How Much Information Is Too Much?

Knowledge may be power, but information can also be overwhelming. Decision-makers often have access to so much potentially relevant data that they must choose what to ignore. Economists call this “rational inattention,” and determining the optimal way to sift information has been the subject of years of research.

Chicago Booth’s Lars Peter Hansen and Boston University’s Jianjun Miao and Hao Xing introduce a further wrinkle: subjective uncertainty. Most models of rational inattention assume the decision-maker has 100 percent confidence in their “priors”—their assessments of the odds that various outcomes will be realized.

But decision-makers are often not so confident in their ability to estimate probabilities. How does that change the problem of the best way to allocate attention? The researchers created a model of decision-making to understand how ambiguity about priors affects the search for information, shedding light on the process behind decisions as varied as which financial asset to invest in or which political candidate to support.

Imagine you have inherited $50,000 and are considering two options: Buy index funds for your retirement account or put the money in your young child’s college fund. There’s a lot of information to help you decide, including myriad sources and factors to consider around historical performance, risk analysis, tax implications, and regulations about how the funds can be used.

The information you choose to invest your attention in will vary based on your predictions about the future. How likely is your child to win a scholarship—or to opt not to attend college? How likely is a downturn in the stock market? What are the odds that you’ll retire at a particular age, and that your social security or your pension will be fully funded?

You may estimate which among numerous information sources are most relevant to you but may not be fully confident in that estimate. There is a cost—in terms of time, attention, or perhaps other resources—that limits your efforts in information gathering, and that initial estimate plays a central role in shaping these efforts. Changing the estimate influences how you proceed in seeking new information.

In the researchers’ model, the significance of this cost decreases as confidence declines. People who are more concerned about ambiguity in their subjective beliefs consider a broader range of future possibilities and expand their search for information to guard against various potential outcomes. They gather data to make a decision that remains valid even if their initial estimate is not entirely accurate.

The decision model they suggest characterizes individual decisions between two or more distinct choices, rather than as a continuous series of choices that change dynamically as decisions are made. “Such problems have applications to such diverse fields as labor economics, industrial organization, macroeconomics, and political economy,” the researchers write.

For Hansen, a Nobel laureate, this research is a new approach to his work on decision-making under uncertainty. His past work has examined how decision-makers’ aversion to uncertainty affects their choices in various contexts, and how that is reflected in the movements of financial markets or public policy. That research has generally treated the information the decision-maker draws upon as given, but his work with Miao and Xing probes how uncertainty affects the search for information itself.