Courses

Please check with the BSE Handbook which mandatory courses you have to choose in your PhD track. Not all courses listed here can be approved as Core Courses for all BSE PhD tracks.

Instructor:
Wednesday,
08:30am to 12:00pm
at SPA1, R23
Description:

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, empirical consequences of macroeconomic shocks; structural estimation, the Ramsey problem, dynamic stochastic general equilibrium (DSGE) models. To this end a number of theoretical and empirical concepts are presented. Examples include 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:
Ljungqvist and Sargent, Recursive Macroeconomics, 2nd edition (Cambridge, USA: 2004)
Selected journal 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.

Credits:
9.00
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Monday,
09:00am to 04:30pm
at Lectures : Monday to Wednesday: DIW Schumpetersaal Thursday: Spandauer Straße 1, R125 Friday: Spandauer Straße 1, R
Description:

Course material will be provided via Moodle. No Moodle-Account is needed; the password will be announced in the first lecture.


Schedule:
Four lectures and/or exercises a day; duration: 90 minutes each,

  • (i) 09:00-10:30,
  • (ii) 10:30-12:00,
  • midday break,
  • (iii) 13:30-15:00,
  • (iv) 15:00-16:30

Lectures:


  • Monday: (i), (ii), (iii)
  • Tuesday: (i), (ii), (iii)
  • Wednesday: (i), (ii)
  • Thursday: (i), (ii)
  • Friday: (i), (ii)

Exercises:

  • Monday: (iv)
  • Tuesday: (iv)
  • Wednesday: (iii), (iv)
  • Thursday: (iii), (iv)
  • Friday: (iii)



Venues:
Lectures :

  • Monday to Wednesday: DIW Schumpetersaal
  • Thursday: Spandauer Straße 1, R125
  • Friday: Spandauer Straße 1, R203

Exercises:

  • Monday to Wednesday: DIW Seminar Rooms
  • Thursday: SPA1 R203 / R021a / R021b
  • Friday: SPA1 R021a / R021b / R023
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Instructor:
Thursday,
09:00am to 01:00pm
at ESMT (various rooms)
Description:

Prerequisite:

To attend this class students must have completed the core micro courses (Microeconomics 1 and 2).

 

This course presents psychological and experimental research in economics indicating departures from perfect rationality, self interest, and other classical assumptions of economics. To do so, a variety of empirical results are discussed. The course, however, focuses on different ways of how these departures from the standard assumptions can be formally modelled. It also discusses the implications of these formal behavioral model for positive and normative predictions in different institutional settings. The course has three aims: (i) familarizing students with the lively debate in experimental and behavioral economics; (ii) providing them with the methodological competence necessary to understand and judge original emprical research; (iii) provide formal tools for using so-called behavioral approaches in other areas of economics.

 

Literature:

There is no standard textbook in behavioral economics and the course is not based on a given textbook. Instead, students are expected to read original papers. Nevertheless, a good starting point is: Kahneman, Daniel and Amos Tversky. Choices, Values and Frames, New York: Russell Sage Foundation; Cambridge, U.K.; New York: Cambridge University Press, 2000.

Credits:
9.00
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Thursday,
02:30pm to 06:30pm
at Eleanor Dulles Room (5.2.010), DIW Berlin, Mohrenstr. 58, 10117 Berlin
Friday,
09:30am to 12:30pm
at Eleanor Dulles Room (5.2.010), DIW Berlin, Mohrenstr. 58, 10117 Berlin
Description:

March 29, 2012 14h30-18h30
March 30, 2012 09h30-12h30
If you would like to attend the DIW masterclass, please write an email to Ms Yun Cao (ycao@diw.de).

