ECON5103 – Advanced Econometrics - Panel Data
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.
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
- 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.
Formal prerequisite knowledge
Recommended previous knowledge
ECON4130 – Statistics 2, ECON4160 – Econometrics - Modeling and Systems Estimation. Basic knowledge of matrix algebra.
- 3 credits overlap with ECON5102 – Advanced Econometrics - Microeconometrics (discontinued)
- 3 credits overlap with ECON9102
- 3 credits overlap with ECON5101 – Advanced Econometrics - Time series (discontinued)
- 3 credits overlap with ECON9101
- 10 credits overlap with ECON5120- Panel Data Econometrics
- 10 credits overlap with ECON9120
*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.
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
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.