Apurv Jain has used some unconventional data to predict the course of U.S. employment: 1.2 billion tweets and 830 million web searches.
As Bloomberg reports, Jain was inspired by a comment from former Federal Reserve Chair Janet Yellen that labor-market conditions might be worse than official statistics indicated. So he began looking for unofficial ones.
He analyzed tweets from 230,000 Twitter users who had lost or gained work to understand the sentiment behind the numbers. He also has discovered that scouring six years of web-search queries allows him to predict revisions in one of the world’s most critical indicators: the U.S. Labor Department’s monthly report on nonfarm payrolls.
It’s all part of the fast-growing world of alternative data, which “can provide details about the economic narrative of our country that the existing government data simply cannot,” said Jain, 41, now a visiting researcher at Harvard Business School. He presented his findings last week at a New York conference on artificial intelligence and data science in trading.
