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:
Thursday,
04:00pm to 07:30pm
at SPA 1, room 203, Individual dates are held in room 25 (PC-Pool)
Description:

This course provides a rigorous review of basic linear regression and techniques both for cross-sectional and panel applications. The course then covers further topics which are important in applied econometric analysis based on individual level data and longitudinal data. These topics include a discussion of the asymptotic theory for nonlinear estimation techniques (MLE, Nonlinear Least Squares), discrete choice models, limited dependent variables models, and linear quantile regressions. The course provides an up-to-date treat¬ment at the level of Wooldridge's textbook on “Econometric Analysis of Cross Section and Panel Data”. The course will regularly discuss the causal interpretation of econometric estimates. The focus of the course is both on understanding the methodological concepts and on how to apply them. Students will learn to implement the estimation methods using the econometric package Stata.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
08:30am to 10:00am
at HU Berlin, Spandauer Straße 1, Room 202
Tuesday,
02:15pm to 03:45pm
at HU Berlin, Spandauer Straße 1, Room 22
Description:

Single-equation regression (OLS and 2SLS), Wald estimator and LATE, system estimation, panel regression, robust standard errors, LM-Tests, maximum likelihood, binary response models, limited dependent variables models, selection models, selected semiparametric methods such as nonparametric regression, partially linear models, or quantile regression.

Literature:
Wooldridge, J.M. (2010): "Econometric Analysis of Cross Section and Panel Data", 2nd. ed., MIT Press.
Further literature will be announced in the course.

Time and venue:
Tuesdays, 8:30-10, Spandauer Straße 1, room 202
Tuesdays, 14-16, Spandauer Straße 1, room 22 (Individual dates are held in room 25 (PC-Pool).)

Exam:
Written exam (90 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
08:30am to 10:00am
at SPA1, Room 202
Tuesday,
02:00pm to 04:00pm
at SPA1, Room 203
Description:

Single-equation regression (OLS and 2SLS), Wald estimator and LATE, system estimation, panel regression, robust standard
errors, LM-Tests, maximum likelihood, binary response models, limited dependent variables models, selection models, selected
semiparametric methods such as nonparametric regression, partially linear models, or quantile regression.

Literature:

Wooldridge, J.M. (2010): "Econometric Analysis of Cross Section and Panel Data", 2nd. ed., MIT Press.
Weitere Literaturempfehlungen erfolgen in der Lehrveranstaltung

Written exam (90 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Friday,
08:30am to 12:00pm
at DIW, Mohrenstraße 58
Wednesday,
08:30am to 12:00pm
at TU Berlin, main building, Straße des 17. Juni 135, lecture hall H 3003A
Description:

Lectures by A. Kriwoluzky:
This class covers the essentials to estimate DSGE models with Bayesian methods. We start by deriving the state-space form of a DSGE model. In a next step, we introduce the Kalman Filter, a very useful tool to extract unobserved components from time series or to evaluate the likelihood of a DSGE model. The exercise classes will apply the simple New Keynesian model to extract monetary policy shocks.
Equipped with the basics, we start exploring the Bayesian way to estimate models. More precisely, we will introduce the Prior and the Posterior distribution of parameters. Students will learn how to evaluate the Posterior distribution numerically using different sampling algorithms. In the exercise class, we discuss how a Bayesian model can be employed to forecast economic variables.
The final part will see the introduction of the Dynare software package that is usually used to solve and estimate DSGE models. After the introduction of the basic setup of a Dynare file, we will put Dynare to work. Finally, we aim to consider complex models such as the Smets and Wouters model (2007, AER).

Lectures by F. Heinemann:
This part of the course covers topics such as determinacy of the price level, bubbles, equilibrium multiplicity, strategic uncertainty, and current limits of DSGE models. More information will be provided here.

Literature:
Will be announced during the lectures.

Time frame (date of first and last class):
- Lectures by A. Kriwoluzky: April 12 till May 15 on the following days: April 12, 17, 24 & May 10, 15
- Lectures by F. Heinemann: every Wednesday from May 22 to July 10 (except July 3)

Time(s):
- Lectures by A. Kriwoluzky: 8:30 – 12:00
- Lectures by F. Heinemann: 8:30 – 12:00 (with a break at 10:00)

Location(s):
- Lectures by A. Kriwoluzky: DIW Berlin, Ferdinand-Friedensburg Room (April 12) & Room 3.3.002c (remaining dates)
- Lectures by F. Heinemann: TU Berlin, Main Building, lecture hall H 3003A

Exam:
Midterm and final exam

For more information please also see the attached syllabi.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at tba
Wednesday, 08:30am at TU Berlin, Main Building, Lecture Hall H 0111
Description:

English description of the course:
- Lectures by M. Trabandt: Advanced macroeconomics, search and matching labor markets, model solution and estimation techniques. More information will be provided in March 2018 at http://www.wiwiss.fu-berlin.de/en/fachbereich/vwl/trabandt/Teaching/Curr...

- Lectures by F. Heinemann: This part of the course covers topics such as determinacy of the price level, bubbles, equilibrium multiplicity, strategic uncertainty, and current limits of DSGE models. More information will be provided at http://www.macroeconomics.tu-berlin.de/menue/teaching_lehre/adv_macroeco...

Literature: will be announced during the lectures.

Exam: midterm and final exam.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at TU Berlin, Hauptgebäude, Raum H 0111
Wednesday,
08:00am to 12:00pm
at DIW
Description:

The first part of the course studies monetary theory: how future expected money supply affects the current price level, why money can be written in the utility function and what is required to determine a unique equilibrium with rational expectations. Turning to the foundations of New Keynesian Macroeconomics, we analyze why monopolistic competition leads to an active role for monetary policy, derive the forward looking Phillips curve and study optimal monetary policy.
The second part of the course is dedicated to the solution of DSGE models in general and in particular models in which labor market frictions play a prominent role. It is designed to develop and sharpen students’ prior knowledge of dynamic macroeconomics and econometrics with a mixture of lectures on state-of-the-art solution and estimation techniques for macroeconomic models and application of the techniques with standard software packages and models from the literature. Students are required at a minimum to have successfully completed the AMA I course and possess a basic understanding of time-series and linear-model econometrics.

StO/PO MA 2005 - 2010: 6 LP, Modul: "Advanced Macroeconomic Analysis II (PhD-level)"
StO/PO MA 2016: 6 LP, Modul: "Advanced Macroeconomic Analysis II (PhD-level)"
StO/PO MEMS 2016: 6 LP, Modul: "Advanced Macroeconomic Analysis II (PhD-level)", Major: Macroeconomics

Written exam (90 min)

http://www.macroeconomics.tu-berlin.de/menue/home/

Credits:
9.00
Click here to get more information or to sign up
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
Click here to get more information or to sign up
Instructor:
Monday,
12:15pm to 03:45pm
at Various locations: ESMT, FU, HU
Thursday,
12:15pm to 01:45pm
at HU Berlin, Spandauer Straße 1, Room 203
Description:

The intention of the course is to familiarize students with the standard tool of modern economic theory and to train them in applying these tools to actual economic problems. It is particularly devoted to market failures and welfare economics. The first part (Part III in MWG) outlines properties of competitive markets and welfare analysis in a partial equilibrium context. It then focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. The second part (Part V in MWG) addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The course addresses these issues both from a positive and normative perspective.

