The objective of the course is for students to develop critical evaluation of real-world developments and policies by dealing with the main macroeconomic accounts: the national income, the balance sheets and flow accounts of the government, the central bank, the banking sector, and the country as a whole in its transactions with the rest of the world. At the end of the course, students should be able to evaluate the assumptions and contingencies on which various policy positions are founded, and the strengths and weaknesses of alternative prescriptions. The class will discuss theory and empirics, and will often rely on publicly available datasets, with regular assignments in Python. Basic knowledge of math is needed. Grades will be based on problem sets + group projects for a term paper.

This is the first course in a sequence of 2 course, allong with Game Theory and Information Economics, that endows students with the basic insights of microeconomi theory. The goal of the course is to introduce students into the way economists see human interactions in markets, with markets broadly defined as places where economic activity takes place. The provided body of knowledge will allow student to understand how demand and supply interact in markets and welfare properties of the outcomes of the interactions.

This is the first course in the statistics sequence for the first year of the master's program. Its objective is to expose students to statistics and data science primarily from a practical perspective. While we will cover econometric theory as necessary, the focus will largely be on application. The goal of the course is to be as applied as possible, with students frequently engaging in programming exercises, preparing them for their own research projects and careers as applied economists.

We will study a few papers that represent the current issues in the government policy dealing with inflation and debt. Afterwards, we will continue with some other papers if there is time left. One half of classes will consist of me covering the contents of the papers including the discussion of your questions. The other half of classes will consist of your presentations of papers and possibly other materials.

This is the second course in the microeconomics sequence and it builds heavily on the first course on microeconomics I. The course consists of two parts. In the first part, the accent will be on a bit more rigours and more general treatment of monopoly, game theory and imperfect competition. The second part will introduce the foundational concepts in information economics (such as adverse selection, moral hazard, signalling and screening). Each concept will be followed by discussion of its economic applications.

This is the second course in a sequence of 2 courses designed to familiarize students with the basic concepts of statistics and econometrics. The goal of the course is to provide students with an an introduction into econometric theory and various practical applications. A central focus will be on regression models, their variations, and the challenges that can arise in practical applications. Therefore, students will learn to apply the theoretical concepts seen in class using statistical software, such as R or Stata.

This course focuses on professional writing in Economics in English in a variety of genres. Students will practice their analytical writing skills in formal, post-graduate level English. There is an emphasis on academic integrity, and the types of grammatical structures and language used in a variety of professional texts in the field. The course includes lectures, peer input on the main tasks throughout development of the work, and individual consultations with the instructor. Extensive written feedback is given with a view to supporting future work.

The main tasks are a position paper and presentation of the paper. The paper should be relevant to the student’s planned MA thesis and its text should be transferable to related papers. Students choose topics that reflect their personal interests in the field.

The skills practiced on this course are designed to support student writing and speaking throughout their studies and beyond into real-world contexts.

The RW1 course includes a focus on development of the required Topic Request Submission paper. RW1 students are required to agree with a faculty member who will chair their MA thesis and to choose an MA thesis topic by April 3, and to notify the instructor and SAO of the chair and topic.

This is a graduate-level course on selected approaches in so-called “structural” econometric estimation, with emphasis on methods originally devised in industrial organization, but applicable also in different fields. Following a review of some key econometric concepts and tools (identification, estimation frameworks, discrete choice models), the course overviews the main econometric approaches adopted in selected areas of industrial organization, such as the estimation of demand and production functions, the analysis of strategic interactions (especially in the setting of oligopolistic competition), and spillover effects (with particular regard to cross-firm spillovers). An objective of the course is to endow attendants with some minimal computational tools that would enable them to implement the reviewed methods on actual data about markets and firms. A number of lectures, as well as many of the course assignments that inform the final grade, are built around coding exercises. While not strictly required, some degree of familiarity with a high-level programming language the likes of R, Python or Julia is desirable, as it would facilitate navigating the course.

