Behavioral economists would argue that the root cause of the low savings rates in America is not only low wages, but also the fact that many individuals make poor decisions that contradict their own self-interest. Instead of being guided by logic and reason, individuals often make seemingly irrational choices because of faulty heuristics and hidden biases. For example, people may tend to be myopic and focus on short-term payoffs, such as by choosing the immediate gratification of overeating at the expense of their future health or spending money now rather than saving for later.
One solution to this type of problem has been to reshape how individuals make decisions. In their bestselling book, Nudge: Improving Decisions About Health, Wealth and Happiness, Richard Thaler and Cass Sunstein, who later became President Obama’s regulatory czar, describe how policymakers can improve people’s lives by strategically framing decisions to direct them toward a preferred outcome. For example, rather than simply giving people the option to enroll in retirement savings plans, companies can automatically sign up their employees. While workers can still go out of their way to opt out, changing the default gives an immediate boost to savings rates. California, for example, is considering establishing a statewide retirement plan that employers would automatically enroll their workers in unless they offered their own plans. This type of proposal has gained support among many policymakers because it strikes a middle ground between the dreaded nanny state and the unsympathetic disregard of a purely libertarian government.
Some government agencies, especially at the federal level, have tried to expand on this approach by recruiting behavioral scientists to more rigorously use data to test and evaluate how changes to programs can yield better results. In many cases, they mirror the type of data-driven approaches the private sector uses for marketing products and services. For example, an agency might test the response rates for different email messages asking individuals to take a specific action and then use the most successful one. Such A/B testing is second nature to most businesses.
But unlike the private sector, government programs still tend to focus on finding the most effective message for the entire group, rather than creating a multitude of tailored messages based on the characteristics of individuals. However, the U.S. has a diverse society, and the message that convinces one person to act may not work for another. For example, the most effective message to persuade new parents to increase their savings rate might be very different from the one used for recent college graduates. Using a one-size-fits-all approach misses the opportunity to use micro-targeting to create personalized interventions that influence individuals based on their attitudes, values and lifestyle. As a result, programs are less effective than they could be.
Personalization was not possible in the past because it would have been prohibitively expensive, but this is no longer the case. Companies like Opower, which uses personalized interventions to encourage consumers to have more energy-efficient behavior, have proven that these data-driven approaches can be successful. And the rise of artificial intelligence and robo-advisers for financial services means these types of opportunities will continue to grow.
By creating personalized nudges, not only for savings but also for other important behaviors, government agencies will be able to both improve overall welfare and better serve their constituents without treading on the everyday freedoms enjoyed by citizens.
