NMAK21008U Demography and Mortality

Volume 2021/2022

MSc Programme in Statistics

  • Demographic modeling
  • Mortality models and forecasting
  • Risk factors
  • Cause specific mortality
  • Quantification of premature mortality
Learning Outcome


  • Basic demographic concepts.
  • Danish and other demographic data sources.
  • The Lee-Carter and other similar models for mortality forecasting.
  • Regression models for prediction of (cause specific or small area) mortality rates.


Skills: The ability to 

  • Implement (simple) models for longevity and demographics in R based on publicly available data sources.
  • Implement (simple) regression models for mortality rates in R.



  • Justify the use of different models in different contexts.
  • Simulating, analyzing, and comparing different mortality models.

The course literature will primarily consist of research papers, which will be made available on Absalon.


Mathematical statistics and probability based on measure theory, such as Mathematical Statistics and Regression or equivalent.

Academic qualifications equivalent to a BSc degree in mathematics, mathematics-economy or actuarial science is recommended.
4 hours of lectures and 3 hours of exercises per week for 7 weeks.
This course will be co-taught for the first four weeks with Pension Systems.
  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 97
  • Theory exercises
  • 21
  • Project work
  • 30
  • Exam
  • 30
  • Total
  • 206

Students receive feedback at the exercise sessions.

7,5 ECTS
Type of assessment
Written assignment, 3 days
Exam registration requirements

To participate in the final exam a compulsory group project must be approved during the course. If it is not approved the first time it can be handed in a second time.

All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners

30 minutes oral examination without preparation time.

No aids allowed.

If the compulsory group project was not approved during the course it must be handed in and approved no later than three weeks before the beginning of the reexamination week.

Criteria for exam assesment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.