Behavioral economics challenges traditional economic assumptions by incorporating psychological insights into decision-making. This module explores Expected Utility Theory (EUT), a foundational concept, and its limitations, leading into key behavioral alternatives that better explain real-world choices.

Expected Utility Theory, pioneered by John von Neumann and Oskar Morgenstern, provides a normative framework for rational decision-making under uncertainty. It posits that individuals choose among gambles to maximize their expected utility, which is the weighted average of the utilities of possible outcomes, with weights being the probabilities of those outcomes.

Despite its elegance, EUT has been shown to be descriptively inadequate, meaning it often fails to predict how people actually behave in real-world situations. Empirical evidence from various studies has revealed systematic deviations from EUT predictions.

Another significant challenge comes from prospect theory, developed by Kahneman and Tversky. Prospect theory addresses several empirical regularities not captured by EUT, such as loss aversion and the way people perceive probabilities.

Several theories have been proposed to provide more accurate descriptive models of decision-making under uncertainty.

Prospect theory describes how individuals evaluate potential losses and gains. Key features include:

• Value Function: People evaluate outcomes relative to a reference point (often the status quo), and the disutility of a loss is generally greater than the utility of an equivalent gain (loss aversion).
• Probability Weighting: People tend to overweight small probabilities and underweight moderate to high probabilities. This is known as probability distortion.

An extension of prospect theory, CPT addresses some of the technical issues of the original formulation, particularly regarding the treatment of probabilities and the independence axiom. It uses cumulative probabilities, which resolves some paradoxes and provides a more robust descriptive model.

Other models, such as regret theory and disappointment theory, also attempt to capture psychological factors influencing decisions under uncertainty, focusing on the emotional consequences of outcomes.

The distinction between normative EUT and descriptive behavioral theories is often tested through carefully designed experiments. These experiments present subjects with choices involving gambles and analyze their decisions to see if they align with EUT or exhibit patterns predicted by behavioral models.

Common experimental designs include:

• Choice Tasks: Presenting subjects with pairs of gambles and asking them to choose.
• Preference Reversal Tasks: Designing scenarios where EUT predicts consistent preferences, but behavioral biases might lead to reversals.
• Field Experiments: Conducting experiments in real-world settings to test the applicability of these theories outside the laboratory.

While Expected Utility Theory provides a powerful normative benchmark for rational decision-making, behavioral alternatives like Prospect Theory offer more accurate descriptive accounts of how individuals actually make choices under uncertainty. Understanding these differences is crucial for developing more realistic economic models and effective policy interventions.