Syllabus for Econometrics

Ekonometri

A revised version of the syllabus is available.

Syllabus

  • 7.5 credits
  • Course code: 2ST092
  • Education cycle: First cycle
  • Main field(s) of study and in-depth level: Statistics G1F
  • Grading system: Fail (U), Pass (G), Pass with distinction (VG)
  • Established: 2007-05-31
  • Established by: The Faculty Board of Social Sciences
  • Revised: 2010-12-17
  • Revised by: The Department Board
  • Applies from: Spring 2011
  • Entry requirements:

    30 credits in statistics

  • Responsible department: Department of Statistics

Learning outcomes

A student that has completed the course should

- have deeper knowledge of statistical theory and methodology particularly in economical and social science applications

- be able to estimate models for cross-sectional data and time series data

be able to interpret the results of an implemented model adaptation

- be aware of limitations and common sources of errors in the analysis

- have ability to present results in oral and written form.

Content

General about econometric models and their application within economic planning. Linear-regression models with one or several explanatory variables. Nonlinear models. Estimation and hypothesis testing. Gauss-Markovs Nonlinear theorem. Heteroscedasticity and autocorrelation. Multicollinearity. Measurement errors. Instrumental variables. Dummy variables. Models with a dichotomous variable as dependent variable: LPM - and the Logit-model. Simultaneous equation models: the simultanity bias, identification. The two-stage least square method.

Instruction

Lectures

Assessment

The examination comprises a written test at the end of the course and compulsory assignments, (laboratory sessions). Three grades are awarded for the course: not passed, passed, and passed with distinction.

Reading list

Reading list

Applies from: Autumn 2017

Some titles may be available electronically through the University library.

  • Asteriou, Dimitrios; Hall, S. G. Applied econometrics

    3rd Edition: London: Palgrave Macmillan, 2016.

    Find in the library

Reading list revisions

Last modified: 2022-04-26