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.

This course offers an introduction to computational social choice. This is an interdisciplinary field, combining knowledge from economics and computational science. 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 algorithms for the implementation of social choice procedures;
1.2. Knowing how to present and interpret the results produced by these algorithms to answer research questions in social choice (widely interpreted);
1.3. Knowing the hypotheses at the basis of the algorithms studied during the course and their logical consequences on the output.

2. Applying knowledge and understanding:
2.1. Applying the algorithms studied in the course to answer a research question in social choice;
2.2. Comparing the results produced by alternative 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 algorithms.

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

4. Lifelong learning skills
4.1 Master complex algorithmic reasoning;
4.2 Master principles of social choice 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) voting;
2) fair allocation;
3) coalition formation;
4) additional topics.

F. Brandt, V. Conitzer, U. Endriss, J. Lang, A.D. Procaccia (2016), Handbook of Computational Social Choice, Cambridge University Press

Grading is comparative. It is based on three components: a) problems sets (40\%); b) critical notes (20\%); c) research project with final discussion (40%)
Problems sets combine formative and summative evaluation.

There will be fifteen meetings of 1h30’ each, mostly based on frontal teaching.
Interactive learning is encouraged but it is expected to take away from class, because the standard UniVE format is too compact --- leaving no sufficient time for students to efficiently 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.

written and oral