Courses

Instructor:
Friday,
09:00am to 12:30pm
at Eleanor Dulles Room (5.2.010), DIW Berlin, Mohrenstr. 58, 10117 Berlin
Monday,
09:00am to 11:00am
at Eleanor Dulles Room (5.2.010), DIW Berlin, Mohrenstr. 58, 10117 Berlin
Description:

The course deals with advanced estimation techniques in modern econometrics and standard single equation and systems of equations models and also covers time series analysis including multiple time series analysis.

Literature: Hayashi, F. (2000) Econometrics, Princeton University Press, Princeton;
Green, W.H. (2003) Econometric Analysis, 7th Edition, Prentice Hall, New Jersey;
Breitung, J., Brüggemann, R. and Lütkepohl, H. (2004). Structural vector autoregressive modeling and impulse responses, in H. Lütkepohl and M. Krätzig (eds), Applied Time Series Econometrics, Cambridge University Press, Cambridge, pp. 159-196;
Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis, Springer.

Grading: assignments and 2 written exams

Credits:
9.00
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Instructor:
Wednesday,
08:30am to 12:00pm
at Schumpeter Hall, DIW Berlin, Mohrenstr. 58, 10117 Berlin
Description:

The objective of this course is to teach M.A. and Ph.D. students to use macroeconomic concepts and techniques for their own research and incorporates a higher degree of formal analysis than in the introductory master’s lecture (IAMA).

Part I (Prof. Burda): Methods of modern macroeconomics for researchers in the field. Stationary Markov environments, state-space methods, stochastic difference equations. Dynamic programming and Lagrangian methods, complete markets, dynamic stochastic general equilibrium models, solution techniques. The Ramsey problem. Empirical interpretation of macroeconomic shocks; structural versus reduced form.

Part II (Prof. Weinke): Dynamic stochastic general equilibrium (DSGE) models for positive and normative macroeconomic analysis. To this end a number of theoretical and empirical concepts are presented: The computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. On the normative side the concept of Ramsey optimal policy is presented.

Literature: Reference list (Prof. Burda): Ljungqvist and Sargent, Recursive Macroeconomics, 2nd edition (Cambridge, USA: 2004); selected journal articles available on moodle.

Reference list (Prof. Weinke): Selected articles, e.g., Galí, Jordi and Pau Rabanal (2004), Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Postwar U.S. Data?, in: NBER Macroeconomics Annual.

Any further documents needed for the lecture will be available on moodle.

Exam: written exam

Change of location on 10/12/16 and 11/30/16: Dulles Room!

Credits:
9.00
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Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Please see schedule attached.

Management Science I, Part 1: Instructor: Francis de Vericourt, ESMT
Topic: Sequential Decision Making Under Uncertainty - With Applications to Operations and Management Sciences

This course is concerned with situations in which decisions are made sequentially. The fundamental tradeoff at stake consists in balancing immediate reward with unpredictable future rewards. These situations can be found in a wide variety of areas ranging from marketing (e.g. dynamic pricing) to the environment (e.g. water management). In this course, we will primarily focus on applications in the field of management science.
The approach is based on Markov decision processes and more generally (stochastic) Dynamic Programming, which provides a set of general methods for making sequential decisions under uncertainty.

Management Science I, Part 2: Instructors: Matthew Bothner, Gianluca Carnabuci, and Linus Dahlander, ESMT
Topic: The Analysis of Economic and Social Networks

The theories and methods of social network analysis have increasingly been harnessed to better understand a diverse array of topics, such as the spread of obesity, the diffusion of innovations, mobility and risk-taking behavior in tournaments, and brokerage and status positions in markets. This course offers an introduction to the theoretical perspectives and quantitative methods of the network-analytic tradition. A number of key concepts will be introduced, together with opportunities to apply corresponding methods and approaches to measurement using data made available in class. The literature on networks is approached with two goals in mind: (1) to understand the foundations of social network theory and (2) to apply methods.

Credits:
9.00
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Instructor:
Monday,
12:00pm to 04:00pm
at HU Berlin, Spandauer Str. 1, Room 203
Description:

This course is devoted to the core elements of microeconomics. We study both the economics of households and the economics of firms and introduce general equilibrium with particular attention to the two welfare theorems. We also examine decisions under uncertainty, introducing expected and non-expected utility theories. The analysis of choice under uncertainty leads to the examination of financial markets and to strategic interaction problems, which we introduce through the key notions in noncooperative game theory, in particular Nash equilibrium and its most important refinements.

Literature: Mas-Colell, A., Whinston, M.D. and J.R. Green (1995), Microeconomic Theory, Oxford University Press
Exam (written? If yes: One or two exam dates?): yes, four midterms and one final exam date (tba)

Credits:
9.00
Click here to get more information or to sign up
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