michael_i_norton's picture
Harold M. Brierley Professor of Business Administration, Director of Research, Harvard Business School; Co-author (with Elizabeth Dunn), Happy Money

Imposing Randomness

Paul Meier—who passed away in 2011—was primarily known for his introduction of the Kaplan-Meier estimator. But Meier was also a seminal figure in the widespread adoption of an invaluable explanatory tool: the randomized experiment. The decided unsexiness of the term masks a truly elegant form—that in the hands of its best practitioners approaches art. Simply put, experiments offer a unique and powerful means for devising answers to the question that scientists across discipline seek to answer: How do we know if something "works"?

Take a question that appears anew in the media each year: Is red wine good or bad for us? We learn a great deal about how red wine "works" by asking people about their consumption and health and looking for correlations between the two. To estimate the specific impact of red wine on health, though, we need to ask people a lot of questions—about everything they consume (food, prescription medication, more unsavory forms of medication), their habits (exercise, sleep, sexual activity), their past (their health history, their parents' and grandparents' health histories), and on and on – and then try to control for these factors to isolate the impact of wine on health. Think of the length of the survey…

Randomized experiments completely reengineer how we go about understanding how red wine "works." We take it as a given that people vary in the manifold ways described above (and others), but cope with this variance by randomly assigning people to either drink red wine or not; if people who eat donuts and never exercise are equally likely to be in the "wine treatment" or the "control treatment" then we can do a decent job of assessing the average impact of red wine over and above the likely impact of other factors. It sounds simple because, well, it is —but anytime a simple technique yields so much, elegant is a more apt description.

The rise of experiments in the social sciences that began in the 1950s—including Meier's contributions—has exploded in recent years, with the adoption of randomized experiments in fields ranging from medicine (testing interventions like cognitive behavioral therapy) to political science (running voter turnout experiments) to education (assigning kids to be paid for grades) to economics (encouraging savings behavior). The experimental method has also begun to filter into and impact public policy: President Obama appointed behavioral economist Cass Sunstein to head the Office of Information and Regulatory Affairs, and Prime Minister David Cameron instituted a "Behavioural Insights Team."

Experiments are by no means a perfect tool for explanation. Some important questions simply do not lend themselves to experiments, and the experimental method in the wrong hands can cause harm as in the infamous Tuskegee syphilis experiment. But the increasingly widespread application of experiments speaks to their flexibility in informing human understanding of how things "work"—and why they work that way.