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Instructor:
Monday,
10:00am to 11:45am
at SPA1, R202
Thursday,
12:00pm to 02:00pm
at SPA 1, R202
Thursday,
02:00pm to 04:00pm
at SPA 1, R202
Description:

Since this course aims primarily at Masters Students, only BDPEMS students with no basic knowledge in econometrics may be admitted for this course conditional on a personal authorization by Prof. Nikolaus Hautsch, following the Beginners' Track in Econometrics. All other students have to attend Econometrics I (Time Series Analysis).

Literature: Davidson, R. and MacKinnon, J.G. (2004): Econometric Theory and Methods, Oxford University Press. Hayashi, F. (2000): Econometrics, Princeton University Press.

Credits:
9.00
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Instructor:
Tuesday,
10:00am to 11:45am
at SPA1, R203/25
Thursday,
08:30am to 10:00am
at SPA 1, R203
Description:

1. Descriptive Methods

Sample Moments

Classical Components Models

Trend Determination Seasonal Adjustment

 

2. Models of Time Series

Stochastic Processes and Stationarity

AR, MA and ARMA Processes

The Partial Autocorrelation Function

 

3. Estimation, Specification, Validation and Forecasting of ARMA Models

 

4. Models for Nonstationary Time Series and Unit Root Tests

Trend Stationarity vs. Unit Root

ARIMA and Seasonal ARIMA Models

Unit Root Tests

 

5. GARCH Models for Clustered Volatility

 

6. Multivariate Extensions VAR Processes

Causality and Impulse Response Analysis

Cointegrated Processes

 

References

Schlittgen/Streitberg (2001): Zeitreihenanalyse, München. * Hamilton (1994): Time Series Analysis, Princeton University Press.

Lütkepohl, H. (2005): New Introduction to Multiple Time Series Analysis, Springer Verlag, Heidelberg.

Credits:
9.00
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Monday,
02:00pm to 06:00pm
at SPA1, R22
Description:

This course provides an overview on the economic analysis of labor markets. The emphasis is on applied microeconomics and empirical analysis. Topics to be covered include: labor supply and demand, human capital, education and training, changes in the wages structure and inequality, biased technological change and returns to skills, organizational change and skill demand, the closing gender gap. The introduction of topics will be on textbook level, but the focus will be on the discussion of empirical implementation strategies used in recent publications. Acquaintance of intermediate microeconomics or labor economics (ideally Prof. Burda’s course in labor economics) and econometrics is highly recommended.

 

Literature:

R. Ehrenberg and R. Smith, 2003, Modern Labor Economics P. Cahuc and A. Zylberberg, 2004, Labor Economics selected journal articles

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Instructor:
Friday,
02:00pm to 06:00pm
at HU Berlin, Spandauer Straße 1, Room 21b
Description:

The course focuses on theoretical concepts, which are fundamental for corporate finance. Topics include: moral hazard, adverse selection, signaling, incomplete contracts and control rights, coordination failure – all with applications to theory of the firm, organizational design, and financial structure.


Literature:
Bolton and Dewatripont. Contract Theory. MIT Press, 2005,
Tirole. Theory of Corporate Finance. Princeton University Press, 2006, and selected articles

Credits:
6.00
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Instructor:
Wednesday,
09:00am to 01:00pm
at ESMT (various rooms)
Credits:
9.00
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Description:

The students should get acquainted with the basic theoretical models that are used to address the major issues of market design and regulation in the electricity and natural gas industry. In addition they should learn how far empirical evidence supports or questions these models.

Credits:
4.00
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Instructor:
Tuesday,
03:15pm to 05:45pm
at Garystrasse 21, R108a
Description:

The aim of microeconometrics is to analyze individual behavior on the basis of micro data (crosssection and panel data) of individuals, households, and firms. The standard linear regression model is generally not applicable to micro data due to the non-metric measurement and censoring of dependent variables at the individual level, selectivity and incomplete observability of endogenous variables, and the dependence of individual observations over time. The empirical methods most frequently applied in empirical microeconomics are surveyed and several applications in empirical microeconomics are presented. Students learn how to apply these methods using real-world microdata and the software package STATA.



