This course is discontinued

ECON5103 - Advanced Econometrics - Panel Data

Schedule, syllabus and examination date

Choose semester

Course content

Panel data (combined cross section/time series data) is a data type which has received gradually increasing interest for empirical analysis in economics. Following a short introductory part, that reviews intermediate level econometrics, the course deals primarily with econometric modeling, estimation, and testing of relationships for panel data in the presence of individual heterogeneity. Selected topics in dynamic panel data analysis will also be discussed.

Most attention is given to balanced panel data (i.e., data sets with equally long time series for all cross-sectional units), but unbalanced data (which are getting increasing importance) are also discussed.

The topics include:

  • regression analysis with individual-specific (and to some extent time-specific) heterogeneity (fixed and random effects) models with random coefficients
  • measurement error models for panel data
  • dynamic models for panel data
  • selected topics in discrete choice analysis with panel data
  • and multi-equation models for panel data. Applications will be discussed.

Learning outcome

You should know

  • basic econometric terminology and estimation and test principles for efficient inference with panel data
  • the potential of panel data to deal with estimation biases following from heterogeneity in individual characteristics and individual behaviour

You should be able to

  • formulate static and dynamic econometric models for panel data on the basis of economic theories and to translate models for cross-section data and for time-series data into panel data models.
  • recognise why panel data is a richer data source than pure cross-section data, pure time-series data and repeated cross sections.
  • estimate parameters in panel data models from actual observations and testing actual hypotheses by using suitable software

You should

  • be able to read and understand project reports and journal articles that make use of the concepts and methods that are introduced in the course
  • be able to make use of the course content in your own academic work, for example in analyses that are part of the master’s or PhD thesis


Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

Students enrolled in other Master's Degree Programmes can, on application, be admitted to the course if this is cleared by their own study programme.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.

The subject is open for both Norwegian and international students.
Students who are admitted to study programmes or individual courses at UiO must each semester register which courses and exams they wish to sign up for in StudentWeb.
International applicants, if you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures for international applicants.

Overlapping courses

*The 9000-course code is used for courses on the PhD level


Access to teaching

A student who has completed compulsory instruction and coursework and has had these approved, is not entitled to repeat that instruction and coursework. A student who has been admitted to a course, but who has not completed compulsory instruction and coursework or had these approved, is entitled to repeat that instruction and coursework, depending on available capacity.


The students will be evaluated on the basis of a portfolio assessment.

Grading scale

Students on master's level are awarded on a descending scale using alphabetic grades from A to E for passes and F for fail.

Students who would like to have the course approved as a part of our PhD program, must obtain the grade C or better. Students on PhD level are awarded either a passing or failing grade. The pass/fail scale is applied as a separate scale with only two possible results.

Explanations and appeals

It is recommended to request an explanation of your grade before you decide to appeal.



The deadline to request an explanation is one week after the grade is published. For oral and practical examinations, the deadline is immediately after you have received your grade.

The explanation should normally be given within two weeks after you have asked for it. The examiner decides whether the explanation is to be given in writing or verbally.

Resit an examination

The Department of Economics has passed following resolution for ECON-courses: It will no longer be possible for candidates to register for an exam in a lower level course after having passed exams in intermediate and advanced level courses in the same subject area (also where there are no pre-requisites that apply to the intermediate course). Further information can be found here.

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.


The course is subject to continuous evaluation. At regular intervals we also ask students to participate in a more comprehensive evaluation.


This course prepares for the Ph.D.program. It provides a head start for last-year master students who intend to continue with a Ph.D.

Facts about this course






Spring 2013


Spring 2013

Teaching language