We live in a world where more and more people and organizations make decisions based on data. These include business decisions, policy-making decisions, and even many personal decisions. Google employs hundreds of quantitative analysts to analyze auctions, forecast revenue, predict customer needs, and surely lots of other things we don’t know about. A good friend of mine just spent the last month carefully analyzing student loan data for the Federal Reserve. I even just read about a guy who scraped dating data from OK Cupid to find himself a wife.

Business and the government often look to economists to do this kind of data analysis for two main reasons. First, economists have been using data to answer questions about optimal behavior for a long time and have developed a set of statistical methods tuned for these problems that we call econometrics. These tools are particularly applicable to the non-experimental (aka “observational”) data that is piling up all around us. The second reason is that economists are good at thinking mathematically about human behavior and markets–two concepts at the heart of many important questions.

I am constantly telling my undergraduate students to take as many classes on econometrics, statistics, and/or data analysis as they can. Only one semester of statistics/econometrics is required to get a bachelor’s degree in economics at Yale, and this introductory course covers the basics of probability, statistical inference, and linear regression. The payoff to taking the second class is huge–that’s where students actually gain proficiency with elementary methods and build up to important methods like instrumental variables and difference-in-differences that can separate causation from correlation.

I recently did an informal survey of ten top-tier economics departments and learned that seven of the ten now require two semesters (or quarters) of statistics and/or econometrics.¹ I will be shocked if in five years it’s not at least nine out of ten. Even now, many advanced applied elective courses teach statistical methods so that students can understand (and contribute to) the research they read.

At the beginning of my last semester in college I had a conversation with a fellow senior that has really stuck with me. He went on and on about how excited he was to be taking Econ 101. At least part of his logic was that he didn’t want to graduate without knowing something about the economy. I had not taken any economics up to this point and had no idea what he was talking about. I didn’t get it at all. Now I do. Economics training gives people tools for understanding how the world works. That training needs to keep up with our increasingly data-driven world.

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