Courses

Informal talks on current research in Graph Theory, and providing the students the opportunity to present their own work, and learn communication and presentation skills.
Instructor: Ervin Győri
Credits: 3.0
The course is an introduction to labor economics, emphasizing applied microeconomic theory and empirical analysis. We are especially interested in the link between research and public policy. Topics to be covered include: labor supply and demand, taxes and transfers, minimum wages, immigration, human capital,...
Instructor: Andrea Weber
Credits: 4.0
We introduce the fundamental methods and toolkit needed to analyze dynamic general equilibrium optimizing models in discrete time. The goal of this course is to provide students with understanding a set of key macroeconomic models and how those can be taken to data. The solution/estimation methods reviewed during the...
Instructor: István Kónya, Tamás Briglevics
Credits: 4.0
This course presents the foundations of, and selected topics in, game theory. We will review basic definitions and equilibrium concepts, and develop applications ranging from auctions to political economy and industrial organization. The goal is to develop a structured way of thinking about strategic interactions,...
Instructor: László Kóczy
Credits: 2.0
This course will explore ways to integrate insights from psychology into economics by formalizing these insights by extending existing economic models. We will look at two types to enrich classical economic models. First, we will look at a richer set of preferences that people have, such as loss aversion, news utility...
Instructor: Marc Kaufmann
Credits: 4.0
Course code: CNSC 6000Level: DoctoralCourse Status: MandatoryBackground and overall aim of the course:Networks are ubiquitous. Economic trade, social relationships, terrorist organizations or biochemical reactions – all span networks. Network science has gone through a spectacular development recently. The data deluge...
Instructor: János Kertész
Credits: 4.0
This course gives an introduction into empirical methods used in modern industrial organization. We will discuss typical issues and solutions that come up in the estimation of production functions, demand systems, and models of industry competition. We will examine some applications of the above methods such as merger...
Instructor: Andrzej Baniak
Credits: 2.0
   The course covers key concepts in econometrics and intends to widen and deepen students’ knowledge of econometric methods. The first few lectures introduce some important econometric estimators, focusing on asymptotic theory in a cross-sectional data setting. The second part of the course is devoted to time series...
Credits: 4.0
This course gives a graduate level introduction to fundamental issues in particular areas in modernmacroeconomics, including long‐term growth, consumption, savings and asset pricing, investment in physicalcapital and inventories, and (if time permits) labor markets. The material also provides the foundation for...
Instructor: Attila Rátfai
Credits: 5.0
CORE: for MA Economics 1st year; MANDATORY: for 1st year PhD with no credits earnedMicroeconomic Theory I is the first course in the microeconomic theory series for the students enrolled in the MA in economics. The objective of this course is to provide students with standard graduate-level microeconomic tools. Topics...
Instructor: Alessandro De Chiara
Credits: 5.0
In the PhD workshop, students present their original research to other students and the instructors. The research presented should be preliminary, and interaction between the speaker and the audience is encouraged.
Instructor: Alessandro De Chiara, tba, Adam Zawadowski, tba
Credits: 0.0
IMPORTANT: This course can accommodate a maximum of 30 students. Priority is given to Mathematics students (Master and PhD) and Network Science PhD students. All other students are selected based on the entry test score. Students that take the course for grade have priority over auditors. All students, both registered...
Instructor: Roberta Sinatra
Credits: 3.0
The goal of the course is to introduce the students to the modern Bayesian econometric analysis of macroeconomic models. Although the course contains a set of theoretical examples and analytical derivations, its focus is mainly on the practical implementation. We will work with reduced-form and structural models and...
Instructor: Eyno Rots
Credits: 2.0