Literature:
Mas-Colell, Whinston, and Green (1995), Microeconomic Theory (MWG), Part III and Part V

Time and venue:
Lectures: Mondays (except for April 11), 12.15 - 3.45 pm
April 8, 11, 29, May 6: ESMT Berlin, Schloßplatz 1, Room 00.17 (29.04.), Bookshop (06.05.)
May 13, 20, 27, June 3: FU Berlin, Garystraße 21, lecture hall 108a
June 17, 24, July 1, 8: HU Berlin, Spandauer Straße 1, room 203

Exercises: Tianchi Li, Thursdays, 12 - 2 pm, HU Berlin, Spandauer Straße 1, room 203

Final exam:
tba

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at Various locations: ESMT, FU, HU (room 22)
Thursday,
12:00pm to 02:00pm
at SPA1, room 23
Description:

The intention of the course is to familiarize students with the standard tool of modern economic theory and to train them in applying these tools to actual economic problems. It is particularly devoted to market failures and welfare economics. The first part (Part III in MWG) outlines properties of competetive markets and welfare analysis in a partial equilibrium context. It then focuses on the three classical contidions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. The second part (Part V in MWG) addresses fundamental issues of welfare economics from the perspective of a policy maker who desingns and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The course addresses these issue both from a positive and normative perspective.
Literature:
Mas-Colell, Whinston, and Green (1995), Microeconomic Theory (MWG), Part III and Part V
Times and Venues:
April 16 - May 7 at ESMT Berlin, Schlossplatz 1, in the corresponding rooms:
April 16, 30 and May 7: Bookshop
April 23: Seminar room 00.17
May 14 - July 11 at FU Berlin, Garystrasse 21, room 108a
June 18 - July 9 at HUB, Room 22, Spandauer Strasse 1

Final exam: tba.

Exercises: Tianchi Li, Thursdays, 12 - 2pm, HU, SPA 1, room 23

Credits: 9

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at SPA1, R203
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. Also matching problems will be discussed.

Literature: Mas-Colell, A., Whinston, M.D. and J.R. Green (1995), Microeconomic Theory, Oxford University Press

Exam: 4 midterms and 1 final exam

Please see the attached timetable for more information on the course dates.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
02:00pm to 04:00pm
at HU Berlin, Spandauer Str. 1, room 220
Thursday,
10:00am to 12:00pm
at HU Berlin, Spandauer Str. 1, room 203
Description:

The course introduces econometric methods for analyzing cross-sectional data, panel data and time series data and discusses their applicability in practice. The following topics are covered: extensions and applications of the linear model; instrumental variable estimation; binary response models; truncated and censored regression, static panel data models; specification, estimation, validation and forecasting of autoregressive models. The application of these methods is explained and illustrated by means of empirical examples.

Literature:
Marno Verbeek: "A Guide to Modern Econometrics", 2012, John Wiley & Sons.
James H. Stock, Mark W. Watson: "Introduction to Econometrics", 2007, Pearson Education.
Christiaan Heij, Paul de Boer et al.: "Econometric Methods with Applications in Business and Economics", 2004, Oxford University Press.

Exam:
Written exam (90 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Friday,
09:00am to 12:30pm
at DIW
Description:

The course deals with advanced estimation techniques in modern econometrics and standard single equation
and systems of equations models. It covers time series as well as microeconometric methods.

Literature: Hayashi, F. (2000) Econometrics, Princeton University Press, Princeton;
Green, W.H. (2003) Econometric Analysis, Fifth Edition (or higher), Prentice Hall, New
Jersey;
Train, Kenneth E. (2009), Discrete Choice Methods with Simulation, Cambridge University Press.

Exam: 2 written exams

*Time(s): 9:00-12:30 + 90 min TA session (time to be determined)

9 ECTS

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
12:00pm to 02:00pm
at HU Berlin, Spandauer Str. 1, room 201
Monday,
10:00am to 12:00pm
at HU Berlin, Spandauer Str. 1, room 201
Description:

Estimation and testing in the general linear model, generalized least squares estimation, asymptotic theory, maximum likelihood estimation and likelihood based testing, nonlinear regression models, stochastic regressors, instrumental variable estimation, (generalized) method of moments.

Please note that this course can only be attended as BSE Core Course, if you have successfully applied for the Econometrics Beginner's Track (PhD Track in Economics). More information can be found in the BSE Handbook.

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

Exam:
Written exam (150 min)

Credits:
9.00
Click here to get more information or to sign up
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
Click here to get more information or to sign up
Instructor:
Tuesday,
10:00am to 12:00pm
at Spandauer Straße 1, Lectures in room 202 (Mon) and room 201 (Tue), Tutorials in room 202
Description:

Lectures: Mon, 10:00-12:00, and Tue, 10:00-12:00
Tutorials: Thu, 14:00-16:00, or Fri, 12:00-14:00

Estimation and testing in the general linear model, generalized least squares estimation, asymptotic theory, nonlinear regression models, stochastic regressors, instrumental variable estimation, method of moments.

Literature:
- Davidson, R. and MacKinnon, J.G. (2004): Econometric Theory and Methods, Oxford University Press.
- Hayashi, F. (2000): Econometrics, Princeton University Press.
Exam: written exam (120 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
12:00pm to 02:00pm
at HU Berlin, Spandauer Str. 1, Room 202
Monday,
10:00am to 12:00pm
at HU Berlin, Spandauer Straße 1, Room 202
Thursday,
02:00pm to 04:00pm
at HU Berlin, Spandauer Straße 1, Room 202
Description:

Lecture:

Mon. 10-12 a.m., Tue. 12-2 p.m.

Tutorial:

Thu. 2-4 p.m., Fri. 12-2 p.m.

 

Estimation and testing in the general linear model, generalized least squares estimation, asymptotic theory, nonlinear regression models, stochastic regressors, instrumental variable estimation, method of moments.

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

Exam: written exam

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

Estimation and testing in the general linear model, generalized least squares estimation, asymptotic theory, nonlinear regression models, stochastic regressors, instrumental variable estimation, method of moments.

 
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
Click here to get more information or to sign up
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
Click here to get more information or to sign up
Friday,
09:30am to 01:00pm
at DIW, Schumpeter Saal
Monday,
09:00am to 11:00am
at Eleanor Dulles Raum 5.2.010, DIW Berlin
Description:

The course is split in two parts. The first part will be taught by Anton Velinov and Niels Aka from the DIW Berlin and the exam is going to take place in December. The grading of the first part is based on the assignments (20%) and an exam (80%) at the end of the term. Each part of the course is given a 50% weight of the total grade.

The second part will be taught by Lars Winkelmann from the Free University Berlin and Annika Schnücker from the DIW Berlin. More information on that is to come.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
12:00am to 02:00pm
at HU, Spandauer Str. 1, room 201
Monday,
10:00am to 12:00pm
at HU, Spandauer Str. 1, room 201
Description:

Time:
Lectures: Mon, 10:00-12:00, and Tue, 12:00-14:00
Tutorials: Thu, 14:00-16:00, or Fri, 12:00-14:00

Location:
Spandauer Straße 1,
Lectures in room 201 and Tutorials in room 202 (Thu) and 22 (Fri)

Description of the course:
Estimation and testing in the general linear model, generalized least squares estimation, asymptotic theory, maximum likelihood and pseudo-maximum likelihood estimation, likelihood-based testing, nonlinear regression models, stochastic regressors, instrumental variable estimation, generalized method of moments.
A deeper insight into advanced methods and additional topics is offered by means of assignments.

