Teaching plan for the course unit

General Information

Competences / Learning outcomes to be gained during study

• — Ability to address relevant economic problems with accuracy in such areas as market regulation, industrial organization and public policy decision-making, and to propose solutions to these problems, drawing on the techniques of theoretical or empirical analyses and simulation.

• — Ability to apply knowledge of quantitative economics to the analysis of economic policy and business management.

• — Ability to write scientific articles that can be published in journals of economics and ability to present corresponding papers at international scientific conferences.

• — Ability to read and assess research papers in economics critically, and to identify their essential contributions to advancing the frontier of knowledge.

• — Ability to formulate original research questions and hypotheses within a relevant theoretical framework that can be tested empirically.

• — Skills to foster lifelong, self-directed/independent learning.

• — Ability to apply the knowledge acquired to problem solving in new or relatively unknown environments within broader (or multidisciplinary) contexts related to the field of study.

• — Ability to acquire the knowledge that fosters originality of thought in the development or application of ideas, above all in a research context.

Teaching blocks

Teaching methods and general organization

The methodology is centred on a series of lectures in which theoretical concepts and their applications to various models are presented and discussed. Mathematical proofs of the main theorems are also presented. Students are required to read and discuss various seminal papers in the field.

Official assessment of learning outcomes

Students are asked to read a paper in Market Design discussing an application of matching theory or auctions to real markets, and then to give a presentation about this application (40% of the grade). Students are provided with a list recommended papers during the course for this activity. Additionally, students sit a short written exam on the algorithms studied in class (10%).

The grades for the Behavioural Economics and Experimental Economics sections of the course are determined by the weighted average of a number of different assignments:

• An in-class presentation (25%) to be delivered in the final weeks of the semester. The paper will be either theoretical or empirical in nature and will address the application of a behavioural model analysed in class or a different type of behavioural bias/theory. Students are provided with a list recommended papers for this activity.
• Students can opt to write either an essay or a referee report (25%). More specifically,
  a) An essay describing a lab or a field experiment that they have conceived, in which an existing or a novel theory is tested. Students need to discuss their motivation for undertaking the experiment, highlighting the originality of the idea and its contribution to the extant literature. Details need to be presented of the structure of the design and the empirical strategy employed. The essay should serve as a spring board for the students’ future research work endeavours but it is not expected to be a detailed polished study at this stage (max. length 5/6 pages).
• A referee report of a recent research paper selected from a list provided by the instructor. The papers will be unpublished studies and the students, acting as reviewers, have to provide a summary, assess the paper’s contribution to the extant literature, identify any shortcomings and make recommendations as to how to improve the paper, mentioning possible extensions and/or potential locations for future research. Students are provided with detailed instructions at the beginning of the course.

A list of articles is made available during the course.

The final examination takes place on the date determined for that purpose. It consists of the following activities:

• The presentation of an article examining the application of matching theory or auctions to a real market (40%).
• A written exam on the algorithms studied in class, including the deferred acceptance and top trading cycle algorithms (10%).
• The presentation of either a theoretical or empirical paper concerning the application of a behavioural model previously analysed in class or of a different type of behavioural bias/theory (25%).
• A written essay on an original lab or field experiment or a referee report on a recent paper (25%).