Courses

Wednesday,
10:00am to 12:00pm
at HU Berlin, Dorotheenstraße 1, Room 005
Description:

This course provides a theoretical and empirical treatment of major topics in corporate finance, including capital structure, investment decisions, corporate governance, corporate cash and payout policy, as well as credit ratings and financial regulation. The course is based on academic articles and designed for Ph.D. students interested in corporate finance. An integral part is the computer lab where students implement key models and econometric methods in GNU/R.

Literature:
Academic articles

Exam (written?):
No final exam. Grading is based on the contribution to class discussions (20%), presentation of research paper (15%), lab code (25%), seminar paper (40%).

Credits:
6.00
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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
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Instructor:
Wednesday,
10:00am to 12:00pm
at Freie Universität, HS 104a (tba)
Description:

The aim of the course is to teach students how to interpret empirical research in public economics and to apply modern econometric methods commonly used in the field. The course covers alternative empirical approaches and important topics in empirical public economics. Empirical approaches include both structural and non-structural estimation methodologies.

Topics include: The measurement of the distribution effects of taxes and transfers, treatment effects estimation of policy reforms, structural estimation of labor supply models with taxes, and the empirical ex-ante evaluation of tax-benefit reforms. The course assumes knowledge of applied microeconometrics.

Literature: Journal articles
Exam (written?): 2 hours final exam; term paper

Credits:
6.00
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Instructor:
Tuesday,
08:00am to 10:00am
at SPA 1, 22
Tuesday,
02:00pm to 04:00pm
at SPA1, 22
Description:

This course presents nonparametric and semiparametric regression techniques and modern microeconometric methods for treatment effects estimation. The treatment focuses on the potential outcome approach, and students learn various methods to account for selection based on observables (regression, matching, inverse probability weighting) and for selection based on unobservables (Heckman selection correction, difference-in-differences, panel regression, instrumental variable regression, regression discontinuity design). These methods are used for cross-section data and longitudinal data, both repeated cross-sections and panel data. Students will familiarize themselves with applying the methods to real empirical data using Stata.

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.
HL: Härdle, W. and O. Linton (1994): "Applied Nonparametric Methods", in: Handbook of Econometrics, Vol. 4, R. F. Engle und O. F. McFadden, (eds.), Elsevier Science.
PU: Pagan, A. and A. Ullah (1999): Nonparametric Econometrics, Cambridge University Press.
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... ).

Further references, particularly regarding the method of Quantile Regression and the application of the methods, will be given in the course.

Exam: written exam (90 min)

Credits:
6.00
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Instructor:
Wednesday,
08:30am to 12:00pm
at DIW, Mohrenstr. 58, Dulles
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
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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
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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
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Monday,
11:00am to 02:00pm
at DIW, room: tba
Description:

This course investigates strategic interactions in energy resource markets and covers advanced optimization and equilibrium concepts to solve the associated models. It aims to provide participants with a strong theoretical understanding of Generalized Nash games, leader-follower Stackelberg games, and the related mathematical concepts of (Quasi-) Variational Inequalites (VI and QVI), Mixed Complementarity Problems, and Mathematical/Equilibrium Problems under Equilibrium Constraints (MPEC/EPEC). The practical part of the course covers applications of these methodologies to energy market problems, based on examples from the recent literature, and case studies in the oil, natural gas, and coal sector.

Participants are expected to have a basic knowledge of nonlinear optimization, mixed complementarity problems, Karush-Kuhn-Tucker conditions and convexity in higher dimensions as well as hands-on experience in GAMS.

Trainer: Sauleh Siddiqui, PhD, is Assistant Professor at the Whiting School of Engineering and is on the leadership council of the Systems Institute at Johns Hopkins University, Baltimore.

Room and time schedule will be announced later on!

Credits:
6.00
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Instructor:
Tuesday,
10:00am to 12:00pm
at Technische Universität Berlin, Straße des 17. Juni 135, Gebäudeteil Mechanik, room M 128 (lecture)
Friday,
02:00pm to 04:00pm
at Technische Universität Berlin, Straße des 17. Juni 135, Hauptgebäude, room H3004 (tutorial)
Description:

Please note that there is both a lecture and a tutorial:

Instructor(s): Marco Runkel (lecture), Zarko Kalamov (tutorial)
Time frame (date of first and last class): October 17, 2017 until February 13, 2018 (lecture), October 20, 2017 until February 16, 2018 (tutorial)
Weekday(s): Tuesday (lecture), Friday (tutorial)
Time(s): 10am – 12am (lecture), 2pm – 4pm (tutorial)
Location(s): Technische Universität Berlin, Straße des 17. Juni 135, Gebäudeteil Mechanik, room M 128 (lecture)
Technische Universität Berlin, Straße des 17. Juni 135, Hauptgebäude, room H3004 (tutorial)

English description of the course: given in the first session
Literature: given in the first session
Exam: final exam (90 minutes)

Credits:
6.00
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