Tutorials by Marica Valente and N.N.

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

Exam:
written exam (150 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
12:00pm to 02:00pm
at HU Berlin, Spandauer Str. 1
Description:

Estimation and testing in the general linear model, generalized least squares estimation, asymptotic theory, maximum likelihood and pseudo-maximum likelihood estimation, nonlinear regression models, stochastic regressors, instrumental variable estimation, generalized method of moments. A deeper insight into advanced methods and additional topics is offered by means of assignments.

Instructor: Bernd Droge (Humboldt-Universität zu Berlin); Tutorials: Marina Furdas and Marica Valente

Time frame: first class on October 17, last class on February 16

Weekdays and Time: Lectures: Mon, 10:00-12:00, and Tue, 12:00-14:00; Tutorials: Thu, 14:00-16:00, or Fri, 12:00-14:00

Location: Spandauer Straße 1, Lectures in room 202 (Mon) and 201 (Tue); Tutorials in room 202 (Thu) and 22 (Fri)

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

Credits: 12 ECTS

Exam: written exam (120 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
10:00am to 12:00pm
at HU Berlin, Spandauer Str. 1, Room 202
Tuesday,
12:00pm to 02:00pm
at HU Berlin, Spandauer Str. 1, Room 202
Thursday,
02:00pm to 04:00pm
at HU Berlin, Spandauer Str. 1, Room 202
Description:

This course is for students with lacking econometric background.

Econometrics I for Beginners: Master Course “Econometric Methods”, 9 ECTS
Econometrics II, 9 ECTS
6 ECTS in a further econometrics course in 3rd semester

To study the beginner’s track, get the approval by Dr. Bernd Droge droge@wiwi.hu-berlin.de (short application justifying lacking econometric background).

Lecture:

Mon. 10-12 a.m., Tue. 12-2 p.m.

Tutorial:

Thu. 2-4 p.m., Fri. 12-2 p.m.

Estimation and testing in the general linear model, generalized least squares estimation, asymptotic theory, nonlinear regression models, stochastic regressors, instrumental variable estimation, method of moments.

Literature:

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

Exam: written exam

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Friday,
09:00am to 01:00pm
at FU Berlin, Garystr. 21, Room 104
Monday,
09:00am to 11:00am
at DIW Berlin, Mohrenstr. 58
Description:

Part I of the course (Anton Velinov) covers commonly used estimation techniques, such as Ordinary Least Squares, Maximum Likelihood, Generalized Least Squares. The Generalized Method of Moments framework is introduced and several popular estimators (IV, 2SLS, 3SLS, FE, RE) are derived from it.

Part II (Lars Winkelmann) provides a survey of the theory of time series methods in econometrics. Topics include univariate stationary and non-stationary models, vector autoregressions, cointegration, high-dimensional predictive models and volatility models.

Literature:
tba

Time and venue:
Lectures: Fridays, 9:00-13:00 at FU Berlin, Garystr. 21, Room 104
Tutorials: Mondays, 9:00-11:00 at DIW Berlin, Mohrenstr. 58, room tba

Exam:
tba

Credits:
9.00
Click here to get more information or to sign up
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
Click here to get more information or to sign up
Instructor:
Friday,
09:30am to 01:00pm
at FU, Garystr. 21, Room 104
Monday,
09:00am to 11:00am
at FU, Garystr. 21, Room 104
Credits:
9.00
Click here to get more information or to sign up
Instructor:
Friday,
09:00am to 12:30pm
at DIW
Description:

The course deals with advanced estimation techniques in modern econometrics and standard single equation and systems of equations models.
It covers time series as well as microeconometric methods.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Friday,
09:00am to 01:00pm
at DIW, different rooms (see schedule)
Description:

The course deals with advanced estimation techniques in modern econometrics and standard single equation and systems of equations models. It covers time series as well as microeconometric methods.

Literature: to be determined

Exam: written

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

The course deals with advanced estimation techniques in modern econometrics and standard single equation and systems of equations models. It covers time series as well as microeconometric methods.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
02:00pm to 04:00pm
at HU Berlin, Spandauer Str. 1, room 22
Thursday,
12:00pm to 02:00pm
at HU Berlin, Spandauer Str. 1, room 203, Empirical Tutorials take place at room 025
Description:

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.

In the tutorials the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

Literature:
- Hamilton (1994). Time Series Analysis. Princeton, University Press.
- Schlittgen/Streitberg (2001). Zeitreihenanalyse. Oldenburg Verlag, München.
- Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer
Verlag, Heidelberg.

Exam: written exam (90 min; 3/4 of final grade) and assignments (1/4 of final grade)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
10:00am to 12:00pm
at HU Berlin, Spandauer Str, 1, Room 220
Thursday,
12:00pm to 02:00pm
at HU Berlin, Spandauer Str. 1, Room 203/PC-Pool 025
Description:

Classical components models; stochastic processes; stationarity; ARIMA processes, GARCH models; specification, estimation and
validation of models; forecasting; unit root tests; multivariate extensions: VAR processes, causality and impulse response analysis,
cointegrated processes. In the tutorials the time series methods are applied to empirical data.

Literatur:
Hamilton, D.J. (1994). Time Series Analysis, Princeton University Press.
Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis, Springer Verlag, Heidelberg

Exam:
Written exam (90 min; 3/4 of final grade) and assignments (1/4 of final grade)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
10:00am to 12:00pm
at HU Berlin, Spandauer Str. 1, Room 220
Thursday,
12:30pm to 02:00pm
at HU Berlin, Spandauer Straße 1, Room 203/025
Description:

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.

In the tutorials (which take place at room 025) the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

 

Literature:
  • Hamilton (1994). Time Series Analysis. Princeton, University Press.
  • Schlittgen/Streitberg (2001). Zeitreihenanalyse. Oldenburg Verlag, München.
  • Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer Verlag, Heidelberg.

Exam: 
Written exam (90 min; 3/4 of final grade) and assignments (1/4 of final grade)

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

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.
In the tutorials the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

Literature:
Hamilton (1994). Time Series Analysis. Princeton, University Press.
Schlittgen/Streitberg (2001). Zeitreihenanalyse. Oldenburg Verlag, München.
Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer Verlag, Heidelberg.

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

This course provides a rigorous review of basic linear regression and techniques both for cross-sectional and panel applications. The course then covers further topics which are important in applied econometric analysis based on individual level data and longitudinal data. These topics includes a discussion of the asymptotic theory for nonlinear estimation techniques (MLE, Nonlinear Least Squares), discrete choice models, limited dependent variables models, and linear quantile regressions. The course provides an up-to-date treat-ment at the level of Wooldridge's textbook on “Econometric Analysis of Cross Section and Panel Data”. The course will regularly discuss the causal interpretation of econometric estimates. The focus of the course is both on understanding the methodological concepts and on how to apply them. Students will learn to implement the estimation methods using the econometric package Stata.

