Chair of Marketing and Consumer Behavior

Panel Data Analysis in Marketing

Lecturer:
Dr. Ossama Elshiewy

Target group:

  • Master students
    (MDM, UF, FRS, Wi-Inf, Wi-Päd, Steuerlehre, Wirtschafts & Sozialgeschichte, International Economics, Development Economics, Angewandte Statistik)

  • All PhD students from the Faculty of Economic Sciences interested in panel data analysis with marketing applications

Learning goals:
  • Panel data refers to observations from different individuals or units (consumers, stores, products, etc.) over several time periods (days, weeks, months, etc.).

  • After successful attendance the students will understand the methodological principles of panel data modeling (especially in the context of consumer behavior and marketing-mix models).

  • Further, they will be able to conduct own panel data analyses using the statistical programming language R. (Previous knowledge in R is not required! The course will focus more on panel data analysis and less on programming, therefore the R-Code will always be uploaded in advance).

Course structure:
The course consists of two parts:
1. Attending a lecture (with integrated exercises)
2. Writing a term paper.

Important note: The lecture will be held in English, but the term paper can be written in either English or German.

Lecture content:
- Introduction to R
- Refreshment in Regression Analysis
- Fixed Effects Models
- Random Effects Models
- GMM Panel Models
- Linear Mixed-Effects Models
- Hierarchical Bayesian Linear Models

Term paper:
The term paper will contain a self-conducted empirical project.
Students will be provided with topics and empirical data, but are also welcome to analyze own projects.
Students are advised to use the statistical programming language R (i.e., the code from the lecture), but can be allowed to use different statistics software in exceptional cases.

Literature:
Hanssens et al. (2003). "Market Response Models: Econometric and Time Series Analysis". Kluwer.
Baltagi (2013). "Econometric Analysis of Panel Data". 5th Edition. Wiley.
Galecki et al. (2013). "Linear Mixed-Effects Models Using R". Springer.
Rossi et al. (2005). "Bayesian Statistics and Marketing". Wiley.

Time and place:
Lecture (with integrated exercises)

Every Wednesday
(First date: April 18, 2018)
Time: 16:15 - 17:45 h
Place: MZG 7.153 (Blauer Turm - WiSoRZ)

Examination:
Term paper (~ 6000 words)
Credits: 6 ECTS
Deadline for submission: September 2018

Theoretical, methodological and empirical elaboration of a selected topic in panel data analysis (preferably with focus on consumer behavior and/or marketing-mix modeling).

Helpful prerequisites:
Basics in
- Hypothesis testing
- Regression analysis