Literature:
A. C. Cameron and P. K. Trivedi, Microeconometrics. Methods and Applications, Cambridge University Press, 2005
W. H. Greene, Econometric Analysis (7 ed.), Pearson, 2012, Chapters 11 and 17-19.
J. M. Wooldridge, Econometric Analysis of Cross Section and Panel Data, MIT Press, 2 ed. 2010

Credits:
6.00
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Instructor:
Monday,
01:00pm to 05:00pm
at DIW, Schumpeter Saal
Description:

This course is devoted to decision making under uncertainty and the economics of asymmetric information. The first topic introduces the Von-Neumann-Morgenstern decision model which is used in many areas of modern economics where risk plays a role (macroeconomics, finance, etc.). The course studies the foundations of this model and alternative approaches. The second part focuses on economic settings with asymmetric information. With the help of game theoretic tools, we study the working of markets with asymmetric information, bilateral trading problems with moral hazard and adverse selection, and the theory of mechanism design. The intention of the course is to familiarize students with the standard tools of modern economic theory and to train them in applying these tools to actual economic problems.

 

Literature:

Mas-Colell, Whinston, Green: Microeconomic Theory (1995), Chapter I,II and IV.

Credits:
9.00
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Instructor:
Wednesday,
08:00am to 12:00pm
at 1st part: SPA1, R025; 2nd part: SPA1, R21b
Description:

Log-Lineraization, Policy Function Iteration, Value Function Iteration, Model Evaluation, 2nd Order Approximation

 

Literature:

Ljungqvist, L. and T. Sargent, Recursive Macroeconomic Theory, MIT Press.

Marimon, R. and A. Scott, editors, Computational Methods for the Study of Dynamic Economies, Oxford University Press 1999.

Credits:
6.00
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Instructor:
Friday,
02:00pm to 04:00pm
at SPA1, R22
Description:

The objective of the course is twofold. First, it familiarizes students with the most standard results and standard analyses of regulation in product markets. The course addresses, in particular, regulatory issues due to market power and concentrates on monopoly, merger regulation and anti-trust. Second, the course discusses regulatory issues that are directly related to the research themes of the doctoral program, in particular environmental regulation and regulation in vertical relationships.

Literature:
see: http://lehre.wiwi.hu-berlin.de/Professuren/vwl/mt/RTG/syllabus-regulatio...

Credits:
6.00
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Instructor:
Description:


Prerequisite:

Students should have taken a PhD-level class in behavioral or experimental economics.

 

Please note, that you have to participate two semesters in this research class in order to achieve 6 ECTS Students who want to take the two-semester sequence for credit should also attend the preliminary (organizational) meeting: October 20, 15:00 at WZB.

The course offer students the possibility to learn about ongoing research in behavioral and experimental economics through seminar presentations from external scholars. Students who want to take this course for credit need to write three referee reports per semester selected from the list of papers that are presented and hand these in three days before the seminar (i.e. deadline is 1pm on the last Monday prior to the seminar). In addition, they need to attend both semi-annual internal all-day workshops and present own original research in at least one of these workshops.

 

Credits:
6.00
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Instructor:
Monday,
12:00pm to 02:00pm
at SPA 1, R21a
Description:

The course covers a part of mathematical statistics which deals with the limiting behavior of different sample statistics, U-statistics, M-, L- and R-Estimates. This course gives better understanding for the basic tools learned in the elementary Statistics I and II, like Law of Large Numbers, Central Limit Theorem, Kolmogorov-Smirnov and Cramer-von-Mises tests, sample mean and sample variance behavior, etc. This course is laying a bridge between probability theory and mathematical statistics by manipulating “probability” theorems to obtain “statistical” theorems.

 

Literature:

R. J. Serfling, Approximation theorems of mathematical statistics, 1980, Wiley series in mathematics.

Credits:
3.00
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