Prerequisites
Knowledge of econometrics at the level of the courses “Econometric Methods 1” (First Master course) or “Econometrics I” (BDPEMS).

Tuesday 8:30-10:00, SPA 1, 202
Tuesday 14:00-16:00, SPA 1, 203 and 025 (PC-Pool)

Outline
1. Review of the linear Regression Model for Cross-Sectional Data
References: WO Chapters 1–6, CT Chapters 4, 21, 22, AP Chapters 2–4

1.1 Preliminaries: Conditional Expectations in Econometrics, Causal Analysis, Linear Projections
1.2 OLS: Asymptotic Theory, Robust Standard Errors, Partitioned Regression, Gauss-Markov-Theorem, Testing
1.3 Instrumental Variable Regression

2. System Estimation by OLS and GLS, Linear Panel Data Models
Reference: WO Chapters 7, 10, AP Chapter 5

3. Nonlinear Least Squares and Maximum Likelihood
Reference: WO Chapters 12, 13

4. Binary Response Models and Limited Dependent Variables
Reference: WO Chapters 15, 17

5. Linear Quantile Regression (QR)
References: KO, AP Chapter 7, WO Chapter 12.10, CT Chapter 4.6

5.1 Introduction to linear quantile regression: Distance function, Asymptotic distribution, Properties of the estimator, Interpretation as Method-of-Moments Estimator,
5.2 Decomposition Analysis with Quantile Regression and Unconditional Quantile Regression

Main References:
• AP: Angrist, J. D. and J.-S. Pischke (2009): Mostly Harmless Econometrics – An Empiricist’s Companion, Princeton University Press.
• CT: Cameron, A. C. and P. K. Trivedi (2005): Microeconometrics – Methods and Applications, Cambridge University Press.
• GR: Greene, W. (2008): Econometric Analysis, 6th ed., International Edition, Prentice Hall.
• KO: Koenker, R. (2005) Quantile Regression. Econometric Society Monograph, Cambridge University Press, Cambridge.
• WO: Wooldridge, J. M. (2010): Econometric Analysis of Cross Section and Panel Data. 2nd edition, Cambridge, MA: MIT Press (see also: http://mitpress.mit.edu/books/econometric-analysis-cross-section-and-pan...).

Grade
The grade will be based on a written final exam (90 minutes, two dates).

Further Information

There will be problem sets with theoretical and empirical exercises which will be assigned as voluntary homeworks for Master students and as mandatory homeworks for PhD students. Homeworks are to be submitted by groups of 2-4 students. The homeworks will be corrected for all students and the same number of credits will be given for all group members. However, the homeworks do not count as part of the final grade for master students. PhD students must obtain at least 50% of all possible credits for the graded homeworks in order to be able to write the final exam but the final grade for the PhD students will only be based on the final exam.

Further references, particularly regarding the method of Quantile Regression and the application of the methods, will be given in the course. The basic estimation techniques will be implemented in the PC Pool using the econo¬metric package Stata.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
02:00pm to 04:00pm
at HU Berlin, SPA1, Room 203
Description:

This course deals with advanced estimation techniques in modern econometrics. In the first part we study generalized methods of moments (GMM) estimation as well as pseudo-maximum likelihood techniques and their applications to different types of single-equation models and multiple-equation systems. If time, a brief introduction to Bayesian econometric methods will be given. The second part covers non- and semiparametric methods in econometrics. We will study basic Kernel density estimation, nonparametric regression techniques and estimation of partially linear and additive models. A deep knowledge of the techniques conveyed in this course is extremely useful since they are applied in various areas in modern econometrics, including time series econometrics, microeconometrics, panel econometrics as well as financial econometrics.

Literature:
Davidson, R. and MacKinnon, J.G. (2004): Econometric Theory and Methods. Oxford University Press.
Gouriéroux, C. and Monfort, A. (1995): Statistics and Econometric Models. Cambridge University Press, Vol. 1 and 2.
Härdle, W.K., Müller, M., Sperlich, S. and Werwatz, A. (2004): Nonparametric and Semiparametric Models. Springer-Verlag.
Hayashi, F. (2000): Econometrics. Princeton University Press.
Newey, W. K. (1993): “Efficient Estimation of Models with Conditional Moment Restrictions”, in Handbook of Statistics, ed. by G. S. Maddala, C. R. Rao, and H. D. Vinod, pp. 419–454. Elsevier Science.

Exam: written exam (90 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
02:00pm to 04:00pm
at HU Berlin, SPA1, Room 203
Thursday,
12:00pm to 02:00pm
at HU Berlin, SPA1, Room 22
Description:

This course deals with advanced estimation techniques in modern econometrics. In the first part we study generalized methods of moments (GMM) estimation as well as pseudo-maximum likelihood techniques and their applications to different types of single-equation models and multiple-equation systems. If time, a brief introduction to Bayesian econometric methods will be given. The second part covers non- and semiparametric methods in econometrics. We will study basic Kernel density estimation, nonparametric regression techniques and estimation of partially linear and additive models. A deep knowledge of the techniques conveyed in this course is extremely useful since they are applied in various areas in modern econometrics, including time series econometrics, microeconometrics, panel econometrics as well as financial econometrics.

Literature:
Davidson, R. and MacKinnon, J.G. (2004): Econometric Theory and Methods. Oxford University Press.
Gouriéroux, C. and Monfort, A. (1995): Statistics and Econometric Models. Cambridge University Press, Vol. 1 and 2.
Härdle, W.K., Müller, M., Sperlich, S. and Werwatz, A. (2004): Nonparametric and Semiparametric Models. Springer-Verlag.
Hayashi, F. (2000): Econometrics. Princeton University Press.
Newey, W. K. (1993): “Efficient Estimation of Models with Conditional Moment Restrictions”, in Handbook of Statistics, ed. by G. S. Maddala, C. R. Rao, and H. D. Vinod, pp. 419–454. Elsevier Science.

Exam: written exam (90 min), two exam dates

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Tuesday,
12:00pm to 04:00pm
at HU Berlin, Spandauer Straße 1, Room 220
Description:

Quasi-maximum likelihood and GMM estimation, multiple equation estimation, empirical likelihood methods, Bayesian inference, MCMC techniques, nonparametric methods, applications.

Literature:
C. Gourieroux & A. Monfort (1995): Statistics and Econometric Models, Vol. I, II, University Press, Cambridge.
Hayashi, F. (2000): Econometrics, Princeton University Press.

Exam:
Written exam (90 min)

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

This course deals with advanced estimation techniques in modern econometrics.
Main topics include generalized methods of moments (GMM) estimation for single-equation models and multiple-equation models, information theoretic approaches as well as pseudo-maximum likelihood techniques. Furthermore, an introduction to Bayesian econometric methods will be given. Here the focus is on fundamental principles of Bayesian inference, Markov chain Monte-Carlo (MCMC) methods as well as different applications of Bayesian inference. The third and forth part covers non- and semiparametric methods in econometrics. We will study basic Kernel density estimation, nonparametric regression techniques and estimation of partially linear and additive models. A deep knowledge of the techniques conveyed in this course is extremely useful since they are applied in various areas in modern econometrics, including time series econometrics, micro econometrics, panel econometrics as well as financial econometrics.

