Expected utility is a concept in economics that helps individuals make decisions when faced with uncertain outcomes. It is a measure of the satisfaction or happiness that a person is expected to derive from a particular decision or outcome. The concept of expected utility is widely used in finance, insurance, and other fields where decision-making under uncertainty is common.

Calculating expected utility involves two main components: the utility function and the probabilities of the outcomes. The utility function assigns a numerical value to each potential outcome to represent the level of satisfaction or utility it provides. The probabilities of the outcomes are then multiplied by their respective utility values and summed up to obtain the expected utility of the decision or outcome. This calculation helps individuals make informed decisions by weighing the potential benefits and risks associated with each option.

Understanding how to calculate expected utility is an important skill for anyone who needs to make decisions under uncertainty. By using this concept, individuals can make more informed decisions that take into account the potential risks and rewards associated with different outcomes. In the following sections, we will explore the steps involved in calculating expected utility and provide examples of how it can be applied in real-life situations.

Fundamentals of Expected Utility Theory

Expected utility theory is a concept rooted in decision theory that aims to quantify the value or satisfaction an individual or investor expects to receive from a specific outcome. It takes into account both the potential outcomes and their respective probabilities. The expected utility is calculated by aggregating the products of possible outcomes with the probability of occurrence of the events.

The expected utility theory considers it a logical choice to choose the event with the maximum expected utility. However, in case of risky outcomes, decision-makers may not choose the action with a higher expected utility. The theory assumes that individuals make choices based on their preferences and that these preferences can be represented by a utility function.

The utility function is a mathematical function that assigns a numerical value to each possible outcome, reflecting the individual's preference for that outcome. The expected utility theory assumes that individuals are rational and that they make decisions based on their preferences and the available information.

The expected utility theory is widely used in economics, finance, and other fields to model decision-making under uncertainty. It provides a framework for evaluating the expected value of different alternatives and helps individuals make informed decisions. The theory has been subject to criticism and debate, and alternative theories have been proposed to address some of its limitations.

Overall, the expected utility theory is a useful concept for understanding decision-making under uncertainty. By considering the potential outcomes and their respective probabilities, individuals can make informed decisions and maximize their expected utility.

Defining Expected Utility

Expected utility is a concept that is widely used in decision theory and economics. It attempts to quantify the value or satisfaction an individual or investor expects to receive from a specific outcome. It takes into account both the potential outcomes and their respective probabilities. The expected utility is calculated by multiplying the utility of each outcome by its probability, and then summing up the results.

Utility is a measure of the satisfaction or happiness that an individual derives from a particular outcome. It is subjective and varies from person to person. For example, some people may derive more utility from a financial gain than from a non-financial gain.

Expected utility theory assumes that individuals are rational decision-makers who try to maximize their expected utility. They consider all the possible outcomes of a decision and their respective probabilities before making a choice. The theory also assumes that individuals are risk-averse, meaning that they prefer a certain outcome to an uncertain one with the same expected value.

Calculating expected utility involves two main steps: first, determining the utility of each possible outcome, and second, multiplying the utility of each outcome by its probability and summing up the results. This calculation provides a single number that represents the expected utility of the decision.

Overall, expected utility is a useful tool for decision-making under uncertainty. It allows individuals to weigh the potential outcomes of a decision and their respective probabilities, and make a rational choice that maximizes their expected utility.

Calculating Expected Utility

Expected utility is a useful tool for decision-making under uncertainty. It allows individuals to evaluate the potential outcomes of a decision based on the probability of each outcome occurring and the utility (value) of each outcome. The expected utility can then be used to compare different options and determine the best course of action.

Identifying Possible Outcomes

The first step in calculating expected utility is to identify the possible outcomes of a decision. For example, if a person is deciding whether to invest in stocks or bonds, the possible outcomes might include a high return on investment, a low return on investment, or a loss.

