Last month, Berkeley’s Data Science Undergraduate Studies (DSUS) hosted the Data Science in Undergraduate Economics Workshop, bringing together academic and corporate leaders actively innovating in the intersection of undergraduate data science and undergraduate economics education.
Why this workshop?
The inspiration for this inaugural workshop was to provide a collaborative outlet for those teaching at the intersection of data science and economics, showcase the work of those leading in this area, create a repository of open-source course materials, and create a community in the current environment of remote work and learning.
Featured presenters from both higher education and the corporate sector included UC Berkeley, Harvard, QuantEcon, Coursera, and Goldman Sachs as a way to bridge the gap between industry and academia in data science and economics. A highlight of the conference was an impromptu address by Nobel Laureate and co-founder of the Quant Econ effort, NYU Professor Thomas Sargent. He claimed to have avoided mathematics classes as a Berkeley undergraduate in Economics (‘64) but now uses Python in Jupyter notebooks on a regular basis.
Data Science and Economics at Berkeley
In the last several years there has been an increased interest in teaching undergraduate economics using data science techniques. Jupyter notebooks as a curricular platform is a tool for making rich and interactive curriculum. This increased interest from students is apparent when looking at the enrollment numbers of Berkeley’s Data Science Undergraduate Studies.
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Of the 950 declared Data Science majors, 17% are enrolled in the economics domain emphasis.
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Economics and Data Science is the most common double major--40% of all students with multiple majors.
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Economics is the most common major, representing 24% of all Data Science minors.
UC Berkeley has not enforced a requirement to sign up for specific tracks. Students can select the Data Science major or minor and decide their domain emphasis. Many students are choosing the economics intersection.
“The Data Science minor has only been available for a year and the major for two-and-a-half years at UC Berkeley," said Eric Van Dusen, Interim Director of Data Science Undergraduate Studies. “These are incredible numbers for growth. Economists would say there was a latent demand waiting to be expressed when this market opened.”
Opportunity for Data Science and Economics
Workshop participants highlighted trends that illustrate why there is such an interest in this intersection. Academic and policy-oriented economists are increasingly using big data to address economic challenges (Harvard); industry is increasingly using Python and Jupyter as basic tools of finance and is hiring graduates with both economics and coding skills (Goldman Sachs GSQuant, FinanceandPython); and the Open Science ecosystem, including software packaging and textbook publishing, is being used to create dynamic new curricula (Quant Econ). Berkeley’s Haas School of Business has implemented a Data 8 Connector Course as a prerequisite for the major. A recent survey of Economics courses found at least 12 courses include elements of data science.