## Courses

### YEAR 1

Research master in economics

Research master in economics and statistics

**ECON-S427 Graduate Macroeconomics I (10 ECTS)-1st semester - Philippe Weil**

The topics covered include;

- consumption,
- investment,
- real business cycle models,
- growth,
- life-cycle models,
- monetary economics,
- theory of economic policy,
- open economy macroeconomics.
- Familiarity with basic optimization techniques

**ECON-S428 Graduate Econometrics I (10 ECTS)-1st semester - David Preinerstorfer**

The course covers:

- Finite sample theory of linear regression models.
- Basic elements of asymptotic theory (notions of convergence and basic properties; laws of large numbers; central limit theorems).
- Large sample properties of estimators and tests in linear regression models.
- Asymptotics of M-estimators and in particular generalized method of moment estimators (asymptotic theory, examples, and related hypothesis tests).
- Basic elements of time series analysis (basic terminology, stationarity, linear time series models).

**ECON-S510 Graduate Microeconomics I (10 ECTS)-1st semester - Georg Kirchsteiger**

In this course students learn the fundamental building blocks of microeconomic theory and game theory. Topics are:

- the theories of consumption and production;
- decision under risk and uncertainty;
- partial equilibrium;
- general equilibrium (existence, uniqueness and stability)
- the two welfare theorems;
- core and cooperative game theory;
- normal form games with complete and incomplete information;
- extensive form games.

**MATH-S400 Mathematics and Economic Modelling (5 ECTS)-1st semester - Thomas Demuynck**

The course covers the following topics:

- Basic introduction into logic and proofs.
- What are the different proof techniques and when to apply them.
- Introduction into real analysis;
- supremum and infimum,
- sequences,
- extreme value theorem and intermediate value theorem,
- Berge's maximum theorem,
- Fixed point theorems: contraction mappings, Brouwer's fixed point, Kakutani's fixed point.

**ECON-S429 Graduate Econometrics II (5 ECTS)-2nd semester - Paula Gobbi**

**ECON-S430 Graduate Macroeconomics II (5 ECTS)-2nd semester - Robert Kollmann**

This course gives an introduction to Dynamic Stochastic General Equilibrium (DSGE) models of business cycles and asset prices.

**ECON-S431 Graduate Microeconomics II (5 ECTS)-2nd semester - Patric Legros**

We will analyze environments in which some of the main assumptions underlying the two welfare theorems of general equilibrium are not satisfied: mainly information asymmetries and externalities. The purpose is to introduce and apply concepts or tools from information economics, decision under uncertainty, contract theory and mechanism.

**ECON-S504 Research Methods (5 ECTS)-2nd semester - Gani Aldashev**

- Part I: Research Design (10h):
- Introduction to the course & theoretical modelling,
- Methodology of experimental economics,
- Model specification,
- Integrating theory and empirics,
- How to write an effective theory paper

- Part II: Applications & data (16 h):
- From raw data to the construction of a dataset with multiple academic purposes:
- an application using DHS data,
- Using and presenting spatial information: an applied economist's perspective,
- Data in international trade research,
- Data used in political economics,
- Firm-level data,
- Historical data, Data:
- Heteroskedasticity and autocorrelation problems

- Part III: Presentation skills and research proposals (10 h):
- Presentation skills, How to write a research proposal

**MATH-S401 Dynamic Optimization (5 ECTS)-2nd semester - Thomas Demuynck**

The course focusses on, among others, the following topics:

- Dynamic programming under certainty.
- numerical methods.
- Stochastic dynamic programming.
- Simulation methods.

**STAT-F404 Graduate Statistics (5 ECTS)-1st semester - Thomas Verdebout**

The course covers the following topics:

- Conditional expectation/probability,
- Halmos-Savage theorem,
- the factorization criterion,
- minimal sufficiency.
- Rao-Blackwell theorem,
- distribution-freeness and ancillarity.
- Completeness and the Lehmann Scheffé theorem,
- U-statistics.
- Exponential families,
- group equivariance.
- Hypothesis testing: Uniformly most powerfull test, Neyman-Pearson Lemma, Unbiasedness, similarity, Neyman alpha-structure and invariant tests.

**STAT-F405 Time Series Analysis 1 (5 ECTS)-1st semester**

**STAT-F407 Stochastic Models (5 ECTS)-1st semester - Thomas Verdebout**

The first part of the course is a review course on probability theory that will help the student to follow the second part of the course and other courses in stochastic calculus, probability and statistics.

