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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Wednesday, 10:00am at SPA1, R23
Description:

The Brown Bag Seminar is an informal research seminar on business and economics. Doctoral students and faculty members are invited to present their current research including work in progress, early stage projects as well as advanced projects. All faculty members and PhD students are kindly invited to attend the seminar.

If you are interested in presenting your work in the seminar, please send an email to Grzegorz Dlugoszek (dlugoszg@hu-berlin.de). Announcements of upcoming talks are sent by email.

The seminar takes place weekly on Wednesdays from 12:30 p.m. until 2:00 p.m. in room 23.

Speaker Affiliation Affiliation Job Market Candidate Title
18.10.17          
25.10.17 Stefanie Seele HU JMC No Role for the Hartz Reforms? Demand and Supply Factors in the German Labor Market, 1993-2014  
01.11.17 Lukas Mergele HU JMC Public Employment Services Under Decentralization: Evidence from a Natural Experiment  
08.11.17 Anna Almosova HU   A Closer Look at the Costs of Digital Currency Provision  
15.11.17 Homayoon Moradi WZB JMC    
22.11.17 Benjamin Larin Uni Leipzig   The Macroeconomics of Housing and the Dynamics of Wealth Inequality  
29.11.17 Ahmed Hanoma FU   Inflation Expectations with MIDAS: Can Market-Based Measures Forecast Survey-Based Measures  
08.12.17 Hannh Liepmann HU JMC The Impact of a Negative Labor Demand Shock on Fertility - Evidence from the Fall of the Berlin Wall.  
13.12.17 Short Session Presentation        
20.12.17 Johanna Krenz HU   Unconventional Monetary Policy in a Monetary Union  
Christmas Holiday          
10.01.18 Anna Almosova HU      
17.01.18 Lech Suwala HU      
24.01.18 Maren Brede HU      
31.01.18 Mauricio Salgado Moreno HU      
07.02.18 Julia Otten HU      
14.02.18 Grzegorz Dlugoszek HU      

 

Credits:
0.00
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Monday,
09:30am to 11:00am
at ESMT, Schlossplatz 1, Room: Garden View
Description:

Course content:

Monday 20th of November: The first lecture is mainly Milgrom and Weber (82), Milgrom (81) and Pesendorfer and Swinkels (97) (Auctions and information aggregation)
Tuesday 21st of November: Second lecture is on Austen-Smith and Banks (96), and some papers of Feddersen and Pesendorfer.
Wednesday 22nd of November: Third lecture is on Battaglini (2017), Wolinsky (2002) and a new paper I am working on with Stephan Lauermann.

BDPEMS is organizing the course.

Credits:
3.00
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Monday,
10:00am to 01:30pm
at ESMT
Tuesday,
12:30pm to 04:00pm
at ESMT
Description:

The Messy Case for FDI Spillovers - Ronald B. Davies (UCD)

Among the supposed benefits of hosting foreign direct investment is that when multinationals are active in the host market, this increases the productivity of domestic firms via technological spillovers. In this short course, we will examine the evidence on such effects. In doing so, not only will we discuss the data on FDI, but also cover the main techniques used to construct productivity. Therefore the course will be of use to those interested in productivity more generally, including those in industrial organization, development, and macroeconomics.

The course will consist of four 90 minute lectures with a short exam given afterwards for those looking for credit.
The room will be announced in time.

Credits:
3.00
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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
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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:
Monday,
10:00am to 02:00pm
at SPA1, R22
Description:

Further description will follow.

Credits:
6.00
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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:
Description:

Graduate students in the field of econonometrics and applied labor markets present and discuss their ongoing research projects.

Audience: master students, doctoral students
No obtainment of credit points. Dates will be announced.

