Scholars typically obtain such data in two ways: They approach the company with a research question they would like to answer; one recent paper in this vein examined the wage gap between male and female Uber drivers, and another sought to put a value on the flexibility of working for Uber. Or the companies can approach scholars with a question they want answered, as with the Cornell study.
When the scholars are faculty members at an academic institution, the companies typically cede editorial control to them.
But the process still tends to skew what we know about the companies, Mr. Zingales said, because companies are unlikely to approve the release of data for a study, or approach a scholar with data, if they believe the conclusion is likely to reflect poorly on them. One such study, he has noted, recently asked whether traffic fatalities increase after Uber and Lyft start operating in a city, for which the companies did not provide detailed data.
Many scholars have an interest in maintaining a relationship with companies because it is difficult to answer key policy questions without access to their data. This can lead researchers to adopt more favorable assumptions when there is legitimate debate about how to handle a methodological question.
Mr. Katz said the problem arose with many companies, but was a growing concern with digital platforms in light of their size and relevance to the economy.
Mr. Hyman said Uber and Lyft had not influenced his results in any way. He said they had approached him after people at Uber read his 2018 book, “Temp,” a well-reviewed history of the rise of alternative work arrangements like freelancing that was relatively positive about the online gig economy.
The companies appeared to be pleased with the findings, and were quick to point out flaws in a study for the City of Seattle, also released last week, that put the typical driver’s wage at $9.73. That study calculated earnings from cruder data the city had obtained from Uber, supplemented by a survey of thousands of drivers.