Literature:
Amemiya, T. (1985): Advanced Econometrics. Basil Blackwell, Oxford.
Greenberg, E. (2008): Introduction to Bayesian Econometrics, Cambridge University Press.
Gouriéroux, C. and Monfort, A. (1995): Statistics and Econometric Models, Cambridge University Press, Vol. 1 and 2.
Hansen, L. P. (1982): “Large Sample Properties of Generalized Method of Moment Estimators”, Econometrica, 50, 1029–1054.
Hayashi, F. (2000): Econometrics, Princeton University Press.
Koop, G. (2003): Bayesian Econometrics, Wiley.
Li, Q. and Racine, J. (2007): Nonparametric Econometrics, Princeton University Press.
Newey, W. K. (1993): “Efficient Estimation of Models with Conditional Moment Restrictions”, in Handbook of Statistics, ed. by G. S. Maddala, C. R. Rao, and H. D. Vinod, pp. 419–454. Elsevier Science.
Newey, W. K. and McFadden, D. (1994): “Large sample estimation and hypothesis testing”, Handbook of Econometrics, Volume IV.
Pagan, A. and Ullah, A. (1999): Nonparametric Econometrics, Cambridge University Press.

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

Covers positive accounting theory and capital market-based accounting research. Topics in the area of positive accounting research cover issues like accounting choice, disclosure quality, earnings management as well as governance-related accounting questions. Capital market-based accounting research focues on topics like the pricing impact of financial accounting disclosure on capital markets, the connection between accounting and the cost of capital or the interplay of financial accounting and corporatefinance decisions. Literature: None. For a reading list of current papers, refer to the full syllabus.

Credits:
6.00
Click here to get more information or to sign up
Instructor:
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
Click here to get more information or to sign up
Instructor:
Wednesday,
08:00am to 10:00am
at 1st part: TU Berlin, Main Building, Room H 2038
Wednesday,
10:00am to 12:00pm
at 1st part: TU Berlin, Main Building, Room 3008
Wednesday,
08:30am to 12:00pm
at 2nd part: HU Berlin, Spandauer Straße 1, Room 21a
Description:

The following topics will be taught: Asset pricing; advanced preference theory such as Epstein-Zin; dynamic contracts and applications; growth models, OLG models; Money and models of price and wage rigidities; economic policy and time consistency, applied VAR analysis.
This will be complemented by deepening the knowledge regarding mathematical and econometric tools, such as MATLAB and/or EViews.

Organisation:
The first part of the course, i.e. from April 11 to May 23, 2012 will be taught by Frank Heinemann at the TU Berlin. Monique Ebell will hold the second part, i.e. from May 30 to July 11, 2012 at HU Berlin.

Exam:
Written exam (90 min)

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

1. Money and Inflation - The Cagan Model of Money and Prices
2. Money in the Overlapping-Generations Model
3. Modelling Money in the Utility Function (Brock/Sidrauski Model, Cash-in advance model, shopping-time model)
4. Monopolistic Competition and Price Rigidities
5. The New Neoclassical Synthesis and Monetary Policy
6. Commitment and Discretion in Monetary Policy
7. Stabilizing Demand and Supply Shocks
8. Current Developments and Open Issues

Literature:
Blanchard, Olivier J.; Stanley Fischer, Lectures on Macroeconomic, MIT Press, 1989.
Walsh: Monetary Theory and Policy, MIT-Press, 2003.
Woodford: Interest and Prices: Foundations of a Theory of Monetary Policy, Princeton University Press, 2003.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at DIW, Mohrenstr. 58, Schumpeter Hall
Description:

The objective of this course is to enable M.A. and Ph.D. students to use macroeconomic concepts and techniques for their own research. This leads to a higher level of formalization in this lecture than in the introductory lecture (IAMA).

Contents (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. Empirical consequences of macroeconomic shocks; structural estimation, the Ramsey problem.

Contents (Prof. Weinke): This course develops dynamic stochastic general equilibrium (DSGE) models and uses them for positive and normative macroeconomic analysis. 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.
Literatur

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

Reference list (Prof. Weinke): We will use 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, and Schmitt-Grohé, Stephanie and Martín Uribe (2012): „An OLS Approach to Computing Ramsey Equilibria in Medium-Scale Macroeconomic Models“, Economics Letters, 115, April 2012, 128-129.

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

Written exam (90 min)

Credits:
9.00
Click here to get more information or to sign up
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
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at DIW, Mohrenstr. 58, Dulles or Schumpeter
Description:

The objective of this lecture is to enable M.A. and Ph.D. students to
use macroeconomic concepts for their own research. This leads to a higher
level of formalization in this lecture than in the introductory lecture
(IAMA).

Contents (Prof. Watzka): 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.

Contents (Prof. Weinke): This course develops dynamic stochastic general
equilibrium (DSGE) models and uses them for positive and normative
macroeconomic analysis. 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.

Location of the lecture: DIW, Mohrenstr. 58:
Oct 15, 2014 08:30-12:00 Dulles
Oct 22, 2014 08:30-12:00 Schumpeter
Oct 29, 2014 08:30-10:30 Schumpeter, 10:30-12:00 Dulles
Nov 05, 2014 08:30-12:00 Schumpeter
Nov 12, 2014 08:30-12:00 Schumpeter
Nov 19, 2014 08:30-12:00 Schumpeter
Nov 26, 2014 08:30-10:30 Schumpeter, 10:30-12:00 Dulles
Dec 03, 2014 08:30-12:00 Schumpeter
Dec 10, 2014 08:30-10:30 Schumpeter, 10:30-12:00 Dulles
Dec 17, 2014 08:30-10:30 Schumpeter, 10:30-12:00 Dulles
Jan 07, 2015 08:30-12:00 Schumpeter
Jan 14, 2015 08:30-12:00 Schumpeter
Jan 21, 2015 08:30-12:00 Schumpeter
Jan 28, 2015 08:30-12:00 Schumpeter
Feb 04, 2015 08:30-12:00 Schumpeter
Feb 11, 2015 08:30-12:00 Schumpeter
Feb 18, 2015 08:30-12:00 Schumpeter
Feb 25, 2015 08:30-12:00 Schumpeter

Literatur:
Reference list (Prof. Watzka): Ljungqvist and Sargent, Recursive
Macroeconomics, 2nd edition (Cambridge, USA: 2004); selected journal
articles

Reference list (Prof. Weinke): We will use 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, and Schmitt-Grohé, Stephanie and Martín Uribe
(2012): „An OLS Approach to Computing Ramsey Equilibria in Medium-Scale
Macroeconomic Models“, Economics Letters, 115, April 2012, 128-129.

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

Exam: written (90 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at DIW (Schumpeter Hall/Dulles Room), Mohrenstraße 58, 10117 Berlin
Description:

Contents 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. Empirical consequences of macroeconomic shocks; structural estimation, the Ramsey problem.

Contents Prof. Weinke: This course develops dynamic stochastic general equilibrium (DSGE) models and uses them for positive and normative macroeconomic analysis. 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 for Prof. Burda's part:

Ljungqvist and Sargent, Recursive Macroeconomics, 2nd edition (Cambridge, USA: 2004) Chapters 2-4
selected journal articles

Literature for Prof. Weinke's part:

chapters 8 and 15 of Ljungqvist and Sargent, Recursive Macroeconomics, 2nd edition (Cambridge, USA: 2004)
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.

