Course syllabus

Statistics, Econometrics, Second Cycle, 7.5 credits

Course code: ST422A Credits: 7.5
Main field of study: Statistics Progression: A1F
    Last revised: 12/03/2020
Education cycle: Second cycle Approved by: Head of school
Established: 01/11/2019 Reading list approved: 12/03/2020
Valid from: Autumn semester 2020 Revision: 1

Aims and objectives

General aims for second cycle education

Second-cycle courses and study programmes shall involve the acquisition of specialist knowledge, competence and skills in relation to first-cycle courses and study programmes, and in addition to the requirements for first-cycle courses and study programmes shall

  • further develop the ability of students to integrate and make autonomous use of their knowledge
  • develop the students' ability to deal with complex phenomena, issues and situations, and
  • develop the students' potential for professional activities that demand considerable autonomy, or for research and development work.

(Higher Education Act, Chapter 1, Section 9)

Course objectives

The general goal of the course is to give deepened knowledge of regression models that are useful in economics.

After completion of the course, the student will have

  • Deeper knowledge of basic concepts in regression analysis
  • Deeper knowledge of econometric theory and the basic tools needed to carry out empirical economic studies and analysis
  • The ability to critically evaluate different regression models and to choose an appropriate modelling approach
  • The ability to communicate modelling issues and results.

Main content of the course

1) Specification and Computation in the context of Classical Linear Regression Model
2) Statistical Inference in Finite Samples in the context of Classical Linear Regression Model
3) After a review of the linear model, we will develop the asymptotic distribution theory necessary for analysis of generalized linear and nonlinear models
4) We will include also elements of the following estimation methods:
- Instrumental variables estimation
- Maximum likelihood estimation
- Generalized method of moments (GMM) estimation and two step estimation methods.

Teaching methods

Lectures and computer labs.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Examination methods

Written Examination, 6 credits (Code: A001)

Computer Labs, 1.5 credits (Code: A002)


For students with a documented disability, the university may approve applications for adapted or other forms of examinations.

For further information, see the university's local examination regulations (in Swedish).

Grades

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may prescribe which grading system shall apply. The grade is to be determined by a teacher specifically appointed by the university (an examiner).

In accordance with university regulations regarding grading systems for first and second-cycle courses (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades shall be used: Fail (U), Pass (G) or Pass with Distinction (VG). For courses that are included in an international Master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the grading scale of A-F shall be used. The vice-chancellor, or a person appointed by the vice-chancellor, may decide on exceptions from this provision for a specific course, if there are special grounds.

Grades used on course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Written Examination
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Computer Labs
Grades used are Fail (U) or Pass (G).

For further information, see the university's local examination regulations (in Swedish).

Comments on grades

To obtain a passing grade for the course as a whole, a passing grade is required on all course components. The final grade for the entire course is a function of the grades of the course components. Detailed information on the requirements for different grade levels is given at the course start.

Specific entry requirements

First-cycle courses of 90 credits in statistics, including an independent project of 15 credits, alternatively 30 credits are for studies in statistics and 60 credits for mathematics, as well as the course Statistics, Statistical Theory, second cycle, 7.5 credits, or first-cycle courses of 90 credits in economics, including an independent project of 15 credits as well as courses of 60 credits in statistics and the course Statistics, Statistical Theory, second cycle, 7.5 credits. The applicant must also have qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations (in Swedish).

Transfer of credits for previous studies

Students who have previously completed higher education or other activities are, in accordance with the Higher Education Ordinance, entitled to have these credited towards the current programme, providing that the previous studies or activities meet certain criteria.

For further information, see the university's local credit transfer regulations (in Swedish).

Reading list and other teaching materials

Required Reading

William H. Greene 2012/ 7. ed.
Econometric Analysis: International Edition
Boston ;London :Pearson, ISBN/ISSN: 978-0-273-75356-8, 1228 pages