Quora is a website dedicated to “sharing and growing the world’s knowledge.” Ask a question, and the good folks at Quora will find someone with first-hand knowledge to answer it.
Today’s contribution to sharing and growing is “Why do technology companies hire economists?”
My response, of course, is Who wouldn’t want to hire an economist?. This response was unsatisfying enough that Quora asked Susan Athey, Professor in the Economics of Technology at Stanford’s Graduate School of Business, to address the question. Here is my condensed version of her response.
This is a great time for economists in tech companies—the most interesting firms in Silicon Valley are hiring chief economists as well as economic teams at a very rapid clip….
Each tech company, and each chief economist, is different, but there are several main categories. First are microeconomic issues involved in pricing and product design… Second is corporate strategy… Third is public policy… Fourth, and closely related, are direct legal and regulatory challenges — antitrust/competition policy issues and regulatory investigations.
More junior economists have a wide variety of roles in tech firms. They can take traditional data science roles, be product managers, work in corporate strategy, or on policy teams. They would typically do a lot of empirical work.
My emphasis (see also, here).
I was particularly interested in this nugget about why economists might be particularly valuable in a room full of data:
I have found that economists bring some unique skills to the table. First of all, machine learning or traditional data scientists often don’t have a lot of expertise in using observational data or designing experiments to answer business questions. Did an advertising campaign work? What would have happened if we hadn’t released the low end version of a product? Should we change the auction design? Machine learning is better at prediction, but less at analyzing “counter-factuals,” or what-if questions. (I’m currently doing a lot of research on modifying machine learning methods to make them more suitable for causal inference).
Click through for her complete answer to the original question, along with her insights on Bitcoin, the impacts of machine learning on economic science, the potential benefits of collusion, and some elaboration on her contention that “there has never been a more interesting time to be an economist.”