Exam:
Written (90 minutes)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at Schumpeter Hall, DIW Berlin, Mohrenstr.58, 10117 Berlin
Description:

Contents 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. Empirical consequences of macroeconomic shocks; structural estimation, the Ramsey problem.

Contents Prof. Weinke: This course develops dynamic stochastic general equilibrium (DSGE) models and uses them for positive and normative macroeconomic analysis. 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.

Moodle link: http://moodle.hu-berlin.de/course/view.php?id=51296.

Literature for Prof. Burda's part:

  • Ljungqvist and Sargent, Recursive Macroeconomics, 2nd edition (Cambridge, USA: 2004) Chapters 2-4
  • selected journal articles

Literature for Prof. Weinke's part: 

  • chapters 8 and 15 of Ljungqvist and Sargent, Recursive Macroeconomics, 2nd edition (Cambridge, USA: 2004)
  • 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.

Exam: 
Written (90 minutes)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at DIW, Mohrenstr. 58, Elinor-Ostrom Hall (1.2.019)
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.

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, 4th edition (MIT Press, USA: 2018); 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 (90 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at DIW, Mohrenstr. 58, Karl-Popper-Room (2.3.020)
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, statespace 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.

Written exam (90 min)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday, 08:30am at TU, Strasse des 17. Juni 135, room H 0107
Description:

This course is divided into two parts:

The first part by Frank Heinemann analyzes how future expected money supply affects the current price level, why money can be written in the utility function and what is required to determine a unique equilibrium with rational expectations. Turning to the foundations of New Keynesian Macroeconomics, we analyze why monopolistic competition leads to an active role for monetary policy, derive the forward looking Phillips curve and study optimal monetary policy.

The second part (starting June 15) of this course deals with search and matching and is taught by Mathias Trabandt from Free University. The syllabus and organizational details about the second part of the course will be published in due course at www.wiwiss.fu-berlin.de/trabandt.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:30am to 12:00pm
at TU Berlin, Main Building, room H 0112
at DIW, Mohrenstr. 58, Schumpeter hall
Description:

The first part (Heinemann) analyzes how future expected money supply affects the current price level, why money can be written in the utility function and what is required to determine a unique equilibrium with rational expectations. Turning to the foundations of New Keynesian Macroeconomics, we analyze why monopolistic competition leads to an active role for monetary policy, derive the forward looking Phillips curve and study optimal monetary policy.

Literature:

Part 1
Blanchard, Olivier J.; Stanley Fischer, Lectures on Macroeconomic, MIT Press, 1989.
Walsh, Carl E., Monetary Theory and Policy, 2nd edition, MIT-Press, 2003.
Woodford, Michael, Interest and Prices: Foundations of a Theory of Monetary Policy, Princeton University Press, 2003.

Exam: written midterm and final exam

See also the information on the website for this course. Part 1:
http://www.macroeconomics.tu-berlin.de/menue/teaching_-_lehre/adv_macroe...

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
08:00am to 12:00pm
at TU Main Building, room H 0111/H 0112
Wednesday,
08:00am to 12:00pm
at DIW Schumpeterhörsaal
Description:

First part: Frank Heinemann
April 10 to May 22, TU Berlin, Main Building, room H 0111/H 0112

Second part: Michael Burda/Alexander Meyer-Gohde
May 29 to July 10, DIW Schumpeterhörsaal

More details will be announced soon.

Credits:
9.00
Click here to get more information or to sign up
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Part 1: Henry Sauermann ‘The economics and sociology of science’

Part 2: Linus Dahlander ‘Management of innovation’

Literature: please see syllabus
Exam: paper presentation/term paper

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT Berlin, Schlossplatz 1
Description:

Management Science I

Instructor: Francis de Vericourt
Sequential decision making under uncertainty

Instructor: Linus Dahlander:
Networks: Data collection and visualizations & Tie strength, dyads, triads, and centrality

Instructor: Gianluca Carnabuci
Network brokerage & Network cognition

Instructor: Matt Bothner
The analysis of economic and social networks

Please see schedule attached.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Management Science I

Part I:
Instructor: Prof. Linus Dahlander, ESMT Berlin
2 sessions
Topic: Networks: Data collection and visualizations & Tie strength, dyads, triads, and centrality

Part II:
Instructor: Prof. Francis de Vericourt, ESMT Berlin
8 sessions
Topic: Sequential decision making under uncertainty

Part III:
Instructor: Prof. Matthew Bothner, ESMT Berlin
4 sessions
Topic: The analysis of economic and social networks

Part IV:
Instructor: Prof. Gianluca Carnabuci, ESMT Berlin
2 sessions
Topic: Network brokerage & Network cognition

Please see syllabi and schedule attached

Credits:
9.00
Click here to get more information or to sign up
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
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Management I Part 1: Instructor: Francis de Véricourt (ESMT)

Topic: Sequential Decision Making Under Uncertainty - With Applications to Operations and Management Sciences
Please note: The course will start on October 22, the missing session will be re-scheduled.
Sessions: 22.10., 29.10., 05.11., 12.11., 26.11., 03.12., 10.12., 17.12.2015, 12.01.2016 (exam session)

Management I Part 2: Instructor: Matt Bothner (ESMT)

Topic: The Analysis of Economic and Social Networks
Sessions: 07.01., 14.01., 21.01., 28.01., 04.02., 11.02.2016

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Management I Part 1:

Instructor: Francis de Véricourt (ESMT)
Topic: Sequential Decision Making Under Uncertainty - With Applications to Operations and Management Sciences
Sessions: 16.10., (no class on 23.10.), 30.10., 06.11., 13.11., (no class on 20.11.), 27.11., 04.12., 11.12., 18.12.2014

Management I Part 2:

Instructor: Matt Bothner (ESMT)
Topic: The Analysis of Economic and Social Networks
Sessions: 08.01., 15.01., 22.01., 29.01., 05.02. (moved to 11.02.!), 12.02.2015

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
08:45am to 11:45am
at ESMT, Schlossplatz 1
Description:

Please note that the sessions start at 8:45am s.t.
Location: ESMT Learning Center Seminar Room 00.21 (Session on 21.11.13 will take place in room 'Bookshop')

The Analysis of Economic and Social Networks - Part I:
Instructor: Linus Dahlander
Sessions: 17.10., 24.10. (Postponed: New date for this session is 07.11.13, 5-8pm), 31.10., 07.11., 14.11.13

The Analysis of Economic and Social Networks - Part II:
Instructor: Matthew Bothner
Sessions: 21.11.13, 23.01., 30.01., 06.02., 13.02.14

Sequential Decision Making Under Uncertainty:
Instructor: Francis de Véricourt
Sessions: 28.11., 05.12., 12.12., 19.12.13, 09.01., 16.01.14

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:30pm
at ESMT
Description:

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 in labor markets, risk-taking behavior in tournaments, and affiliation-based market signaling. 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) understanding the foundations of social network theory and (2) applying methods.

Exam: Project work and presentations.

Please note that this class starts at 9am s.t..

