In recent years, economists have played an increasingly important role in high technology firms. Their understanding of economic systems and their experience disentangling causation from correlation in empirical data complement the skills of data scientists coming from other backgrounds. In addition, their knowledge of incentives and market design makes them indispensable for organizations developing or operating in the new kinds of markets, platforms, and economies created by our digitized world.
These developments are not just restricted to the high tech sector--the explosion of digitized data is creating new challenges and opportunities for businesses, governments, and non-profits of all kinds.
As a result economics training is expanding to include new areas such as computer programming and machine learning. As the premier economics department in San Francisco, the world's high-tech hub, we are taking the lead in updating economics education to reflect these new developments. Whether students hope to join the many established firms and numerous startups located within a few blocks of campus, or want to find innovative ways to fight poverty in the developing world, our goal is to equip them with the tools they need.
Here are some resources for students interested in learning more about this developing sector.
Two articles from economists Susan Athey (Stanford Business School) and Michael Luca (Harvard Business School) give the best overall analysis of this trend:
The short version is Why Tech Companies Hire So Many Economists, appeared in the Harvard Business Review on February 12, 2019. A longer discussion, Economics (and Economists) in Tech Companies, was published in the Journal of Economic Perspectives in Winter, 2019.
Two labor economists at employment-oriented tech firms have also weighed in:
To learn about academic research on the topic, read this review article on Digital Economics by Avi Goldfarb (University of Toronto's Rotman School of Management) and Catherine Tucker (MIT Sloan) in the Journal of Economic Literature, published in March 2019. For even greater depth, dig into the NBER Project on the Economics of Digitization, which contains reading lists, course syllabi, data sources, and other resources for PhD students and academic researchers working in this area.
Economics in the Age of Algorithms, Experiments, and A.I. San Francisco, October 28-30, 2018. This is the second annual Tech Economics conference, organized by the National Association of Business Economists and sponsored by Amazon, Google, IBM, Microsoft, Netflix, Uber, Zillow, CBRE, CoreLogic, Facebook, Haver Analytics, Indeed, and Realtor.com.
The third annual Tech Economics conference will be held in Seattle, November 3-5, 2019.
News Articles on Tech Economics
Amazon gets an edge with its secret squad of PhD economists CNN Business, March 13, 2019
"Soon there may be more economists at tech companies than in policy schools" Quartz, October 31, 2018
"Uber's Secret Weapon is its Team of Economists" Quartz, October 14, 2018
"The World’s Top Economists Want to Work for Amazon and Facebook" Bloomberg.
"All of a Sudden, Economists Are Getting Real Jobs" Noah Smith on Bloomberg.
"Goodbye, Ivory Tower. Hello, Silicon Valley Candy Store." The New York Times.
"Economics in the age of big data" Science
"How Online Shopping Makes Suckers of Us All" The Atlantic
"How we all became lab rats for American corporations and theoretical economists" The Los Angeles Times
"Chief economists are the new marketers" The Washington Post
"Economists Adding Up At Amazon.com, Microsoft, Google" Investors Business Daily
Discussions in Online Forums
Quora: "Why do technology companies hire economists, and what is their contribution? What kinds of problems do they work on?"
Medium:"4 Reasons Why Economists Make Great Data Scientists (And Why No One Tells Them)"
What Can Uber Teach Us About the Gender Pay Gap? This great podcast from Freakonomics illustrates the potential for collaboration between high tech firms and economists to research important social issues.
Why Uber is an Economist's Dream, also from Freakonomics, provides another illustration of how new sources of data from the digitized economy provide new windows into classic economic questions.
Susan Athey on Machine Learning, Big Data, and Causation, from EconTalk.