Assignments
Assessment
Assignments
Practice with theory, evidence, speaking, writing, and research design
The course combines problem sets, staged research work, presentations, oral discussion, and a final exam. Official submission instructions and due dates live on Canvas. The final exam takes place during the last class meeting on Wednesday, December 9; final research papers are due Wednesday, December 23, at 11:30 PM.
Grade Components
Brief, low-stakes exercises at the start of many class meetings support continuous engagement with readings and course material. The format may be a written response, an economic problem, or a quiz question; exercises may be individual or collaborative.
Two focused early-course problem sets develop fluency with transaction costs, incomplete contracts, best responses, Nash equilibrium, no-shirking models, and welfare analysis.
An early project-development exercise where students identify a fact about the world and begin connecting it to economics of work, organizations, or power. Brainstorming 1 is due Monday, September 28, at 5 PM on Canvas; submissions close at the same time. Upload a photograph or short document showing your initial brainstorm and the Claude or Codex output that develops or refines it. Explain what you started with and how the AI-assisted version improved it. Follow the assignment and brainstorming worksheet on Canvas.
A short proposal that names a research question, motivates its importance, identifies 3-5 relevant sources, and lays out a plan for the final project.
A serious beta draft of the research paper submitted before the final version, with feedback from the instructor and a peer reviewer.
Students present their projects to peers and practice explaining motivation, model, evidence, and implications clearly.
The final paper is submitted with a response explaining how the student used feedback and revised the argument.
A short in-person oral exam focused on problem-set content and relevant readings.
A sit-down final exam that complements the research project and checks comfort with the course's core theory and readings.
Participation
This is a discussion-based course. Students should prepare for class by reading the assigned chapters and articles, watching any posted videos, and arriving ready to discuss models, evidence, and implications.
Participation may include class discussion, helping fellow students, think-pair-share activities, in-class notes, and brainstorming. Graded in-class responses, problems, and quiz questions are described separately above.
Responsible Use of AI
Students are encouraged to learn how to use large language models and other AI tools responsibly, with attention to their benefits and their limits. AI tools can fabricate sources and make mistakes in mathematics and modeling, so students remain responsible for checking claims and understanding submitted work.
The final project includes a reflection on whether and how AI was used.