In the second part of the course we study different types of processes: Discrete time processes: Martingales and Markov chains. Continuous time processes: Markov processes, Poisson processes and Brownian motions.

### Year 2, Research master in economics.

Research master in economics

Research master in economics and statistics

**ECON-S522 Research Seminar (5 ECTS) - 2nd semester - Georg Kirchsteiger**

Attendence of the research seminar in economics/econometrics/statistics

**MEMO-S522 Master thesis (25 ECTS) - promotor by choice**

**ECON-S504 Research methods (5 ECTS) - 2nd semester - Gani Aldashev**

- Part I: Research Design (10h):
- Introduction to the course & theoretical modelling,
- Methodology of experimental economics,
- Model specification,
- Integrating theory and empirics,
- How to write an effective theory paper

- Part II: Applications & data (16 h):
- From raw data to the construction of a dataset with multiple academic purposes:
- an application using DHS data,
- Using and presenting spatial information: an applied economist's perspective,
- Data in international trade research,
- Data used in political economics,
- Firm-level data,
- Historical data, Data:
- Heteroskedasticity and autocorrelation problems

- Part III: Presentation skills and research proposals (10 h):
- Presentation skills, How to write a research proposal

Research master in economics

Advanced Methods track for which they need to take

**15 credits from the courses**
Topics in Economics track for which they need to select

**15 credits from the courses**Research master in economics and statistics

2-4 courses from the economics optional course list

**(Total of 25 ECTS)**
2-4 courses from the statistics optional course list

**(Total of 25 ECTS)****ECON-S460 Advanced Topics in Microeconmics (5 ECTS) - 2nd semester - Micael Castanheira**

**ECON-S519 Graduate Microeconomics III (5 ECTS) - 1st semester - Georg Kirchsteiger & Patrick Legros**

Advanced topics in microeconomics. In odd years the couse is given by P. Legros, in even years by G. Kirchsteiger

**ECON-S461 Advanced Topics in Macroeconomics (5 ECTS) - 2nd semester - Heiko Hesse**

**ECON-S520 Graduate Macroeconomics III (5 ECTS) - 1st semester - Philippe Weil**

This course covers the following topics:

- Consumption smoothing over dates and states of nature.
- Failures of representative agent models in the intertemporal and in the risk dimension.
- Hansen-Jagganathan mean-variance frontiers. Variation on preferences.
- Modern methods in the economics of uncertainty.
- Precautionary saving.
- Incomplete markets.

**ECON-S513 Behavioural Economics (5 ECTS) - 2nd semester - Georg Kirchsteiger**

Standard microeconomic theory is based on two main assumptions: Rationality and selfishness. When actual behavior of economic agents - as observed in economic experiments or in the field - does not conform with economic theory, this behavior might either contradict the rationality assumption or the selfishness assumption (or both).

The first part of the course is devoted to the analysis of non-selfish preferences. Based on experimental evidence, we present behavioral models of altruism, envy, fairness, and reciprocity, and show their impact on different economic problems.

The second part of the course deals with boundedly rational behavior, i.e. learning, and its impact on markets.

**ECON-S521 Graudate Econometrics III (5 ECTS) - 1st semester - David Preinerstorfer**

Special interests of participating students can be taken into consideration (if they broadly fit into the framework below); suggestions are welcome and will be discussed in the first lecture. The general framework of the lecture is as follows:

- Revision of hypothesis testing, confidence interval construction, and related optimality concepts.
- (Non-) Testability of hypotheses (Bahadur-Savage-type results)
- Identification in econometrics.
- Impossibility results when parameters can be nearly non-identified (applications to testing under weak instruments, unit root testing, Spectral density estimation, and testing for long-range-dependence).
- Uniform vs. non-uniform asymptotic approximations with a special emphasis on autocorrelation robust testing, model selection, and the zero power trap in testing for spatial or temporal autocorrelation.
- Impossibility results in high-dimensional testing problems.

**STAT-F404 Graduate Statistics (5 ECTS) - 1st semester - Thomas Verdebout**

This course covers the following topics:

- Conditional expectation/probability,
- sufficiency,
- Halmos-Savage theorem,
- the factorization criterion,
- minimal sufficiency.
- Rao-Blackwell theorem,
- distribution-freeness and ancillarity.
- Completeness and the Lehmann Scheffé theorem,
- U-statistics.
- Exponential families,
- group equivariance.
- Hypothesis testing:
- Uniformly most powerfull test,
- Neyman-Pearson Lemma,
- Unbiasedness, similarity,
- Neyman alpha-structure and invariant tests.

