About
Table of contents
- About
- Lectures & Tutotials
- Prerequisites
- Grading
- Research Proposal
- Assignments
- Fraud, Plagiarism, & Academic Integrity
- Resources
About
This is a Behavioral Economics Reading Group course. This course is offered by the Department of Economics at the European University at Saint Petersburg. The course is designed to introduce graduate students to classical and recent literature on various topics predominantly in the domain of behavioral economics and political economy.
Lectures & Tutotials
The course is designed to function as a discussion group; therefore, no explicit lectures are scheduled, except for the first one—an introduction to the field, which will be delivered during the initial meeting. Overall, there will be one introductory lecture and eight discussion meetings. At the beginning of the course, participants will vote to choose eight topics out of the following 16.
Prerequisites
Intermediate courses in Calculus, Linear Algebra, Probability Theory, and Mathematical Statistics, as well as a basic course in Standard Game Theory, are required. A basic course in Behavioral Economics will be an advantage.
Grading
The grade for the course will be based 50% on the quality of the group discussions and 50% on the research proposal. Students who score 55 points or more during the course are considered to have successfully passed. There are two grades available: one for those who passed the course (55-84) and another for those who passed with distinction (85-100). Please note that in the event of plagiarism detection, the paper will receive a score of 0 (refer to section 7 for details).
Research Proposal
Each student will develop an individual or group novel research idea for an experimental study. Each project should include the following points:
Introduction:
A strong motivation for the research on the chosen phenomenon, a clearly formulated research question, and a deep discussion of major (expected) implications of the study and its societal relevance.
Literature review:
A brief overview of previous work in the chosen field of students’ interests (using Google Scholar, RePEc, and similar resources).
Experiment design:
A detailed description of the proposed experiment.
Hypotheses:
Several statements, each aligned with the design of the proposed experiment and motivated by existing literature.
Discussion:
A discussion of the limitations of the proposed experimental study should be provided, along with a more general discussion of the (expected) results, comparing them to existing literature.
Assignments
Each participant in the course is expected to familiarize themselves with all the papers scheduled for a particular meeting (detailed information on the meeting schedule and respective readings will be available here after the first course meeting). Being prepared to discuss the key aspects of each paper—its motivation, theoretical/empirical/experimental background, hypotheses, research methodology, key findings, and general discussion—is essential to fully participate in the group discussion.
Fraud, Plagiarism, & Academic Integrity
Any instance of academic dishonesty will be considered a grave offense. Each participant in the course is expected to be familiar with and adhere to the norms and values that uphold academic integrity. The most severe transgressions that undermine this integrity include fraud and plagiarism. Plagiarism, a type of fraud, is defined as the unauthorized use of another author’s work without appropriate citation. Please be aware that the deliberate usage of AI-generated content (e.g., ChatGPT) in the final paper will be deemed as fraud. In the event that the course instructor uncovers a case of fraud or plagiarism, the University’s Ethical Committee may impose substantial sanctions on the offender. The most stringent sanction that the Committee may impose is the submission of a request for the student’s expulsion to the University Board.
Resources
All resources will be made available to course participants.
A PDF syllabus for this course can be found here.