84563 - BEHAVIORAL ECONOMICS

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Decent work and economic growth Sustainable cities Responsible consumption and production Climate Action

Academic Year 2019/2020

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

Main reference:

Holt, Charles A. Markets, games, and strategic behavior: An Introduction to Experimental Economics. Second edition. Princeton University Press, 2019.

We will cover Parts I, II, and III, and chapters 24 and 25.

Additional readings on behavioral finance:

Barberis, Nicholas, and Richard Thaler. A survey of behavioral finance; in "Handbook of the Economics of Finance", Vol.1B, Eds. Constantinides, George .M, and Milton Harris. Elsevier 2003.

Barberis, Nicholas. Psychology-based Models of Asset Prices and Trading Volume (Working Paper No. 24723). National Bureau of Economic Research. https://doi.org/10.3386/w24723

Both articles will be used only in part, as additional references since the main textbook does not cover this topic.

Lecture notes:

The lecture notes will be made available on the IOL platform before each class (but might be corrected/updated shortly after the class). They should NOT be taken as the only reference, as they often do not cover the analytical details discussed in the manual, which are important for a thorough understanding of the subject matter.

Teaching methods

Teaching will combine participation in mock-experiments, active on-line learning exercises, and traditional lecturing. Attending classes is not compulsory but highly recommended, as participation in the classroom experiments and discussions is meant to help students’ understanding of the topics of the course.

Assessment methods

The final exam aims at verifying 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 written final exam which will include a set of questions covering both the mathematical/analytical aspects of the models discussed in class and their interpretation.

In the final exam students may use calculators (but not other electronic devices), but they may not consult notes, books, or other written material (including their classmates' exam papers).

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

The maximum grade in the final exam is 30 – and this also holds for the two midterm exams. In case the student takes the mid-term exams, the final grade is given by the average of the grades obtained in the first and in the second mid-term.

To get the “award” (30 cum laude) student will have to do a presentation on a topic of their choice, among those discussed in the course. The presentation can also contribute to the determination of the final grade, adding up to 2 bonus points to the grade obtained in the final exam. The presentation is not mandatory. Presentations will take place on November 29 and December 4.

Grade rejection: students can reject the grade obtained at the exam only once. To this end, they must email a request to the instructor within the date set for registration. The instructor will confirm reception of the request within the same date.

Rejection is intended with respect to the whole exam, whose grade is the average of the grades obtained in the two mid-terms. If the grade is rejected, the student must retake the full exam (consisting of both parts). The only grade that can be rejected without any communication from the student is the one of the first mid-term: in this case the student can either take the second mid-term or sit the full exam (thus losing the grade obtained in the first mid-term).

Students sitting the first mid-term can take the second mid-term on the first examination date set for the full exam, right at the end of the integrated course, or on the following call. A student can sit the second mid-term only once; if he/she fails or rejects the grade obtained, he/she will have to resit the full exam and will lose the grade obtained in the first mid-term.

The bonus points from the presentation can be used again after the grade rejection, but are only valid in case the student passes the exam by February.

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, and active participation to the in-class discussion will be encouraged.

Attending the classes is not compulsory, but highly recommended.

Students will also be requested to constantly test their understanding of the basic concepts discussed in class by means of quizzes that will be published on the on-line e-learning platform (IOL) at the end of each week. Quizzes are not compulsory, can be retaken as many times as students wish, and will not be corrected. The tutor of the course will be available one hour per week to answer questions on the quizzes.

Office hours

See the website of Maria Bigoni