Assigning Probabilities

Once the possible outcomes have been identified, the next step is to assign probabilities to each outcome. Probabilities can be based on historical data, expert opinions, or other sources of information. For example, if a person is deciding whether to invest in stocks or bonds, the probability of a high return on investment might be 30%, the probability of a low return on investment might be 50%, and the probability of a loss might be 20%.

Determining Utility Values

After assigning probabilities to each outcome, the next step is to determine the utility (value) of each outcome. Utility values can be subjective and can vary from person to person. For example, a high return on investment might have a utility value of 10 for one person and a utility value of 8 for another person.

The Expected Utility Formula

Finally, the expected utility can be calculated using the following formula:

EU = Σ (P × U)

Where EU represents the expected utility, P denotes the probability of each outcome, and U represents the utility value of each outcome. The formula is expressed as the sum of the product of the probability of each outcome and the utility value of each outcome.

By using the expected utility formula, individuals can make informed decisions that take into account both the probability and utility of each possible outcome.

Decision Making with Expected Utility

Choice Under Uncertainty

Expected utility theory is a useful decision-making tool when an entity does not know the outcome. Individuals can calculate expected utility by summing up (probability x utility) for every outcome. By incorporating expected utility into the financial decision-making process, one can make more informed choices that align with their individual preferences and risk tolerance.

Risk Aversion and Expected Utility

Expected utility theory is used to make decisions when the outcome is uncertain. A person will choose the outcome with the highest expected utility. However, risk aversion can affect the decision-making process. Risk-averse individuals will choose an option with lower expected utility but lower risk, while risk-seeking individuals will choose an option with higher expected utility but higher risk.

Limitations of Expected Utility in Decision Making

While expected utility theory is useful in decision-making, it has limitations. One limitation is that it assumes individuals are rational and have complete information about the outcomes. In reality, individuals may not have complete information or may not be rational in their decision-making. Additionally, expected utility theory does not take into account emotions or the subjective nature of individual preferences.

In conclusion, expected utility theory is a valuable tool in decision-making under uncertainty. By calculating expected utility, individuals can make more informed choices that align with their preferences and risk tolerance. However, it is important to recognize the limitations of expected utility theory and consider individual emotions and preferences in the decision-making process.

Applications of Expected Utility

Expected utility theory has a wide range of applications in various fields, including economics, finance, insurance, actuarial science, and healthcare decision analysis. This section will explore some of the most common applications of expected utility theory in these fields.

Economics and Finance

Expected utility theory is widely used in economics and finance to model decision-making under uncertainty. It helps decision-makers to evaluate the expected value of different options and make rational choices based on their preferences. For example, an investor may use expected utility theory to calculate the expected return and risk of different investment options and choose the one that maximizes their expected utility. Expected utility theory is also used in public policy to evaluate the welfare effects of different policies and social arrangements [1].

Insurance and Actuarial Science

Expected utility theory is a fundamental concept in the field of insurance and actuarial science. Insurance companies use expected utility theory to calculate the expected value and risk of different insurance policies and set premiums accordingly. For example, an insurance company may use expected utility theory to calculate the expected value of a life insurance policy and set the premium based on the expected utility of the policyholder. Actuaries also use expected utility theory to model the risk of different events and calculate the expected value of future cash flows [2].

Healthcare Decision Analysis

Expected utility theory is increasingly used in healthcare decision analysis to model the preferences and values of patients and healthcare providers. It helps decision-makers to evaluate the expected value of different treatment options and make informed decisions based on their preferences and goals. For example, a patient may use expected utility theory to evaluate the expected benefits and risks of different treatment options and choose the one that maximizes their expected utility. Expected utility theory is also used in health economics to evaluate the cost-effectiveness of different healthcare interventions and policies [3].

In summary, expected utility theory is a powerful tool for decision-making under uncertainty and has a wide range of applications in various fields. It helps decision-makers to evaluate the expected value and risk of different options and make rational choices based on their preferences and goals.

