ADVANCED MICROECONOMICS

This is a second-year doctoral course. Topics may vary across different years. Content is geared towards students with interests in theoretical research, but it showcases applications useful for students with interests in applied or empirical areas.

(The topic for 2026-2027 has not yet been chosen.) The goal of the course is building up interdisciplinary skills in economic modeling and open up novel pathways for research.

1. Knowledge and understanding:
1.1. Knowing models and algorithms;
1.2. Knowing how to present and interpret the results produced by these models and algorithms to answer research questions (widely interpreted);
1.3. Knowing the hypotheses at the basis of the models and algorithms studied during the course and their logical consequences on the output.

2. Applying knowledge and understanding:
2.1. Applying the models and algorithms studied in the course to answer a research question in social choice;
2.2. Comparing the results produced by alternative models or algorithms based on different set of hypotheses and their limitations concerning the research questions at hand;
2.3. Applying economic theory to assess the plausibility of alternative set of assumptions fed into the models or algorithms.

3. Evaluation and project skills:
3.1. Designing novel models or procedures (or tweaking existing one) to address an economic research question of interest;
3.2. Evaluating the contribution provided by models and algorithms available in the economic literature to address a research question of interest;
3.3. Thinking about the design of models and algorithms aimed at improving the existing knowledge base or address specific issues.

4. Lifelong learning skills
4.1 Master complex modeling and algorithmic reasoning;
4.2 Master theoretical methodologies to guide applications;
4.3 Ability to exploit new tools and adapt them to different contexts.

You must have successfully completed the first-year requirements for the doctoral program in Economics, including the comprehensive exam in Microeconomics. In particular, you are expected to be thoroughly familiar with contents analog to Chapters 1-5 and 7-8 of Jehle and Reny (2011), Advanced Microeconomic Theory, third edition. Familiarity with formal reasoning is necessary to fully benefit from the class. There are no coding prerequisites.

The course is arranged in four main blocks:
1) AI Demand.
2) AI Supply.
3) AI Pricing.
4) AI Policy.

I. Baley and L. Veldkamp (2025), The Data Economy: Tools and Applications.

J. Gans (2025), The Microeconomics of Artificial Intelligence .

R. Spiegler (2024), The Curious Culture of Economic Theory.

Teaching notes.

Grading is comparative. It is based on four deliverables components: a) class participation (discussion, random call); b) homework; c) one class presentation; d) one critical review or research project.
Problems sets combine formative and summative evaluation.

written and oral

The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

A+ 4,25 A 4,00 A- 3,75 A/B 3,5
B+ 3,25 B 3,00 B- 2,75 B/C 2,5
C+ 2,25 C 2,00 C- 1,75 C/D 1,5

There will be fifteen meetings of 1h30’ each.
Interactive learning is strongly encouraged, but it is expected to be carried out mainly away from class, because the standard UniVE format is too compact --- leaving no sufficient time for students to handle all the material covered.

For more information and updates, trust only the class Moodle page.

Ca’ Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support services and accommodation available to students with disabilities. This includes students with mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.