% during the past 18 months. So why is Zillow’s ibuying busi
ness in the morgue? And whodunnit?
Finding the right suspect matters for reasons bigger than the
fate of Zillow itself. The ibuying business is one of many exam
ples of firms using a platform to collect big data, analyse it using
advanced techniques and empower their algorithms to enable a
market to work more smoothly. This trend has pushed down tran
saction costs in many asset markets, from stocks and bonds to
camera equipment and clothing. The fate of Zillow’s ibuying
business might indicate that using technology to buy and sell
something as idiosyncratic as a house is a flip too far.
Consider the most serious suspect first: the housing market. It
has been in an unusual state of flux. At first the covid19 pandemic
caused a freeze in all property transactions. Then prices went ber
serk, rising at record levels year on year in April. Undoubtedly, vo
latile prices do no favours to algorithms trained on historical data.
Still, in theory rising prices should help ibuyers by making it
harder to sell a house for less than was paid for it. The reverse, fall
ing prices, could be a more likely culprit but as yet the data are
mixed. A houseprice index compiled by the National Association
of Realtors (nar) finds that values peaked in June 2021, at 19%
above prepandemic levels, and have since dropped by 2.8 per
centage points. Another byS&PCoreLogic CaseShiller suggests
prices are still galloping ahead. Both are published with a lag (the
narruns to the end of September, CaseShiller to the end of Au
gust), which means the evidence is inconclusive. The next suspect is the mathematical models. A handful of
firms offer ibuying services, the first and biggest of which is
Opendoor, founded in 2014. They charge a fee for the services they
provide: buying and selling homes immediately, with zero fuss.
The quick inandout makes them more like marketmakers than
property investors, who buy to hold. To succeed, ibuying firms
need two critical pieces of information: the current value of a
home and a forecast of the price at sale time, typically two to three
months in the future. To figure these out they need troves of data,
ranging from the precise location of a home, to how many rooms it
has, to whether it has a pool or not. They compare these with the
closest comparable homes that have sold recently and look at re
cent trends to make a forecast. That enables them to make an “in
stant” offer to a homeowner. In the past the algorithms appear to
have worked pretty well. Mike DelPrete, of the University of Colo
rado, found they offered homeowners about 1.4% below market
value—not a bad outcome for a quick, hasslefree sale.
Zillow’s boss, Rich Barton, said the big problem was with the
firm’s forecasts. He claimed it had found itself unable to predict
prices threetosix months into the future. In particular Zillow
seems to have projected much rosier conditions than material
ised. In Phoenix, where houseprice appreciation has been partic
ularly rapid but seems to be slowing, Zillow is listing homes for an
average of 6.2% less than it paid for them.
This problem is exacerbated by the fickle economics of adverse
selection. Even if the algorithms of ibuying firms are excellent at
pricing homes at a fair value on average, they only need to be a lit
tle off for the risk to skew to the downside. Homeowners will prob
ably not sell their home for much less than they think it is worth,
but they will happily settle for a higherthanexpected price. Mr
Barton revealed in a shareholder letter on November 3rd that
“higherthan anticipated conversion rates” were part of the pro
blem. One former Zillow employee has claimed that the company
wanted around 50% of homeowners who sought an offer to take it,
but as many as 74% of offers made in recent months were taken
up. Zillow bought almost 10,000 homes in the third quarter, more
than double the amount from the prior threemonth period,
which itself was more than double the amount in the first quarter.
The suspicion is that Zillow’s algorithm was making overly gener
ous offers, and homeowners were rushing to take advantage.
This may have been a Zillow problem, not an ibuyer one, how
ever. Some of Zillow’s competitors seemed to realise before Zillow
that the market was losing steam. OpenDoor and Offerpad, an i
buyer founded in 2015, both began making more conservative of
fers relative to their models’ valuation around July as price appre
ciation began to cool. When they reported their earnings on No
vember 10th neither Opendoor nor Offerpad exhibited anything
like the problems suffered by Zillow. Inside job
Perhaps the fatal blow was, in fact, selfinflicted. Zillow expanded
its ibuying business aggressively. Opendoor expanded gradually.
It offered ibuying services in only six markets after three years,
taking its time to refine its algorithms. It is now operational in 44
markets. Zillow added almost as many markets in half as much
time. A former Zillow employee told Business Insiderthat manage
ment had been hellbent on catching up with Opendoor, the front
runner. In order to compete, the employee alleged, the company
pushed to offer generous deals to potential clients. It calledthis
“Project Ketchup”. Now it has its own fake blood on its hands.nFree exchange
A Zillow whodunnit