This is a second-year graduate-level course. The course is based on selected and (mostly) recent empirical research papers focusing on particular aspects of the economic history of the United States, paying particular attention to the topics of internal and international migration, cities, innovation, and culture. Beyond providing students with an in-depth understanding of the research frontier in US economic history, the course will focus on developing skills in developing, communicating, presenting, and evaluating research ideas and causal research designs in applied economics more broadly.

The course will provide fundamental understanding of stylized labor supply and demand in their static and advanced versions, and associated models of wage determination. The course will combine theoretical concepts, empirical evidence and empirical methods including use of econometrics and individual level data. Policy and mechanism designs debates involving students will be encouraged.
The course has three major goals (i) to guide students through current theoretical and empirical understanding of major labor market issues, (ii) to promote student’s own empirical research on topic selected, (iii) to make students familiar with stylized research resources, field standards and approaches. Throughout the topics, empirical methodological approaches will be clarified (data and econometric / identification techniques).
The prerequisite for are principles of microeconomic theory, statistics and econometrics from the 1st year.

The goal of the course is to introduce tools necessary to understand and implement empirical studies (evaluations of causal effects) with cross-sectional and panel data. Heterogeneous treatment effects and dynamic panel data models fall outside of the scope of the course, as do machine learning techniques and AI. Examples from applied work will be used to illustrate the discussed methods. Note that the course covers much of the work of the Nobel prize laureates for 2000 and 2021. The main reference textbook for the course is Econometric Analysis of Cross Section and Panel Data, Jeffrey M. Wooldridge, MIT Press 2002. I provide suggestions for reading and additional references throughout the lecture notes (available on my homepage).

This course is the second step in student’s ongoing practice of their professional communications skills in the broad field of economics. It includes written tasks, a negotiation, and presentations, and continues the collaborative features of Research Writing 1. Lectures, discussions, teamwork, and individual consultations with the instructor are aimed to continue to build student’s skills and confidence, and to provide useful take-aways for real-world endeavors. The skills practiced on this course are designed to support student writing and speaking throughout their studies and beyond into real-world contexts. The RW2 course includes a focus on MAER students’ early development of their required Master’s thesis. Development of the thesis will be supported via in-class work and individual consultation with the instructor.

The main topics of the class are econometric approaches to the problem of sample selection and (individual-level) heterogeneity. While the methods apply more generally, the class will focus on methods to address the selection problem from the program evaluation literature and place particular emphasis on heterogeneity in randomized control trials in the second part of the course

This course focuses on the theoretical study of market power, covering key concepts and models in static and dynamic oligopoly theory, along with their applications. It examines how firms behave in industries where a few competitors interact strategically, meaning they must consider each other's actions. These strategic interactions have both positive (e.g., pricing, market structure, innovation intensity) and normative implications (e.g., competition policy). While the emphasis is on positive analysis, the course also frequently addresses the normative aspects.

This course focuses on economic development with an emphasis on economic history, culture, and political economy. We will use a historical and comparative approach to explore how societies evolve and develop. Specifically, we will examine research on whether differences in contemporary economic development have historical origins. We will also study the mechanisms and channels through which history influences development, with particular attention to the role of domestic institutions and culture in explaining historical persistence. While this research area uses the methods of economics, the research questions overlap with those in other disciplines like history, psychology, political science, anthropology, and geography. We will discuss methods for observational data as well as for survey data collection and field experiments.

Michal Kejak: The increasing complexity in the analysis of theoretical and applied dynamic macroeconomic models—primarily due to the lack of available analytic solutions for most of them, and when they do exist, they are often trivial simplifications of the original problem—necessitates the use of efficient numerical methods in macroeconomics. The first part of the course is devoted to elementary concepts of numerical analysis and basic numerical methods, while the second part focuses on numerical methods for solving dynamic macroeconomic models. Students will be expected to write their own simple programs and run application programs and toolboxes in MATLAB.

