EAE6089 · Graduate
Department of Economics, School of Economics, Business and Accounting (FEA-USP)
Danilo Souza · August 3 - October 11, 2026
Description
Mission
This course prepares students to engage critically with the economics of crime, with an emphasis on empirical research that uses modern methods of causal identification. We cover the effects of policing, punishment, labor market conditions, and education on crime, as well as public policy in illegal markets and the dynamics of organized crime. Students will learn to assess the existing evidence, identify gaps in the literature, and design original projects with the potential for high-impact publication.
Prerequisites
Students should be comfortable with microeconomic theory — in particular the analysis of market failures and welfare — and with modern methods of causal identification, including differences-in-differences, regression discontinuity, and instrumental variables. Prior coursework in econometrics is strongly recommended.
Content summary
- Motivation: data, the state of the field, and empirical challenges
- The rational choice model: static and dynamics
- Policing, enforcement, and discrimination
- Incarceration, monitoring, and punishment
- Labour market conditions and education
- Organised crime: causes and consequences
- Illegal markets and drugs
A detailed reading list for each topic is available above.
Meetings
- Mondays and Wednesdays, 4:00–5:50 PM
- Room A-8, FEA I Building
- August 3 - October 11, 2026
Assessment
Assessment has three components: (i) a referee report on an unpublished paper, (ii) a class presentation of a published paper, and (iii) an original research project on a topic related to the course, submitted as a 10–15 page paper and presented in class. The first two are worth 20% each; the project accounts for the remaining 60%.
Key dates
- Referee report due on 11 September
- Research project presentations: 23 & 28 September
- Final research project due on 9 October
Use of AI
AI tools are not prohibited, but they must not form the basis of your work: the analysis, the interpretation, and the ideas must be yours. This course follows the standards now set by academic publishers, and you are strongly encouraged to read both — they are short, and you will be held to them when you submit your own papers: Elsevier and Wiley.
Every submission in which AI was used must close with a section titled ``Declaration of generative AI and AI-assisted technologies in the [referee report / manuscript] preparation process’’, stating exactly which tool was used and at which stages. Use the templates provided by either publisher. Basic spelling and grammar checks need not be declared.
When writing your referee report, never upload the paper, or any part of it, into an AI tool. An unpublished manuscript is a confidential document, and doing so may violate the authors’ confidentiality and proprietary rights.
Questions
Questions that come up during class are best resolved in class. For anything that remains, please come to office hours. Short questions — ones that fit in a few lines — can be sent by email with the subject line EAE6089 — FirstnameLastname. Beyond that, feel free to reach out in person or by email about anything else.