Universität Wien

390049 DK PhD-M: Applying Advanced Regression Techniques (2015W)

Continuous assessment of course work

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 15 participants
Language: English

Lecturers

Classes

Currently no class schedule is known.

Information

Aims, contents and method of the course

This course seeks to complement Multivariate Business Statistics for PhD students in Management in three distinct ways.
1. It will introduce to the analysis of panel data
2. It will introduce to programming with one of the most powerful software tools in econometrics, namely STATA.
Most importantly, however,
3. the course will offer you an additional opportunity to become ever more familiar with the hands on application of both basic and more advanced regression techniques for your own research purposes.
There will be some overlap with other empirical classes you may have attended before, however, we will keep it to a minimum.
Finally, note that the focus of the course is solid application. Hence, neither our theory sessions nor any of the exercises will be centred on mathematical proofs but rather on a proper understanding of the logic, options, and caveats of the methods we discuss. As such, it complements more theory-laden classes offered by colleagues in adjacent areas (e.g. statistics, econometrics).

Assessment and permitted materials

Course assessment
Your final grade will be composed of the following elements:
20% class participation
30% presentation of a research article in class
50% final data-based project

Minimum requirements and assessment criteria

Basically, you may benefit from the class and you should feel welcome to join if you

(1) are enrolled as a PhD student in Management at the University of Vienna with an interest in doing empirical research,
(2) have successfully attended the Multivariate Business Statistics class in the PhD Management program, and
(3) have successfully attended at least one other econometrics class at PhD level in a management program or at Master’s level in statistics or econometrics.

These formal requirements are put in place to ensure that we can move to interesting applications rather sooner than later.

That said, experience shows that most of you will still benefit from a brief revision of the basics for a variety of reasons. We will therefore be starting from a very basic level to make sure that everybody is on board. This being said please note that we will be moving fast.

In order to minimize the overlap with the core courses on statistical methods, we will be revisiting basic econometrics only very briefly before we move on to more advanced techniques.

Examination topics

Teaching format
How can we reach the course goals? After some introductory sessions (during which we will revisit some important insights from your earlier courses) the focus will be on getting you to work on applied problems yourself. Essentially, the course will follow a sandwich format where front-end theory sessions, alternate with student presentations on selected research articles, and computer sessions during which we work on simulated and real data.

Reading list

Readings basic references and research articles
The basic reference we will use throughout the course is Introductory Econometrics by J. Wooldridge, Thomson, 2003. Whenever necessary, we will draw from other textbooks. Likely, the most relevant ones for us will be Econometric Analysis of Cross Sectional and Panel Data by J. Wooldridge, MIT Press, 2002, and Limited-Dependent and Qualitative Variables in Econometrics, by G. Maddala, Cambridge University Press, 1999.
Additionally, we will be drawing from a series of research articles that apply the methods discussed throughout the course. I will provide you with a reading list shortly before the course commences in January 2007. I expect the articles will be drawn from journals such as Management Science, Strategic Management Journal, Research Policy, and other potential target outlets for your own research.

Association in the course directory

Last modified: Mo 07.09.2020 15:46