95859 - Introduction To Behavioral Economics

Learning outcomes

The goal of this course is to introduce students to the vast field of behavioral economics, an interdisciplinary area that employs the employs concepts from economics and psychology to gain a deeper understanding of individual behavior. The theory has important applications to finance, the organization of human resources and the labor market, consumer behavior, marketing, health, and the associated public policies.

Course contents

Requirements:

The course relies on basic notions of microeconomics and game theory, and makes use of simple algebra and calculus.

MAIN TOPICS

Part 1: Individual decisions

Choice under risk and uncertainty.

In this set of classes, we will focus on individual decision making when the payoff outcomes cannot be known for sure in advance. After having reviewed the basic concepts of Expected Utility Theory, we will discuss some “anomalies” in lottery-choice situations, and other observed departures from the theoretically optimal behaviour, and we will discuss Prospect Theory as an alternative model of choice under risk and uncertainty.

Information and learning

Information specific to individuals is often unobserved by others. Such information may be conveyed at a cost, but misrepresentation and strategic non-revelation is sometimes a problem. Informational asymmetries yield rich economic models that may have multiple equilibria and unusual patterns of behavior. Here we will consider how information is used to form and update beliefs (Bayesian updating and behavioral models of learning). Finally we will study situations in which people may learn from others’ actions, giving rise to bandwagon effects.

Part 2: Behavioral Game Theory

This part presents several games in which behavior is influenced by intuitive economic forces in ways that are not captured by basic game theory. We will consider models that try to account for these empirical regularities, by relaxing the strong game-theoretic assumptions of perfect rationality and perfect predictions of others’ decisions.

Part 3: Social preferences

Bilateral bargaining

This part focuses on the issues of fairness, equity, trust and reciprocity within the framework of bilateral bargaining. We will review the vast experimental literature on these issues, which highlight how – under several circumstances – observed behavior tends to depart in substantial ways from the standard theoretical predictions.

Public choice

This part focuses on situations in which the outcome, and the social welfare, depends on the behavior of a large set of agents. We will study situations where the actions taken by some people affect the well being of others. Examples are the provision of public goods, and the exploitation of common resources.

Part 4: Behavioral macroeconomics and behavioral finance

Behavioral macroeconomics

This part covers studies that are motivated by macro issues of consumption, banking, and multi-market production, in the attempt to provide some insights in the understanding of banking and macroeconomics crises.

Behavioral finance

This part reviews the main insights from the field of Behavioral finance, which approaches the study of financial phenomena through the lenses of models that do not rely on the assumption of agents' full rationality. We will explore the main types of deviations form full rationality that have been shown to impact on financial markets, the emergence of financial bubbles, and the literature on the "limits to arbitrage," which discusses the consequences that these departures from the rationality paradigm may have on the equilibrium outcomes.

Readings/Bibliography

Required material
The required material consists of lecture notes, slides, quizzes, and any additional readings indicated by the instructor. These materials will be made available on the course’s e-learning platform, Virtuale, and are necessary to prepare for the exam, both for attending and non-attending students.

Main references
Holt, Charles A. Markets, Games, & Strategic Behavior. Second edition. Princeton University Press, 2019.
Barberis, Nicholas, and Richard Thaler. “A Survey of Behavioral Finance.” In Handbook of the Economics of Finance, Vol. 1B, edited by G.M. Constantinides, M. Harris, and R. Stulz. Elsevier, 2003.
Barberis, Nicholas. “Psychology-Based Models of Asset Prices and Trading Volume.” NBER Working Paper No. 24723.

Additional material
Additional readings, exercises, and links to online learning material may be provided through Virtuale during the course.

Teaching methods

Teaching will combine participation in mock experiments, active online learning exercises, quizzes, classroom discussion, and traditional lecturing. Attending classes is not compulsory but highly recommended, as participation in classroom experiments and discussions is meant to help students understand the topics of the course and connect theoretical models to observed behavior.

Assessment methods

The final exam aims to verify the acquisition of the following learning outcomes:

• basic knowledge of the methodology of experimental economics;
• understanding of the main differences between the predictions of the standard neoclassical model and the alternative predictions of behavioral models;
• ability to apply behavioral models to interpret and predict behavior in simple frameworks.

Students will be assessed based on their performance in a written and oral final exam. The written part of the exam will be held in the computer lab and will contain multiple-choice questions and exercises with numerical answers. The oral part will include open questions and will assess students’ ability to explain the models discussed in class, interpret their implications, and apply them to simple economic environments.

The written part of the final exam lasts one hour. Students may access the oral part only if they pass the written part. The final grade is the sum of the scorse obtained in the written and in the oral part of the exam.

Students also have the option of taking two midterm exams. The structure of the full exam is equivalent to the sum of the content of the two midterms. The midterm exams also include a written part (lasting 30 minutes) and an oral part. In case the student takes both midterms, the final grade is given by the average of the grades obtained in the first and in the second midterm.

The dates of the final exams are fixed and cannot be changed. Requests for additional dates will not be accepted.

During the written part of the exam, students may use standalone calculators, but they may not use any other electronic devices apart from the computer assigned to them for the exam. They may not communicate with others, consult notes, books, or other written material, or access resources other than those explicitly made available for the exam. Any attempt to violate these rules will result in the student’s exclusion from the exam.

Students with learning disorders and/or temporary or permanent disabilities are invited to contact the responsible University office as soon as possible (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students ). The office will propose possible adjustments. Requests for adaptation must be submitted to the lecturer at least 15 days before the exam date; the lecturer will assess the appropriateness of the proposed adjustments, taking into account the teaching objectives of the course.

The maximum grade is 30 cum laude.

The grade is graduated as follows:

• below 18: failed;
• 18–23: sufficient;
• 24–27: good;
• 28–30: very good;
• 30 cum laude: excellent.

Grade rejection: students can reject the grade obtained at the exam only once. To this end, they must email a request to the instructor by the grade registration deadline. The instructor will confirm receipt of the request by the same deadline.

Rejection refers to the whole exam. If the grade is rejected, the student must retake the full exam. The only grade that can be rejected without any communication from the student is the grade obtained in the first midterm: in this case, the student can either take the second midterm or sit the full exam, thereby losing the grade obtained in the first midterm.

Students sitting the first midterm can take the second midterm on the first examination date set for the full exam, right at the end of the integrated course, or on the following exam call. A student can sit the second midterm only once; if they fail or reject the grade obtained, they will have to resit the full exam and will lose the grade obtained in the first midterm.

For assessment purposes, the use of generative AI is not allowed during the written exam, the oral exam, or the midterms. Any use of generative AI during assessment activities constitutes a violation of academic integrity.

Teaching tools

During the course, students will be involved in mock experiments, which should provide them with a more vivid idea of the issues to be examined later during the lecture. Active participation in in-class discussion will be encouraged.

Attending classes is not compulsory, but highly recommended.

Students will also be invited to constantly test their understanding of the basic concepts discussed in class by means of quizzes published on Virtuale. Quizzes are not compulsory, can be retaken as many times as students wish, and will not be graded. The tutor of the course will be available one hour per week to answer questions on the quizzes.

Lecture notes, slides, quizzes, and any additional material will be made available through Virtuale.

Generative AI tools may be used as a support for individual study, for example to summarize notes, revise concepts, or generate self-assessment questions. Their use in assessment activities is regulated by the rules stated in the Assessment methods section.

Office hours

See the website of Maria Bigoni