Behavioral Game Theory
Behavioral Game Theory looks at how people really make choices
It helps us understand two main things:
- How real people act when they don't follow "perfect" logic
- How feelings like fairness or trust change the outcome of a game
In regular Game Theory, we assume everyone is a math wizard who only cares about winning. But in the real world, people have emotions! They learn from mistakes and care about what others think.
The Ultimatum Game
Imagine two players: one proposes how to divide a sum of money, and the other can either accept or reject this proposal.
The proposer is told:
- If the proposal is accepted, both players get the agreed shares
- If rejected, neither player receives anything
What would be a fair offer?
... think about it for a bit ...
Traditional Game Theory suggests offering the smallest amount to the other player...
But Behavioral Game Theory observes that people often reject unfair offers.
This shows a preference for fairness over pure monetary gain.
Example: The Trust Game
In this game, Player 1 can send money to Player 2. Any money sent is tripled. Then, Player 2 decides how much to send back.
- If Player 1 sends $10, it turns into $30 for Player 2
- Player 2 can then be nice and send $15 back, or be greedy and keep all $30
Logic says "Don't send any money, because Player 2 will just keep it." But Behavioral Game Theory shows that many people do trust each other, and it pays off!
Loss Aversion (we hate losing)
People hate losing more than they love winning. This is called Loss Aversion.
For example, losing $20 feels much worse than the "happy feeling" of finding $20. Because of this, players often pick a "safe" choice even if a "risky" choice might give them a huge prize.
Example: Playing It Safe
Imagine you must choose one of these options:
- Safe choice: Get $5 for sure
- Risky choice: 50% chance to win $15, 50% chance to lose $5
Even though the risky choice has a higher average payoff, many people choose the safe option because they really want to avoid the possibility of losing $5.
Loss aversion: The pain of losing $5 feels stronger than the pleasure of winning $15.
Example: A Game Show Decision
A contestant has already won $1,000. They are offered a final gamble:
- 50% chance to win $2,000 total
- 50% chance to drop back to $500
Many contestants refuse the gamble, even though it could double their money, because losing $500 feels worse than the joy of gaining another $1,000.
This is one reason companies keep existing production methods rather than inventing something new due to perceived risk.
Real World Use
Example: Habits and Safety
Sometimes people follow a "system" just because everyone else does. It feels safe.
- Staying late at work to be seen, even when no extra work gets done
- Teaching only to the test instead of building real understanding
- Being "busy" as a sign of importance or success
- Endlessly scrolling news feeds out of habit
Example: Selling Too Early
An investor buys a stock for $50.
- If the price goes up to $60, they quickly sell to "lock in" the gain
- If the price drops to $40, they often refuse to sell and keep hoping it will recover
People dislike the feeling of a realized loss more than they enjoy a realized gain, so they avoid selling at a loss even when it might be the smarter choice.
Loss aversion: Losing $10 feels worse than the pleasure of gaining $10.
Example: Keeping a Bad Plan
A company has already spent $1 million developing a product.
- New information shows the product is unlikely to succeed
- Stopping now would save money in the long run
Even so, managers often continue the project because stopping would mean "accepting the loss." They prefer to risk losing more money rather than admit the original loss.
Loss aversion: People work harder to avoid admitting losses than to achieve new gains.
This is often called throwing good money after bad.
In economics it is known as the sunk cost fallacy: money already spent is gone, so it should not affect future decisions.
Good decisions look forward, not backward.
When we know how humans actually act, we can build better ways to work together.
Conclusion
Behavioral Game Theory teaches us that being "smart" isn't just about math. It's about understanding people!