Ctirad Slavík: This is the second part of the Computational Macroeconomics course. The first part will be taught by Michal Kejak. In my part, we will discuss issues related to heterogeneity and inequality. We will start by characterizing the solution to a heterogeneous agents model with complete markets and conclude that the dynamics implied by the model are not consistent with real-world data. We will then analyze models in which markets are (exogeneously) incomplete - either because not all assets are traded (there is only one risk-free asset) or there are borrowing constraints. First, we will characterize the solution to individual agents' problems when the interest rate is fixed (partial equilibrium) with, first, deterministic and, second, stochastic, income fluctuations. Next, we will study general equilibrium versions of these models without and with aggregate risk.

The course will introduce several basic approaches to bounded rationality in macroeconomics, and discuss its implications for consumer behavior, optimal policies, and macroeconomic dynamics. We will cover adaptive learning, restricted perceptions equilibria, model switching, sparse rationality, imperfect information, cognitive discounting, and other ways of modeling bounded rationality; survey experimental evidence on learning and bounded rationality, and use a DYNARE toolbox for estimation of DSGE models under adaptive learning. We will cover recent advances in DSGE models’ estimation, such as Hamiltonian Monte Carlo, Active Subspace Monte Carlo, and Machine Learning approaches. We will also survey a recent literature on formation of expectations, especially of inflation expectations, and on consistency of survey expectations with Full Information Rational Expectations (FIRE) assumption. The grade for this Part is based on homeworks (20%), exam (40%), and a project (30%). An additional 10% will be allocated based on in-class presentations of assigned papers.

This course, intended for second-year Ph.D. students interested in Micro Theory and Game Theory, introduces a selection of topics and research frontiers in these fields. Topics covered include modeling incomplete information (Aumann model and Universal belief space), the Bayesian framework and information structure (Blackwell experiments), observational learning, experimentation (exploitation vs. exploration), repeated games and reputation, among other emerging topics. The course aims to prepare students for conducting their own research.

The course will bring students to the research frontier in applied economics with a special emphasis on economic history and long-run development. The course consists of weekly lectures and seminars in which we discuss topics such as pre-industrial development, industrialization, the formation of norms for long-run economic outcomes, war economics, the economics of crises, the economics of totalitarian regimes, regional development after World War II and more recent figures of economic growth, transition, and monetary integration. The lectures will provide stylized facts and underlying theoretical concepts, while we will critically discuss recent empirical research papers on the respective topics during the seminars. The course further consists of Stata assignments in which students will challenge published papers with newly established methodological. In the end, students have to prepare and present their own research proposal in the field of quantitative economic history.

The course focuses on modern monetary economics, both from a theoretical and practical policy-making perspective. It covers the role of money in the economy, endogenous money creation in the modern monetary system, monetary policy instruments in normal times as well as the unconventional monetary policy tools. The transmission mechanism of monetary policy is analysed both in partial and general equilibrium. The optimal institutional design for modern central banks is discussed within the dynamic inconsistency model for monetary policy, including the discussion of its political-economy background, consequences and potential solutions. The inflation targeting framework is presented both for closed and small-open economies, and contrasted to alternative policy frameworks, including pegged exchange rate arrangements and price-level targeting. Finally, the nexus between monetary policy and other policy areas is explored, including the interaction with fiscal and macro-prudential policies.

This graduate-level course introduces machine learning techniques and applications tailored for the social sciences. It aims to equip students with essential tools to apply machine learning in different areas, including causal inference and time-series analysis. The course combines practical Python applications with foundational statistical methods. Topics include generalized linear models, decision trees, and neural networks, providing a solid foundation in core machine learning approaches. By the end of the course, students will have a comprehensive understanding of key machine learning paradigms.

This course is the second step in student’s ongoing practice of their professional communications skills in the broad field of economics. It includes written tasks, a negotiation, and presentations, and continues the collaborative features of Research Writing 1. Lectures, discussions, teamwork, and individual consultations with the instructor are aimed to continue to build student’s skills and confidence, and to provide useful take-aways for real-world endeavors. The skills practiced on this course are designed to support student writing and speaking throughout their studies and beyond into real-world contexts. The RW2 course includes a focus on MAER students’ early development of their required Master’s thesis. Development of the thesis will be supported via in-class work and individual consultation with the instructor.