[1] Investopedia

[2] Corporate Finance Institute

[3] National Center for Biotechnology Information

Critiques and Alternatives to Expected Utility Theory

Expected Utility Theory (EUT) is a popular model used to understand decision-making under uncertainty. However, the theory has faced several critiques, leading to the development of alternative models. This section will discuss (livebookmark.stream) some of the most important critiques of EUT and describe some extensions/alternatives that have been developed to accommodate these critiques.

Prospect Theory

Prospect Theory (PT) is an alternative to EUT developed by Daniel Kahneman and Amos Tversky in 1979. PT explains that people evaluate outcomes relative to a reference point and are more sensitive to losses than gains. Thus, the theory suggests that people are risk-averse when faced with gains but risk-seeking when faced with losses. PT also suggests that people are more likely to choose a certain outcome over a risky outcome when the potential losses are greater than the potential gains.

Rank-Dependent Utility

Rank-Dependent Utility (RDU) is another alternative to EUT that was developed in the 1990s. RDU suggests that people evaluate outcomes based on the rank of the outcome relative to other possible outcomes. This means that people are more likely to choose an outcome that is ranked higher than other outcomes, even if the difference in expected utility is small. RDU also suggests that people are more sensitive to changes in probabilities when the probabilities are low, which is known as the probability weighting function.

Regret Theory

Regret Theory (RT) is an alternative to EUT that was developed in the 1980s. RT suggests that people evaluate outcomes based on the regret they would feel if they made a certain decision. This means that people are more likely to choose an option that minimizes their potential regret, even if the expected utility of the option is lower than other options. RT also suggests that people are more likely to take risks when they have already experienced regret in the past, as they want to avoid feeling regret again.

In summary, EUT is a widely used model for decision-making under uncertainty, but it has faced several critiques leading to the development of alternative models such as PT, RDU, and RT. These alternative models provide a more nuanced understanding of decision-making and have been applied in various fields such as economics, psychology, and neuroscience.

Frequently Asked Questions

What are the steps involved in calculating expected utility for different outcomes?

To calculate expected utility for different outcomes, an individual must first determine the probability of each outcome occurring. Then, they must assign a utility value to each outcome, which represents the satisfaction or happiness derived from that outcome. Finally, they must multiply the probability of each outcome by its corresponding utility value and sum the results. The resulting figure represents the expected utility of the decision.

How does one differentiate between expected utility and expected value in decision-making scenarios?

Expected value refers to the average outcome of a decision, while expected utility takes into account the satisfaction or happiness derived from each outcome. In other words, expected value is a purely objective measure, while expected utility incorporates subjective factors.

What is the role of the utility function in determining expected utility?

The utility function is used to assign a value to each outcome based on its perceived satisfaction or happiness. The function maps the outcomes to a numerical scale, allowing for comparisons between different outcomes. The utility function is a crucial component of expected utility theory, as it allows individuals to make decisions based on their subjective preferences.

How can expected utility be applied to game theory and strategic decision making?

Expected utility theory is commonly used in game theory and strategic decision making to determine the optimal course of action. By calculating the expected utility of each possible decision, individuals can select the option with the highest expected utility. This approach is particularly useful in situations where the outcomes of different decisions are uncertain.

What methods are used to calculate the expected utility of a lottery or gamble?

There are several methods used to calculate the expected utility of a lottery or gamble, including the expected value method, the certainty equivalent method, and the risk premium method. Each method involves different assumptions and calculations, and the most appropriate method will depend on the individual's risk preferences and the specific details of the decision.

In what ways does expected utility theory assist in making economic decisions?

Expected utility theory is widely used in economics to model decision-making under uncertainty. By taking into account the subjective preferences of individuals, expected utility theory provides a more realistic model of decision-making than traditional economic models. This approach allows economists to better understand and predict the behavior of consumers and investors, and to design policies that are more effective in achieving desired outcomes.