**STAT-F423 Statistical Learning (5 ECTS) - 2nd semester**

The course covers the following topics:

- The 'Data Deluge' and 'Big data' world;
- goals of statistical/machine learning theory;
- mathematical framework;
- classification and Support Vector Machines;
- linear regression problems and high-dimensional statistics (ridge, lasso, etc.);
- kernel methods;
- consistency and complexity issues;
- risk bounds; applications in various fields (economics, finance, computer vision, bioinformatics, etc.)

**STAT-F405 Time Series Analysis 1 (5 ECTS) - 1st semester**

**STAT-F507 Time Series Analysis 2 (5 ECTS) - 2nd semester**

**STAT-F408 Computational Statististics (5 ECTS) - 2nd semester - Maarten Jansen**

The course covers the following topics:

- multiple regression,
- model selection,
- elements of sparsity.
- bootstrap.
- monte carlo,
- MCMC.
- Elements of Bayesian statistical methods

**ECON-S432 Advanced International Trade (5 ECTS) - 2nd semester - Paola Conconi**

This course is divided into two parts, each with one main goal.

The objective of the first component is to understand the effects of various commercial policies.

The goal of the second part of the course is to explore some topics at the frontier of research in international trade and make each student an “expert” in one of the topics.

**ECON-S453 Impact Analysis (5 ECTS) - 1st semester - Philip Verwimp**

This course is divided into two parts, each with one main goal. The objective of the first component is to understand the effects of various commercial policies. The goal of the second part of the course is to explore some topics at the frontier of research in international trade and make each student an “expert” in one of the topics.

**ECON-S451 Advanced Industrial Organization (5 ECTS) - 2nd semester - Patrick Legros**

**ECON-S529 Development Economics (5 ECTS) - 2nd semester - Philip Verwimp**

This is an advanced course geared towards MA students in Economics. In the course I assign a total of 23 papers from the literature.

**ECON-S452 Environmental Economics (5 ECTS) - 1st semester - Estelle Cantillon**

Environmental economics is the field of economics that studies the interactions between economic activities and the environment (i.e. both the impact of economic activities on the environment, and the impact of the environment on economic activities) and the ways to regulate or organize economic activities to achieve an appropriate balance between environmental, economic and other social goals.

This course provides an introduction to the key concepts, tools and methods of environmental economics, as well as to several environmental policy applications. You will have to learn the foundations that cut across environmental issues but you will also be exposed to some in-depth assessments of specific sectors where governments have to deal with complex decisions to address the market failures at the origin of environmental concerns.

While the course emphasizes public interventions (as is traditional in environmental economics), it also discusses the potential contributions of the private sector and individuals.

**ECON-S417 Quantitative Financial Risk (5 ECTS) - 1st semester**

The course is mainly focused on volatility (univariate and multivariate) modeling and their use in financial practice, such as risk measurement, portfolio choice and Value at Risk.

**ACTU-F402 Lévy Processes in Finance and Insurance (5 ECTS) - 1st semester**

**INFO-F422 Statistical Foundations of Machine Learning (5 ECTS) - 2nd semester - Gianluca Bontempi**

The structure of the course is as follows:

- Foundations of statistical modelling,
- parametric estimation,
- nonparametric estimation and resampling,
- supervised learning ( model selection, variable selection),
- algorithms for regression (neural networks, local learning,
- classification algorithms (KNN, Naive- Bayes, SVM), (vii) applications of machine learning (data mining, text mining, web mining)

**STAT-F418 Topics in Nonparametric Smoothing (5 ECTS) - 1st semester - Maarten Jansen**

Study of at least one of the following topics:

- spline smoothing
- kernel or multiscale local polynomial estimation
- wavelet or multiscale smoothing.

**STAT-F420 Topics in Mathematical Statistics I (5 ECTS) - 1st semester - Thomas Verdebout**

**STAT-F421 Topics in Mathematical Statistics II (5 ECTS) - 2nd semester - Davy Paindaveine**

The content changes regularly, according to the students' profiles and interests. Topics covered in the past include: Statistical depth, Le Cam-type asymptotic inference, Rank-based inference