Every Uber ride in Minneapolis makes a Bay Area Victorian a smidge more expensive. Every small business running ads in Little Rock, Arkansas, raises a tower a tiny bit higher. Every Pinterest board in Provo, Utah, reshapes this place, where people went to prom and repaired mufflers and dreamed of parrots and poetry. San Francisco is now the town that apps built.
Read: Tech billionaires’ obligation to the cities around them
And while digital space is seemingly infinite, San Francisco has an extremely limited housing supply. Only 5,471 properties changed hands last year out of almost 400,000 housing units. So what will happen when billions of dollars in stock options can become cash anytime someone clicks Sell?
The common wisdom is simple: housing Armageddon.
But even the end times have a structure. Much of what the world knows about the tech world’s effects on San Francisco’s real-estate market comes from three sources: house-hunting lore (“They bid 400 grand over asking! All cash!”), realtors talking up their industry’s prospects, and aggregated market data from firms like CoreLogic. The numbers point to crazy market dynamics: The median home price hovered around $1.3 million in 2018.
But precisely because the tech industry has become so ubiquitous, blending in seamlessly with the old-line wealth generated by hometown firms like Bechtel, McKesson, Levi’s, various banks, and more obscure fortunes, it’s been hard to disentangle what all those engineer salaries and options are doing in the world.
At least until Deniz Kahramaner got interested. He’s a 20-something Stanford-trained data scientist turned real-estate agent, and he wanted to understand who was driving the local housing market. When he founded Data Bay Area, a real-estate group affiliated with the unicorn start-up Compass, he came into a common data set of property records. Title companies, which are the internal machinery of the real-estate market, generate business for themselves by giving away the data on who owns all the properties in a city.
“Historically, realtors have used it to spam people,” Kahramaner told me. But as he looked at the records of every property purchase in San Francisco, his data-science background saw not marketing information, but analytical potential. Most realtors think about where property is purchased, not necessarily who is doing the buying. “I thought, Wow, this is an incredibly rich data set. You can see who bought what,” he said. “Why is no one analyzing this!?”
So he did, creating an unprecedented data set about the nature of San Francisco’s home buyers that allows his analysis of the potential effects of the IPOs on the city to go one layer deeper. His research suggests that the boom is going to be spikier than anticipated, concentrated in just a few neighborhoods, at least at first. It will also proceed more slowly than most people are anticipating. Shares are generally locked up for six months after a company goes public, but the bulk of the money probably won’t enter the market for a year or two, Kahramaner believes.