78176 - Behavioral Economics

Course Unit Page


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

No poverty Decent work and economic growth Sustainable cities Partnerships for the goals

Academic Year 2020/2021

Learning outcomes

At the end of the class, the student has acquired knowledge of the most active and influential areas of research in behavioral economics. In particular, the student understands the empirical methodologies adopted, the theoretical implications of the findings, and their possible applications in economic environment with and without strategic interaction.

Course contents

The core theory used in economics rests on basic assumptions on individual selfishness, rationality and utility maximization. During the last three decades, these assumptions have been put into question by a growing stream of literature, broadly defined as “behavioral economics,” which aims at improving the descriptive accuracy of these assumptions, while maintaining the formal discipline of economic modeling. Based on field and experimental evidence on how individual behavior departs from the conventional theoretical predictions, behavioral economists have posited explanations for these departures, proposed extensions to the existing models and alternative theoretical approaches aimed at capturing them, and considered what are the possible practical implications of these findings.

This course aims at providing a critical overview of the most active and influential areas of research in this field, with a focus on the empirical methodologies adopted, on the theoretical implications of the findings, and on their possible applications (e.g. in the fields of health and labor economics, finance, marketing). It is divided into two main sections, the first dealing with individual choices, the second with strategic interaction. In the first part of the course we will discuss topics related to preferences over risky and uncertain outcomes, intertemporal choices, reference dependence and loss-aversion. In the second part of the course, we will deal with the literature concerning behavioral game theory, which uses the tools of standard game theory, but takes into consideration emotions, mistakes, limited foresight, and doubts about how smart others are.

A basic knowledge of game theory and microeconomics is a pre-requisite for attending the course.


Part 1

  • Anomalies: framing, anchoring and preference reversal
  • Decision making under risk
  • Mental accounting, reference dependence, loss aversion and endowment effect
  • Intertemporal preferences

Part 2

  • behavioral game theory
  • social preferences

Part 3

  • criticisms to behavioral economics
  • conclusions


Dhami, Sanjit. "The Foundations of Behavioral Economic Analysis." Oxford University Press, 2016.

DellaVigna, Stefano. "Psychology and Economics: Evidence from the Field." Journal of Economic Literature 47.2 (2009): 315-372.

Camerer, Colin F., George Loewenstein, and Matthew Rabin, eds. Advances in behavioral economics. Princeton University Press, 2003.

Camerer, Colin. Behavioral game theory: Experiments in strategic interaction. Princeton University Press, 2003.

Teaching methods

Each class will be devoted to the discussion of one core issue in behavioral economics. Before or during the classes, students will be invited to participate in a short on-line mock experiment, replicating the basic features of the studies that will be later presented. Results will be later analyzed and compared to those prevailing in the literature. The second part of the class will be dedicated to the theoretical models developed to account for the empirical findings, and the last part will deal with their policy implications and possible practical applications.

Assessment methods

Students will be assessed based on four weakly problem-sets, and a final in-class exam.

The final examination aims at evaluating the achievement of the following goals:

- knowledge of the most influential models of behavioral economics, in the realms of decision making under uncertainty, intertemporal decision making, behavioral game theory, and social preferences.

- understanding of the empirical methodologies adopted in the articles surveyed during the course

- understanding of the theoretical implications of the empirical findings, and their possible practical implications.

The problem sets will be published on the course' e-learning platform.

In the problem-sets (accounting for 5% of the mark each) students will have to comment or interpret graphs, figures and equations from the studies discussed in class, or briefly summarize the results. For the problem-sets teamwork is allowed but in the end each student will have to hand in his own answer, and “carbon-copied” works will be strongly penalized.

The final exam (80% of the mark) will last 2 hours, and will include a set of 6 questions of increasing complexity, covering both the mathematical/analytical aspects of the models discussed in class and their interpretation.

The exam will be held in the computer lab, or on line if the health situation does not allow to hold it in person. Questions will be randomly extracted from a predefined set, so the exam content will be different for each student.

In the final exam students may use calculators (but not other electronic devices), but they may not communicate with others, consult notes, books, or other written material. Any attempt to violate these rules will result in the student's exclusion from the exam.

An example of the final exam is available here:


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.

Participation in the mock experiments and the completion of the four problem sets is required. Attending classes is instead not compulsory, even though it is recommended.

The mock experiments will be computer-based and will require the use of a pc, tablet or smartphone connected to the internet.

Office hours

See the website of Maria Bigoni