Courses

Wednesday,
10:15am to 11:45am
at Garystr. 21, 14195 Berlin-Dahlem, HS 106
Description:

The aim of applied microeconometrics is to analyze individual behavior on  the basis of micro data  (cross-section 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 micro data and the software package STATA

Lectures 10:15-11:45, Garystr. 21 HS 101
Computer Exercises biweekly 08:30-10:00, K 006a PC Pool 1

Literature: M. Verbeek, A Guide to Modern Econometrics (4 ed.), Wiley, 2012. 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 Selected journal articles on empirical applications. Exam: Written final exam; research paper

Credits:
6.00
Click here to get more information or to sign up
Friday, 02:00pm at DIW, Schmoller R1.2.026
Description:

Federico Ciliberto (University of Virginia) will hold his lecture from 14:00-17:30 (13.11) until 09:00-12:30(16.11).

This seminar will over two papers in empirical industrial organization in detail to show how frontier methodologies can be implemented in Matlab. By the end of the class, the students will be able to adapt and extend the methodologies to new problems. We will begin with the estimation of complete information, static, discrete games. Then, we will consider the estimation of dynamic models of strategic interaction with incomplete information, with a particular focus on discrete choice dynamic models. Each lecture will consist of two parts: in the first part we will go over selected parts of the articles, where the article makes the fundamental methodological advances; in the second part we will go in detail over how the methodological advances are actually implemented in Matlab. The unifying theme in the two papers is how to use moment inequalities to estimate models of strategic competition.

Click here to get more information or to sign up
Instructor:
Friday, 10:00am at HU Berlin, Spandauer Straße 1, Room 21a
Description:

This course studies recent developments in the literature on “persuasion games”. The goal is to develop a good understanding of these games, their theoretical underpinning, and the underlying economic mechanisms which they capture and emphasize. In each session a course participant actively presents a specific research papers in this field for 45 to 60 minutes, pointing out and explaining its main contributions. In the remaining 45 to 30 minutes, all course participants jointly and actively discuss the relevance and the relation to the rest of this literature. Participants are expected to attend all the sessions and participate actively.

Credits:
4.00
Click here to get more information or to sign up
Instructor:
Wednesday, 08:00am at FH 314, Fraunhoferstr. 33 – 36, 10587 Berlin
Description:

The students

  • Get introduced into the fundamental effects of taxes on capital ows and trade in open economies
  • Learn about the consequences of globalization on national and international tax policy
  • Gain insights into the reasons for the inecient provision of public goods due to tax competition
  • Become aquainted with policy instruments to mitigate tax competition
  • Acquire knowledge about prot shifting of multinational rms and dierent corporate tax systems
  • Learn how international trade of goods and services should be taxes

Literature: Literature: Haufler, A. (2001), Taxation in a Global Economy, Cambridge University Press

 

Exam: written

Credits:
6.00
Click here to get more information or to sign up
Instructor:
Monday, 12:15am at Spandauer Str. 1, R 21b
Description:

Description of the course:
The course covers a part of mathematical statistics which deals with the limiting behavior of different sample statistics, U-statistics, M-, L- and R-Estimates. This course gives better understanding for the basic tools learned in the elementary Statistics I and II, like Law of Large Numbers, Central Limit Theorem, Kolmogorov-Smirnov and Cramer-von-Mises tests, sample mean and sample variance behavior, etc. This course is laying a bridge between the probability theory and the mathematical statistics by manipulating with “probability” theorems to obtain “statistical” theorems.
In the first part of the course we discuss basic tools of asymptotic theory in statistics: convergence in distribution, in probability, almost surely, in mean. We also consider main probability limit laws: LLN and CLT. Then we deal with the usual statistics computed from a sample: the sample distribution function, the sample moments, the sample quantiles, the order statistics. Properties, such as asymptotic normality and almost sure convergence will be derived in the lecture. Afterwards, comes the asymptotics of statistics concocted as transformations of vector of more basic statistics. Next part concerns statistics arising in classical parametric inference and contingency table analysis. These include maximum-likelihood estimates, likelihood-ratio tests, etc. Last part of the course treats U-statistics, statistics obtained as solutions of equations (M-estimates), linear function of order statistics (L-estimates) and rank statistics (R-estimates).