The first session (18.10.12) is taking place in the ESMT Admin Building, room 0.35 on the ground floor. Please use the entrance on Breite Str. 1. All further sessions are taking place in the ESMT Learning Center. Please use the entrance Schlossplatz 1 and refer to the info screen for room numbers.
  

 

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

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 in labor markets, risk-taking behavior in tournaments, and affiliation-based market signaling. 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) understanding the foundations of social network theory and (2) applying methods.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday,
09:00am to 01:00pm
at ESMT (various rooms)
Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Management Science II

Please see syllabus and schedule attached

Part 1:
Instructor: Henry Sauermann
Topic: The organization of science

Part 2:
Instructor: Linus Dahlander
Topic: Creativity and Innovation

Part 3:
Instructor: Stefan Wagner
Topic: Innovation, intellectual property rights and the market for technology

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Management II Part 1:

Instructor: Stefan Wagner
'Innovation, Intellectual Property Rights and the Market for Technology'

Management II Part 2:

Instructor: Özlem Bedre-Defolie
'Topics in Industrial Organization'

Please see schedule and syllabi for details.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Management Science II - Part 1: Innovation, Intellectual Property Rights and the Market for Technology

Instructor: Stefan Wagner

The course is designed to impart profound understanding of the economic principles and managerial practices on a range of topics pertaining to the protection of intellectual property in the realm of technical inventions. It will include an economic analysis of the incentives created for firms to engage in costly and risky R&D endeavors that (i) result from the design of the underlying IP regime itself as well as from (ii) strategic interaction of firms within this system. Moreover, we will scrutinize how firms can use intellectual property rights to appropriate the value created from their innovative activities by either exploiting them themselves or by using it for contracting with other firms in the market for technology.

Management Science II - Part 2: Industrial Organization

Instructor: Özlem Bedre-Defolie

This course familiarizes students with classical statistical methods of management research and theoretical models in industrial organization and strategic management. The second part of the course analyzes in depth competitive strategies of vertical relations and control (B to B contracting), vertical foreclosure, entry deterrence, horizontal foreclosure (tying and bundling strategies), and economics of platforms.

Evaluation:
Grading is based on one individual assignment for which each student is expected to write one referee report on a recent research paper. The instructors will provide a list of research papers on the topics of each part of the course from which students could choose one paper to prepare a referee report. The list of research papers will be provided during the course.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1
Description:

Management Science II

This course familiarizes students with classical statistical methods of management research and theoretical models in industrial organization and strategic management.

Please see syllabus attached.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1, Room 00.21/00.17
Description:

Management Science II

April 17 - June 19, 2014: Innovation, intellectual property rights and the market for technology, Instructor: Stefan Wagner
June 26 & July 3, 2014: Demand estimation, Instructor: Michał Grajek
July 10 & 17, 2014: Factor analysis, Instructor: Catalina Stefanescu-Cuntze

Please see attached documents for details.

The course will take place in room 00.21 or 00.17, Schlossplatz 1. The session on May 8 will take place in room 'Bookshop'. The sessions on May 15 and July 17 will take place in room 0.35 Admin Building - please use entrance Breite Str. 1.

Starting time for this course is 9 o'clock s.t.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1, Room 00.21
Thursday,
09:00am to 12:00pm
at ESMT, Schlossplatz 1, room to be confirmed
Description:

The course Management Science II is divided into two consecutive modules: The first module encompasses intellectual property rights and the market for technology while the second module covers marketing models. Time I and Venue I above refer to the first module, Time II and Venue II to the second module.

Please refer to the downloads below for details (course outline and format, reading list, etc.) about the two modules.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Thursday,
02:00pm to 05:00pm
at Module I: ESMT Bookshop
Thursday,
02:00pm to 05:00pm
at Module II: at ESMT, room to be confirmed
Description:

The course Management Science II is divided into two consecutive modules: the first module encompasses marketing models while the second module covers intellectual property rights and the market for technology. Time I and Venue I above refer to the first module, Time II and Venue II to the second module.

Please refer to the dowloads below for details (course outline and format, reading list, etc.) about the two modules.

Credits:
4.50
Click here to get more information or to sign up
Instructor:
Description:

The course Management Science II is divided into two consecutive modules: The first module encompasses intellectual property rights and the market for technology while the second module covers marketing models. Time I and Venue I above refer to the first module, Time II and Venue II to the second module.

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

This course is devoted to the economic theory of preferences and choice, consumer choice, demand, production, market equilibrium, decision making under uncertainty, and game theory. The intention of the course is to familiarize students with the advanced tools of modern microeconomic theory.

Literature:
Mas-Colell, Whinston, Green: Microeconomic Theory (1995).

Credits:
9.00
Click here to get more information or to sign up
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
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at ESMT, Schlossplatz 1, Room 00.21
Monday,
12:00pm to 04:00pm
at FU Berlin, Boltzmannstrasse 20, Room 328
Monday,
12:00pm to 04:00pm
at HU Berlin, Spandauerstr. 1, Room 203
Description:

This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and 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, and Green (1995), Microeconomic Theory, Part III and Part V

Exam:
Written exam (90 min)

Locations:
ESMT, Schlossplatz 1, Room 00.21 (April 8 to April 29, 2013)
FU (May 6 – June 3, 2013)
HU, Spandauerstr. 1, Room 203 (from June 10, 2013)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at ESMT, Schlossplatz 1, Room 00.21
Monday,
12:00pm to 04:00pm
at HU Berlin, Spandauer Straße 1, Room 203
Description:

The course provides a rigorous and systematic introduction into the theory of markets and organizations at a level geared to Ph.D. students. It covers all areas of microeconomics on an advanced level. Particular emphasize is given to the theory of asymmetric information and incentives.  

Note: The first part (April 16 to May 21, 2012) takes place at the ESMT, the second part  (May 28 to July 9, 2012) takes place at Spandauer Str. 1.

Exam:
Written exam (90 min)

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

This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and 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, and Green (1995), Microeconomic Theory, Part III and Part V

Credits:
9.00
Click here to get more information or to sign up
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
Instructor:
Monday,
12:00pm to 04:00pm
at R203, Spandauer Str. 1
Description:

This course is devoted to the economic theory of preferences and choice, consumer choice, demand, production, market equilibrium, decision making under uncertainty, and game theory. The intention of the course is to familiarize students with the advanced tools of modern microeconomic theory.

Literature: Mas-Colell, Whinston, Green: Microeconomic Theory (1995).

Exam:
4 written exams during the course,
1 final written exam

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at HU Berlin, Theologische Fakultät, Room 26 (BU 26)
Description:

This course is devoted to the economic theory of preferences and choice, consumer choice, demand, production, market equilibrium, decision making under uncertainty, and game theory. The intention of the course is to familiarize students with the advanced tools of modern microeconomic theory.

Literature: Mas-Colell, Whinston, Green: Microeconomic Theory (1995).

Tutorials:
Tue. 12-2pm, room 21a (Philipp Heller)
Wed. 2-4pm, room 21b (Philipp Heller)
Thu. 2-4pm, room 21b (Johannes Johnen)

Exam:
4 written exams during the course,
1 final written exam

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
01:00pm to 05:00pm
at DIW Berlin, Mohrenstr.58, Schumpeter Hall
Description:

This course is devoted to the economic theory of preferences and choice, consumer choice, demand, production, market equilibrium, decision making under uncertainty, and game theory. The intention of the course is to familiarize students with the advanced tools of modern microeconomic theory.

