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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:
Monday, 08:30am to 12:00pm at online
Description:

This course provides students with the neccessary background to understand modern academic research in finance and to pursue their own finance-related research projects. It covers principles of asset pricing, financial intermediation and corporate finance. The course covers both empirics and theory. More information can be found on Moodle: https://moodle.hu-berlin.de/enrol/index.php?id=95193

The course is a mandatory Core Course in the PhD track in Finance. It can also be attended as an Elective Course for the PhD tracks in Accounting, Economics or Management. The course will be useful for any PhD student aiming to pursue a research career that touches on finance-related topics, e.g., at universities, business schools, central banks, financial regulators.

Evaluation:

Master students: Final exam
PhD students: Final exam and presentation

Literature:

Jean Tirole, “The Theory of Corporate Finance”, (2006), Princeton University Press
John Cochrane, "Asset Pricing", Princeton University Press, 2nd Edition

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

This course deals with advanced estimation techniques in modern econometrics. In the first part we study Pesudo-ML and GMM as extremum estimation problems with special attention to asymptotic theory and the weak instruments problem. The second part covers non- and semi-parametric topics including the bootstrap, density estimation, and non- and semi-parametric regression. The third part covers the concept of econometric identification, and possible frameworks to write down and interpret causal estimands (treatment effects). We also discuss a number of techniques for estimation of treatment effects (IV, Diff-and-Diff, RDD, Matching).

Literature:

tba

Exam:

Written exam (90 min)

More information can be found on Moodle: https://moodle.hu-berlin.de/enrol/index.php?id=102843

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Wednesday, 08:30am to 12:00pm at online
Description:

Time frame (date of first and last class):

  • Lectures by Alexander Kriwoluzky: every Wednesday from April 14 to May 26
  • Lectures by Frank Heinemann: every Wednesday from June 2 to July 14

Time(s):

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

Description of the course:

  • Lectures by A. Kriwoluzky: This part of the course teaches methods to analyze the effects of monetary and fiscal policy. Methods cover narrative and high-frequency identification of policy interventions, local projections, Vector-Autoregression models, and DSGE models.
  • Lectures by F. Heinemann: This part of the course covers topics such as growth, determinacy of the price level, bubbles, equilibrium multiplicity, strategic uncertainty, and current limits of DSGE models. More information will be provided at https://www.macroeconomics.tu-berlin.de/menue/teaching_lehre/adv_macroeconomic_analysis_ii/

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:
Thursday, 09:00am to 12:00pm at ESMT, Schlossplatz 1 or Zoom
Description:

Part 1: Networks and organizations I: Core concepts and methods to understand networks in organizations
Instructor: Eric Quintane

The first part of the course introduces social network analysis within organizations. We will start by discussing key ideas and debates in social network analysis, such as the notion of embeddedness, network structure and the role of individual agency. We will then take a deeper dive into the methodological implications of doing research with social network data. We will cover 1) measures used to identify network positions and key network characteristics, 2) more advanced statistical models developed to handle the problem of dependence of observations and 3) concepts and measures regarding network dynamics. This first part will equip you with the knowledge that you need to embark in more advanced topics in network analysis.

Part 2: Networks and organizations II: Further topics in network analysis, including semantic networks,
strategic network formation, and Bonacich centrality
Instructor: Matt Bothner

The second part of the course explores empirical applications of network-analytic methods to a wide array of agents—professional auto racers, gangsters, college fraternity members, and words in semantic networks. In addition to our empirical emphasis, we’ll consider a game-theoretic network formation model designed to better understand the performance-related consequences of peer monitoring within the firm.

Part 3: Organizational learning, behavioral strategy, and luck
Instructor: Chengwei Liu

The third part of the course focuses on organizational learning and its implications for strategy. We will cover canonical ideas/models, such as the exploration and exploitations trade-off, the traps when organizations learn from successes and failures, how randomness complicates learning, and how learning reinforces or changes organizational routines. A framework of strategy as arbitrage will be introduced to connect several ideas covered in this course.

Please see schedule and syllabus attached.

Credits:
9.00
Click here to get more information or to sign up
Instructor:
Monday, 12:00pm to 04:00pm at online
Thursday, 12:00pm to 02:00pm at online
Description:

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. 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 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 issue both from a positive and normative perspective.

Course times:

Mondays 12:00 - 4.00 pm: lectures
Thursdays 12:00-2:00 pm: exercises (held by Amir Habibi)

Literature:

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

Exam:

Written exam (90 min)

More information can be found on Moodle: https://moodle.hu-berlin.de/enrol/index.php?id=103735

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