Economics > Behavioral Economics > Prospect Theory
Description:
Prospect Theory is a pivotal concept within the field of Behavioral Economics, which itself is a sub-discipline of Economics that marries insights from psychology with traditional economic theories to better understand how individuals make decisions. This theory, introduced by Daniel Kahneman and Amos Tversky in their seminal 1979 paper, challenges the classical economic assumption that humans are rational agents who always make decisions to maximize their utility.
Prospect Theory contends that individuals evaluate potential losses and gains in ways that deviate from the predictions of Expected Utility Theory. This theory is comprised of several key elements:
Reference Dependence: Unlike traditional theories that assume absolute levels of wealth or utility, Prospect Theory posits that people evaluate outcomes based on a reference point, usually their current state. Gains and losses are perceived relative to this point rather than in absolute terms.
Loss Aversion: One of the cornerstone principles of Prospect Theory is that losses weigh more heavily on individuals than gains of an equivalent amount. This asymmetry implies that the pain of losing $100 is generally felt more intensely than the pleasure of gaining $100.
Diminishing Sensitivity: This principle states that the impact of changes in wealth diminishes as one moves farther from the reference point. The subjective difference between getting $100 and $200 is larger than between $1,100 and $1,200, even though the absolute difference is the same.
Probability Weighting: People tend to overestimate the likelihood of low-probability events and underestimate the likelihood of high-probability events. This leads to a probability weighting function that is not linear, which means real-world decisions can’t be accurately captured by mere probabilities alone.
Mathematically, Prospect Theory can be described using a value function \( v(x) \) and a probability weighting function \( \pi(p) \). The value function typically is concave for gains and convex for losses, and steeper for losses than for gains, which captures the loss aversion phenomenon:
\[ v(x) =
\begin{cases}
(x - r)^\alpha & \text{if } x \geq r \\
-\lambda(r - x)^\beta & \text{if } x < r
\end{cases}
\]
Here:
- \( r \) represents the reference point.
- \( \alpha \) and \( \beta \) are parameters that measure the sensitivity for gains and losses, respectively.
- \( \lambda \) is a parameter for loss aversion; typically \( \lambda > 1 \).
The probability weighting function \( \pi(p) \) captures the non-linear perception of probabilities:
\[ \pi(p) = \frac{p\gamma}{(p\gamma + (1-p)\gamma){1/\gamma}} \]
Where \( \gamma \) is a parameter that captures the decision maker’s sensitivity to changes in probability.
Prospect Theory has had significant implications across multiple domains such as finance, insurance, and marketing. It explains why people might engage in gambling, prefer sure gains over probable ones, and display a variety of biases that traditional economic theories cannot account for.
In essence, Prospect Theory provides a more nuanced and psychologically-accurate framework for understanding decision-making under risk and uncertainty, emphasizing that human decisions are often influenced more by perceived gains and losses rather than by final outcomes.