You probably think you know yourself pretty well. So when you make a plan, you assume you have a reasonably accurate picture of what future you will do. New research suggests that assumption is wrong, and that the gap has real consequences for the decisions we make every day.
That is the central finding of "Noisy Foresight," co-authored by Chad Kendall, associate professor of finance and business economics at the University of Miami Patti and Allan Herbert Business School, and Anujit Chakraborty of the University of California, Davis. Published in the Journal of the European Economic Association, the paper examines whether people can think ahead to their own future actions and use that foresight to make better decisions today.
It turns out most of us cannot, even when the only person we have to predict is ourselves.
The experiment
To test this, Kendall and Chakraborty designed an investment task. Participants started with one dollar and chose how much to leave invested in an uncertain project. In a second step, they would learn how the investment performed and then decide whether to withdraw.
In practice, participants always had a safety valve. If the investment performed poorly, they could simply pull their money out later. Knowing that, most people should have felt comfortable investing more from the start.
But many participants still acted as though they would be stuck with a bad outcome, even though they repeatedly proved to themselves that they would avoid it.
About 60 percent of participants changed their investment based on a number that, logically, should have had no effect on their decision at all. They were reacting to a bad outcome they would never actually accept.
What made the finding especially striking is that participants were not confused in the second step. When that moment arrived, they almost always chose correctly. They had seen themselves do it over and over across 20 or more rounds. Yet they never connected that pattern back to their first-period decisions.
"There's very little learning," Kendall said. "They've seen themselves make the rational decision in the second period over and over again, but they don't ever fold it back and think, well, I should learn that I'm never getting this bad thing."
Treating your future self like a stranger
What sets this research apart from earlier work is where the failure shows up. Economists already knew that people struggle to anticipate what other players will do in multi-person games. This experiment removed all of that. There were no other players, no competing interests. The only person to predict was yourself.
"You would think if you could ever figure this out, it would be when it's you," Kendall said. "You don't have to worry about whether that person's crazy, or maybe that person's trying to get me. It's you."
The failure persisting anyway points to something fundamental. "People think in a forward, time-progressing kind of way," Kendall said. "They don't think: what I do tomorrow affects what I should do today." In the most extreme reading of the data, participants were treating their future selves as a different person entirely.
Modeling the mistake
After testing several competing models against the data, the researchers found that the best fit was what they call the "noisy self" model. It describes people who do not ignore the future entirely, but who behave as if their future self might occasionally make mistakes, even though that future self almost never actually does.
The model also incorporates cognitive discounting, a tendency to treat future payoffs as if they are worth less than they are, not because of any preference for money now over later, but as a kind of mental fading when simulating outcomes not yet experienced. Together, the two factors explained the behavior of roughly 90 percent of participants.
The advice Kendall draws from his own research is straightforward, if easier said than done. "Think ahead about your future," Kendall said. "Try to plan future choices before you think about what to do today. That's an easy prescription. It's not so easy to do in practice."
