A gambler walks into MGM Grand, pockets swollen with $10,000. He converts his cash to chips and finds a seat. After playing poker for an hour, he understands the play style of his opponents. Feeling comfortable, he examines his middling five-card hand, considers the odds, and folds. As the day drags on, the same dealer deals our gambler the same five cards with the same odds against the same people at the same table. Does he fold? Kahneman’s insight is…it depends.
While economic models based on rational agents, or people, assume that “decision makers evaluate outcomes by the utility of final asset positions,” prospect theory proposes that decision makers care about both a reference point as well as a bet’s expected value and direction. So, if our gambler received his hand up $5,000, he would evaluate it differently than if he had received it down $5,000 — assuming our gambler’s current reference point is the amount of money he started with.
So, whether our cardsharp stays or folds — really does depend. If he is below his initial $10,000, he would be more likely to stay whereas if is above his $10,000 he would be more likely to fold — all else equal. Thus prospect theory, helps explain why gamblers who start off risk neutral will be more likely to bet big when they are down and protect their winnings when they are up. In short, “losses loom larger than gains.”
These insights emanate from the idea that decisions are a mixture of involuntary perception and deliberate reasoning. In his Nobel lecture, Daniel Kahneman describes the two components of decision making as if they were separate systems within one’s brain — called system 1 and system 2. While system 1 operations are “fast, automatic, effortless, associative, and difficult to control or modify,” system 2 operations are “slower, serial, effortful, and deliberately controlled.”
System 1 is excellent for minimizing cognitive effort. However, it can also lead us astray because it relies on shortcuts and lacks enough input from system 2. In other words, system 1 is great at determining the meal we would like from a large menu, while system 2 is more apt at solving a linear algebra equation.
To compute rapidly, system 1 often relies on rules of thumb — or heuristics — to reach conclusions. While psychologist Gerd Gigerenzer notes that heuristics are extremely useful tools, Kahneman’s focused on when heuristics stumble. For example, when people use a mountain’s clarity to judge its distance, distances will “be overestimated on foggy days and underestimated on clear days.” Throughout his career, Kahneman highlighted numerous cognitive biases that lead to faulty judgments such as anchoring, availability, and representativeness.
While Kahneman’s book, Thinking, Fast and Slow, has come under fire for relying on studies that were later found to be irreproducible, his contributions helped set off the development of behavioral economics. Practitioners of this new field include economist Richard Thaler, cognitive psychologist Dan Ariely, and Law Professor Cass R. Sunstein whose work extends and applies Kahneman’s insight to government policy by presenting information in ways that they hope will lead to better outcomes.
While some scholars question the viability of this new endeavor, the impact of Kahneman and his research partner Amos Tversky on the field of economics has undoubtedly been great, no matter how you frame it.