Credits:
0.00
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Wednesday,
10:00am to 12:00pm
at SPA1, R23
Description:

What determines business cycle fluctuations? How can we make causal statements in macroeconomics in general? In this course, students will study concepts, methods and techniques used in empirical macroeconomics. Therefore, it will be a good complement to advanced macroeconomics courses. The course consists of three blocks (see tentative schedule below). In the first block, the course covers basic time series models, estimation and inference methods and forecasting. In the second block, the course will introduce students to the identification of causal effects in macroeconomic time series through restrictions coming from economic theory and/or other information. The third block, subject to time availability, will be devoted to more advanced topcs. Students will also learn how to program in Matlab.

The course consists of a weekly lecture throughout the semester (2SWS). A repetition section (2SWS) will cover analytical and computer exercises. Due to the extensive nature of the material covered, successful completion of the course makes it essential to attend class regularly. Lectures will be in English.
Pre-requisites: IAMA/Advanced Monetary Economics/other advanced macroeconomics courses and Introduction to Econometrics/Macroeconometrics (BSc). In general, students should have taken standard undergraduate level econometrics and be knowledgeable in basic probability and modern dynamic macroeconomic models (DSGE). Some prior knowledge of scientific programming is desirable but not essential for successful completion of the course.

Aims/Outcomes: Upon successful completion of this course, the student should be able to:
(a) Communicate and explain key concepts in (time series) macroeconometrics.
(b) Specify, estimate and critically assess vector autoregressive models.
(c) Understand the concept of identification and the link between DSGE models and the data.
(d) Formulate and solve macroeconometric problems with computer software.
(e) Develop further analytical and computational skills.
(f) Appreciate the differences between empirical approaches to tackle macroeconomic questions.

The following books cover most of the material. Further references/readings will be provided during the lecture.

*Canova, F. (2007) “Methods for Applied Macroeconomic Research”, Princeton University Press
*Hamilton, J.D (1994), Time Series Analysis, Princeton U Press
*Kilian, L and Lütkepohl, H (2017), Structural Vector Autoregressive Analysis (online)
*Lütkepohl, H (2007), New Introduction to Multiple Time Series Analysis, Springer

Credits:
6.00
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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
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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
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
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:
Description:

This semester we will offer an one-off additional seminar for students at all levels (Bachelor/Master/Doctoral). Its main objective is to learn the fundamentals of the Open Data Science workflow based on Github and R. We will do this by jointly evaluating the findings of a field experiment on the effects of self-regulated online learning and procrastination on exam performance. Interested students can apply by sending their Github account ID and their most recent transcript of records to Joachim Gassen (gassen(at)wiwi.hu-berlin.de) until November 3, 2017. For further information please check the attached syllabus. Feel free to contact Joachim Gassen directly in case you have additional questions.

Credits:
6.00
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Wednesday,
10:00am to 02:30pm
at tba
Description:

The Preparatory Math Course provides the general background in mathematics and statistics necessary for the first year courses and for research related work in economics in general. It is aimed to give a brief overview of the main concepts and methods used in economics research. Topics include calculus, analysis, matrix algebra, probability, statistics and others.

Please find attachd the syllabus and the timetable. You'll find the slides to the course when you follow the link attached.

Credits:
0.00
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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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Instructor:
Friday,
10:00am to 12:00pm
at SPA1, R23
Description:

Reading group on mechanism design without transfers

Literature: Original papers on mechanism design without transfers
Exam (written?): No

Credits:
3.00
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Friday,
10:00am to 12:00pm
at SPA1, R22
Description:

Search and matching frictions as a fundamental defining attribute of labor markets. Introduction to search theory in partial equilibrium. On-the-job search and wage distributions in general equilibrium. Models of wage-posting. Jovanovic's model. Incorporation of search-matching frameworks in general equilibrium models: Diamond, Mortensen/Pissarides, and other macro models. Implications for labor market institutions.

Literature: Specialized Literature, Skript
Exam: Written exam (90 min)

Credits:
6.00
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Instructor:
Thursday,
10:00am to 12:00pm
at Do 202 Sitzungsraum / Kaminzimmer (Boltzmannstr. 16-20), Do HFB/K I Konferenzraum (Garystr. 35-37), Do Hs 108a Hörsaal (Garystr. 21)
Credits:
6.00
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