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

Exam: Oral exam

Credits:
3.00
Click here to get more information or to sign up
Tuesday, 10:15am at Spandauer Str. 1, R 21a
Description:

The course offers an overview of advanced statistical methods in quantitative finance and insurance which should be comprehensible for a graduate student in financial engineering as well as for an inexperienced newcomer who wants to get a grip on advanced statistical tools applied in these fields.

   

Literature:

-      Cizek, Härdle, Weron (2011): Statistical Tools for Finance and Insurance. 2nd ed., Springer Verlag.

-      Franke, Härdle, Hafner (2011): Statistics of Financial Markets. 3rd ed., Springer Verlag.

-      Härdle, Hautsch, Overbeck (2009): Applied Quantitative Finance. 2nd extended ed., Springer Verlag.

-      Härdle, Simar (2012): Applied Multivariate Statistical Analysis. 3rd ed., Springer Verlag.

-      Gentle, Härdle, Mori (2012): Handbook of Computational Statistics, Concepts and Methods. 2nd ed., Springer Verlag.

-      Klugman, Panjer and Willmot (1998): Loss Models: From Data to Decisions. Joh Wiley & Sons.

   

Exam: Oral exam

 

 

Credits:
3.00
Click here to get more information or to sign up
Monday,
04:15pm to 07:45pm
at Spandauer Str. 1, R 23
Description:

Description of the course:

Learn from Nobel prize winners, such as Engle (ARCH Models, 2003), Scholes, Merton, (Derivative Valuation, 1997) or Modigliani (Financial Markets Analysis, 1985) to understand statistics of financial markets!

The class is addressed to students with excellent knowledge of multivariate statistics and students with good skills in statistical software. This course is a starting point for students interested in quantitative finance and students with ambitions to work in the derivative, investment and risk-control departments. Former students of this course work for example at Deutsche Bank, Sal. Oppenheim, Citigroup, European Central Bank, BAFin, KPMG, Nadler Company and many international universities.

   

Literature:

-      Franke, J., Härdle, W., and Hafner, C. (2011): Statistics of Financial Markets: an Introduction. 3rd ed., Springer Verlag, Heidelberg. ISBN: 978-3-642-16520-7 (599 p)

-      Härdle, W., Hautsch, N. and Overbeck, L. (2009): Applied Quantitative Finance. 2nd extended ed., Springer Verlag, Heidelberg. ISBN 978-3-540-69177-8 (448 p)

-      Hull (2005): Options, Futures, and Other Derivatives. 6th ed., Prentice Hall. ISBN 0-13-149908- 4 (816 p)

-      Härdle, W., Simar, L. (2007): Applied Multivariate Statistical Analysis. 2nd extended ed., Springer Verlag, Heidelberg. ISBN 3-540-72243-4 (456 p)

-      Cizek, P., Härdle, W., Weron, R. (2011): Statistical Tools for Finance and Insurance. 2nd ed., Springer Verlag, Heidelberg. ISBN: 978-3-642-18061-3 (420 p)

   

Exam: Oral exam (70%) and presentation (30%)

 

 

Credits:
6.00
Click here to get more information or to sign up
Thursday,
02:00pm to 05:30pm
at DIW Berlin, Mohrenstr.58
Friday,
09:00am to 12:30pm
at DIW Berlin, Mohrenstr. 58
Click here to get more information or to sign up
Instructor:
Thursday, 10:15am at Kaminzimmer, Boltzmannstr. 20, Freie Universität Berlin
Description:

This course is one of four Ph.D. courses in the Major Area: Public Economics of the BDPEMS.

This course is a reading course yielding 6 ECTS. Each participant has to present in a detailed way an important recent research article and to actively discuss the presentations made by the other participants. Grades depend on presentation and discussion. The course in the winter term 2014-2015 deals with new developments in public economics related to inequality.

The course is on Thursdays 10 – 12 a.m. and takes place in the "Kaminzimmer" in the building of the Economics Department of the Free University (Boltzmannstr. 20, 14195 Berlin).

Date of beginning: October 22, 2015.

Information requests on the course can be addressed to: Giacomo.Corneo@fu-berlin.de.

Credits:
6.00
Click here to get more information or to sign up
Subscribe to Courses