The aim of the seminar is to develop students’ skills in empirical data analysis. Particularly, this involves the improvement of their data-analytic thinking as well as training and hands-on experience in applying a statistical software. Application is open to students from the M.Sc. Business Administration, MMT, and Media Informatics programs.
This course offers an introduction to data analytics. Data analytics is crucial in helping firms to solve today’s business challenges. Participants of this seminar will be exposed to tools and methods that support data-driven decision making. Besides developing participants’ skills in empirical data analysis, this course prepares students for writing an empirical Master’s thesis.
While many students have theoretical knowledge of econometric concepts, they often lack experience in applying those concepts to empirical problems before commencing their Master’s thesis. This seminar is intended to step into this gap. Each student (or student team) will be assigned a recent research paper in the field of electronic commerce, which was published in an international journal. Students will replicate the main empirical results of the respective paper and (if possible) provide and discuss additional analyses beyond the findings of the original paper.
The seminar takes an applied econometrics approach with a focus on valuable econometric methods for (causal) inference in economics and marketing. The seminar’s emphasis is on applications and interpretation of results. The seminar involves participation in two econometrics workshops, writing a seminar paper based on the replication project, and a final presentation of the results.
The aim of the seminar is to develop students’ skills in empirical data analysis. Particularly, this involves the improvement of their data-analytic thinking as well as training and hands-on experience in applying a statistical software.
The following papers are mere examples and not the basis for the seminar projects. We encourage you to take a look at the papers and the available supplementary materials to familiarize yourself with the task.
Please send us your current CV, a transcript of records (full LSF transcript including ALL courses – failed and passed), and a short statement why you want to participate in this seminar. Please send your application to the secretary's office.
Please note: the deadline for applications has been extended to April 10, 2024 (12 noon).
Please note: Participation in the kick-off session means your registration is binding. For further information see also the examination board’s regulations
| Date and Time | Activity | Place |
|---|---|---|
| April 10 12 noon | Deadline for Applications | by email to ecm@som.lmu.de |
| April 15 11 am - 12 noon | Kick-Off Session | Ludwigstr. 28, Front Building, Room 211b |
| April 22 10 am - 3 pm | Workshop "Introduction to Data Analytics" part 1/2 | IuK Pool: Ludwigstr. 28, Front Building, Room 207 |
| April 22 by midnight | Deadline for submission of project preferences (please send 3 preferences in descending order) | by e-mail to N.Gallitz@lmu.de |
| April 23 10 am - 3 pm | Workshop “Introduction to Data Analytics” part 2/2 and announcement of project assignments | IuK Pool: Ludwigstr. 28, Front Building, Room 207 |
| June 26 12 noon | Deadline for submission of seminar papers (please send a digital copy of your report (PDF) as well as your data and code to your advisor and CC to our secretary) | by e-mail to advisor and ecm@som.lmu.de |
| July 3 12 noon | Deadline for submission of final presentations | by e-mail to N.Gallitz@lmu.de |
| July 4 from 9 am | Final presentations | Ludwigstr. 28, Front Building, Room 211b |