Exercise classes:    

Andreas Asseyer: Thursday, 8-10am, Spandauer Str., 21a

Jano Costard: Tuesday, 4-6pm, DIW, Dulles (5.2.010)

Dietmar Fehr/Tobias Schmidt: Tuesday, 1:30-3:30pm and 4-6pm, DIW, Schmoller (1.2.026)

Literature: 
Mas-Colell, Whinston, Green: Microeconomic Theory (1995).

Exam:
4 during the course, 1 final exam

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at TU Berlin, Straße des 17. Juni 135, Main Building, room H 0106
Thursday,
02:00pm to 04:00pm
at HU Berlin, Spandauer Str. 1, room 21a
Friday,
04:00pm to 06:00pm
at HU Berlin, Spandauer Str. 1, room 21b
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. Also matching problems will be discussed.

Literature:
Mas-Colell, A., Whinston, M.D. and J.R. Green (1995), Microeconomic Theory, Oxford University Press

Time and venue:
Lectures: Mondays, 12:00-16:00, TU Berlin, Straße des 17. Juni 135, Main Building, room H 0106
Tutorials: Thursdays, 14:00-16:00, HU Berlin, Spandauer Str. 1, room 21a or Fridays, 16:00-18:00, HU Berlin, Spandauer Str. 1, room 21b

Exam:
4 written midterms and 1 written final exam

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at Spandauer Str. 1, 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. Also matching problems will be discussed.

Literature: Mas-Colell, A., Whinston, M.D. and J.R. Green (1995), Microeconomic Theory, Oxford University Press

Exam (written): 4 midterms and 1 final exam

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at HU Berlin, Spandauerstr. 1, Room HS 203
Monday,
12:00pm to 04:00pm
at FU Berlin, Boltzmannstr. 20, Room HS 328
Description:

This course is devoted to market failures and welfare economics. The first part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The second part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. 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, and Green (1995), Microeconomic Theory, Part III and Part V

Exam:
Final Exam: July 24 at HU Room tba

Exercises:
Tianchi Li
Thursday, 12:00pm to 14:00pm
April 24 – May 22 at HU Berlin, Spandauerstr. 1, Room HS 203
May 29 – July 17 at HU Berlin, Spandauerstr. 1, Room HS 203

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

This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and 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, and Green (1995), Microeconomic Theory, Part III and Part V

Exam: Final Exam: 18.7.2016

Mondays, 12:00pm to 04:00pm

18.4 Matthias Lang
25.4 Matthias Lang
2.5 Matthias Lang
9.5 Matthias Lang
16.5 no lecture
23.5 Helmut Bester
30.5 Helmut Bester
6.6 Helmut Bester
13.6 Helmut Bester
20.6 Roland Strausz
27.6 Roland Strausz
4.7 Roland Strausz
11.7 Roland Strausz
18.7 Exam

April 18 – June 13 at FU Berlin, Boltzmannstr. 20, Room HS 328
June 20 – July 18 at HU Berlin, Spandauerstr. 1, Room HS203

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at ESMT, Schlossplatz 1, Room 00.17
Monday,
12:00pm to 04:00pm
at FU Berlin, Boltzmannstr. 20, Room HS 328
Monday,
12:00pm to 04:00pm
at HU Berlin, Spandauerstr. 1, Room 203
Description:

Instructors:
Paul Heidhues - ESMT, Schlossplatz 1, Room 00.17 (April 13 to May 4, 2015)
Helmut Bester - FU, Boltzmannstr. 20, Room HS 328 (May 11 to June 8, 2015 - no class on May 25)
Roland Strausz - HU, Spandauerstr. 1, Room 203 (June 15 to July 13, 2015)

Description of the course:
This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and 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, and Green (1995), Microeconomic Theory, Part III and Part V

Exam:
Final Exam (13.07.2015)

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday,
12:00pm to 04:00pm
at ESMT, Schlossplatz 1, Room 00.21/00.17
Monday, 12:00pm at FU, Garystr. 21, Room 105
Monday, 12:00pm at HU (Rooms tbc)
Description:

Instructors:
Paul Heidhues - ESMT, Schlossplatz 1, Room 00.21/00.17 (April 14 to May 12, 2014)
Helmut Bester - FU (May 19 to June 16, 2014)
Roland Strausz - HU (June 23 to July 14, 2014)

Description of the course:
This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and 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, and Green (1995), Microeconomic Theory, Part III and Part V

Exam:
Final Exam (14.07.2014)

Credits:
9.00
Click here to get more information or to sign up
Thursday,
02:30pm to 05:30pm
at Ferdinand Friedensburg Room 22008, DIW Berlin. On June 12 in R12026
Description:

This course discusses advantages and limitations of structural econometric models to give students an understanding of why and when adding structure is important. It also provides insights into strategy in important papers in structural Labor, Public and IO literature and establishes basic estimation techniques and numerical methods such as Simulation, Numerical integration and Discretisation. Besides of that, the course provides introduction to the matrix programming language MatLab.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Friday,
10:15am to 11:45am
at HU Berlin, Spandauer Str. 1, room 21b
Description:

In the seminar, the theoretical foundations of machine learning will be discussed. Topic include probably almost correct learning, VC dimension, risk minimization, boosting, model selection, stochastic gradient descent, support vector machines, kernel methods, and neural networks. After an introduction to the general topic of machine learning, students will present a chapter in the book “Understanding machine learning” by Shalev-Shwartz and Ben-David (Cambridge Universit Press) and hand in a short summary of the key findings. Participation in the discussions is expected.

Literature:
“Understanding machine learning” by Shalev-Shwartz and Ben-David (Cambridge Universit Press)

Exam:
Presentation and portfolio (30,000 characters). The portfolio examination consists of a research project in which the students show their learning progress.

Credits:
9.00
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Instructor:
Monday,
02:00pm to 04:00pm
at Spandauer Straße 1, room 22; Empirical Tutorials take place at room 025 (Mon)
Tuesday,
12:00pm to 02:00pm
at Spandauer Straße 1, room 203
Description:

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.

In the tutorials the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

Literature:
- Hamilton (1994). Time Series Analysis. Princeton, University Press.
- Schlittgen/Streitberg (2001). Zeitreihenanalyse. Oldenburg Verlag, München.
- Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer
Verlag, Heidelberg.
Exam: written exam (90 min)

Credits:
9.00
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Instructor:
Friday, 10:00am at Technische Universität, mainbuilding, Straße des 17. Juni 135, room H0112
Description:

What is a causal effect and how can we identify and estimate a causal effect from nonexperimental data? These are among the most important questions in applied econometric research. This course will give an introduction and overview over the most important concepts and methods in this field, including the Rubin model of causality, the Roy model, statistical matching, instrumental variables, difference-in-differences methods, switching regression models, regression discontinuity design.

Time frame (date of first and last class): 17.4 - 17.7.2015

Time(s) and Location(s):
Lecture: Fr 10:00-12:00, room H0112 (TUB main building)
Tutorial: Fr 8:00-10:00, room H1028/TEL 206re

Credits:
9.00
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