Technology

2005 to develop algorithms for estimating home prices. When the housing market started to crater, he emerged as a favorite source for journalists looking for data and commentary. “At a time when you still had industry people saying ‘Yes, we’ve had some correction in prices, but there’s nothing to see here, move on,’ I’d be the guy who came out and said, ‘No, we’re going to see another two years in housing recession; here’s why,’” says Humphries, whose current title is chief analytics officer and chief economist. “We felt being as accurate as we could would garner respect from consumers.”

Publishing data-driven research has become a popular strategy for web marketplaces and listings sites to showcase their depth of knowledge about a particular industry. That includes home renovation startups such as Houzz and BuildZoom, and jobs sites like Indeed and Glassdoor. More data is generally a good thing, says Bill McBride, who blogs about the housing market at Calculated Risk, but it pays to consider where it comes from and how it’s compiled. “Some of the private data is garbage,” he says. “It’s not that the people producing it are not as smart or that they don’t do hard work. The motivations are different.”

In the early days of the data boom, tech companies sought to entice big brains by allowing them to keep one foot in academia, says Susan Athey, a former chief economist at Microsoft who now teaches at Stanford. Recently, Amazon has emerged as an exception to that rule, says Athey: It keeps a tight leash on research produced by its in-house economists. Nonetheless, it’s managed to attract a team whose size and quality rivals the economics departments of top universities, Athey says, in part because the company offers access to unique data. “I can’t run an experiment on a couple of million people at Stanford. If you want to be aware of what interesting questions are out there, you almost have to go and work for one of these companies.” Patrick Clark