Making Better Decisions: Decision Theory in Practice

Making Better Decisions: Decision Theory in Practice

Itzhak Gilboa

Language: English

Pages: 232

ISBN: 1444336525

Format: PDF / Kindle (mobi) / ePub


Making Better Decisions introduces readers to some of the principal aspects of decision theory, and examines how these might lead us to make better decisions.

  • Introduces readers to key aspects of decision theory and examines how they might help us make better decisions
  • Presentation of material encourages readers to imagine a situation and make a decision or a judgment
  • Offers a broad coverage of the subject including major insights from several sub-disciplines: microeconomic theory, decision theory, game theory, social choice, statistics, psychology, and philosophy
  • Explains these insights informally in a language that has minimal mathematical notation or jargon, even when describing and interpreting mathematical theorems
  • Critically assesses the theory presented within the text, as well as some of its critiques
  • Includes a web resource for teachers and students

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switch to it, we may never get anywhere. By contrast, a preference for the status quo adds stability to our choices. It prevents us making too frequent changes, which have their own cost. c. Habit formation: We get used to certain products. Sometimes it’s a matter of changing tastes: you can get used to a particular brand of cereal, or beer, to an extent that your taste buds truly demand this product and no other. Sometimes it’s a matter of routine: you may not have a strong preference between

ticket, you should ignore it in your current decision. The amount of money you may have paid is a sunk cost, as it cannot be retrieved. And to many, rationality dictates that sunk costs be ignored. If you accept this reasoning, you should ask yourself why many people sometimes find themselves behaving differently, that is, taking sunk costs into account. Are there any circumstances where it actually makes sense to do so? Or are there modes of behavior that are generally effective and useful, but

researchers and friends, but I would be amiss not to mention David Schmeidler, who was my graduate advisor and has remained a close friend and collaborator ever since; Edi Karni, who taught me my first course on decision theory; and Peter Wakker, who, since our days as graduate students, has been and remains a wonderful source of knowledge on theory, experiments, and applications. I have benefited no less from the numerous students whom I have taught over the years. Without their input,

Decisions under Risk U X Y Figure 4.1 A concave function. If you take the bet, you will have a wealth of W + X, that is, the random variable ⎧W + 100 0.50 W+X=⎨ ⎩W − 100 0.50 And if you refuse the bet, you are left with your wealth, W, for sure. Assuming that you maximize the expectation of a function u(x), what will be your decision? Consider the graph shown in Figure 4.2. If you refuse the bet, you are left with W for sure, and the utility is u(W) with probability 1, implying that the

another example of an event that is uncertain in the sense that we do not know its probability. The same holds also for many personal decisions, such as the choice of a career or a spouse. When you get married no one provides you with the probability that you will end up divorcing, and relying on general statistics to infer this probability is not very promising. And similar uncertainty exists when you consider the possibility of success of a new business venture, or a new career path, and so

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