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Advanced Panel Data Econometrics with applications in R
Provider: Faculty of Science

Activity no.: 5246-19-03-31 
Enrollment deadline: 28/04/2019
Date and time29.04.2019, at: 08:30 - 03.05.2019, at: 16:30
Regular seats40
Course fee1,000.00 kr.
LecturersArne Henningsen
ECTS credits5.00
Contact personCharlotte Bukdahl Jacobsen    E-mail address: cja@ifro.ku.dk
Enrolment Handling/Course OrganiserArne Henningsen    E-mail address: arne@ifro.ku.dk
Written languageEnglish
Teaching languageEnglish
Course workload
Course workload categoryHours
Lectures25.00
Exercise(s)10.00
Preparation / Self-Study25.00
Evaluation1.00
Report writing70.00
Sum131.00
Aim and content
The use of panel data -- also known as longitudinal data -- in scientific and applied empirical analyses has rapidly increased in past decades. Methods for their analysis have been developed and extended accordingly. This course will briefly present traditional panel data estimators and then focus on several `modern' panel data estimators such as panel time series models and dynamic panel data models. The course will also teach how to use statistical tests to test panel data specifications under different assumptions and how these tests can be used to identify the most appropriate panel data estimators for specific empirical applications. Besides lectures on the theory and application of various panel data models, the course will have practical exercises, where the students will learn to use the statistical software R to explore and re-arrange panel data sets, prepare them for further analyses, estimate various traditional and modern panel data models, and apply a number of statistical specification tests. The course will be largely based on the recently published textbook “Panel Data Econometrics with R” (Croissant, Y. & Millo, G., 2018, Wiley)", and the forthcoming chapter “Analysis of Panel Data using R” (Henningsen, A. & Henningsen, G. in: Panel Data Econometrics Volume 1: Theory, edited by Tsionas, M., forthcoming, Elsevier).

Learning outcome
After having completed the course, the course participants will know the theory of state-of-the-art panel data methods and statistical tests for testing panel data specifications and they can apply these methods and tests to panel data, e.g., using the statistical software R.

Teaching and learning methods
The theory will be taught mostly through (interactive) lectures, dialogue teaching, and self-study. The practice will be taught mostly through exercises, group work, self-study, and the exam (i.e. estimating panel data models, conducting statistical tests, and writing a short report about this, see following section).

Preparation and self-study: It is expected that the participants prepare for the course by reading the course material that will be sent to the students about 4 weeks before the course starts. It is also expected that the participants recapitulate the contents of the course by reviewing the lecture notes and the other course material in order to appropriately conduct the analyses and write their report for the exam.

Exam form and criteria for assessment: The exam consists of a brief report about an empirical panel data analysis (max. 6 pages) that each participant has to write and send to the course organiser no later than 2 months after the end of the course. The participants need to find a suitable research question and panel data set for their analyses themselves. It is encouraged that the research question and data set are parts of the participants’ PhD projects. In their reports, the participants must state their research question, describe the panel data set, model specifications and statistical tests that they use in their analysis, present their results, and discuss the appropriateness of their chosen model specification, e.g., based on the results of statistical tests. A participant passes the exam if his/her report indicates that he/she has obtained the intended learning outcome (see section “learning outcome”).

Lecturers
Professor Yves Croissant, CEMOI, Faculty of Law and Economics, University of La Réunion, France
Senior Economist Giovanni Millo, Group Insurance Research, Assicurazioni Generali S.p.A., Trieste, Italy
Senior Researcher Geraldine Henningsen, Department of Management Engineering, Technical University of Denmark, Denmark
Associate Professor Arne Henningsen, Department of Food and Economic Resources, University of Copenhagen, Denmark

Teaching will take place Monday to Thursday 8:30-12:00 and13:00-17:00 as well as Friday 8:30-12:00 and 13:00-16:30.

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