SFOK18006U Advanced Health Economics with STATA

Volume 2023/2024
Education

MSc in Public Health Science - elective course

MSc in Health Informatics - elective course

MSc in Global Health - elective course

MSc in Human Biology - elective course

MSc in Health Science - elective course

Content

The focus of the current course is the evaluation problem, i.e., how to identify causal effects from observational data. We elaborate on health economic theories known from the mandatory health economics courses at the public health department and combine these theories with the econometrician’s tool-box to analyze patterns in health surveys typically used in public health and health economics. Students will be introduced to state-of-the-art econometrics methods, including difference-in-differences, instrumental variables and regression discontinuity design. Course time will be split evenly between theory and applications. We will first review a standard textbook treatment of the method, using examples from papers that have employed the technique. Students will be expected to read the assigned papers before the class. After the theoretical introduction, we will use STATA to apply the methods to individual level data. The applications will include a subset of a range of topics heavily discussed in both health economics and epidemiology, such as the topic of health capital, effects of early life conditions on long-run outcomes, topics on health insurance and the demand for medical care, and special populations (mental health, the elderly, the disabled). Thus, while the topics require algebra, a central part of the course will be the practical coding and the of estimation models in STATA.

Learning Outcome

After the course the students are expected to: 

  • Knowledge
    • Explain central health economic concepts related to micro behavior
    • Reflect on the counterfactual problem in health econometric applications
    • Explain and apply econometric techniques (eg. OLS, Instrumental variables, differences in differences) to identify causal relationships
    • Reflect on underlying assumptions for these models
  • Skills
    • Understand and extract relevant information from scientific papers in applied health econometrics 
    • Choose among econometric models for different applications and argue for the choice
    • Formulate testable research questions related to casual relations
    • Assess not only the advantages of different techniques, but also their pitfalls
    • Write clearly about data, econometric analyses and results
    • Interpret empirical results within a health economic framework
    • Code in STAT
    • Carry out micro-econometric analyses on individual level data using STATA software
  • Competencies
    • Independently plan and carry out health economic evaluations using micro data
    • Understand commonly used empirical strategies byhealth economists and compare them to those of epidemiologists    

Book:

Mastering 'Metrics: The path from cause to effect, Joshua D. Angrist and Jörn-Steffen Pischke

Papers:

Assigned readings for each lecture will be posted 2 weeks in advance.

 

Participants are required to complete and pass the course ‘Statistics’ in the Public Health Science MSc.
External participants have to complete and pass an equivalent course prescribed 10 ECTS.
Lectures and exercises.
Student lecture-to-lecture hand-ins (homework) including STATA coding, results and written work. Supervised by the lecturer, the students will go through own STATA codes.
This course is available without pre-approval for students at the MSc in Health Informatics, MSc in Global Health, MSc in Human Biology and MSc in Health Science: It should the noted that it is recommended to have passed statistics course at MSc level as well as knowledge of basic OLS estimation in order to pass the exam.
  • Category
  • Hours
  • Class Instruction
  • 40
  • Preparation
  • 110
  • Exam
  • 125
  • Total
  • 275
Written
Oral
Individual
Collective
Continuous feedback during the course of the semester
Peer feedback (Students give each other feedback)

Feedback takes place during the entire course. Students upload homework and feedback is given from peers as well as the lecturer. There is a poster session where students receive feedback on their project idea. After students work on developing their project, they also present a more advanced version and receive peer feedback during dedicated presentation sessions. Each assignment is curated to help prepare students for the final assignment.

Credit
10 ECTS
Type of assessment
Written assignment
Type of assessment details
The final course paper can be submitted individually or in groups of two students. The format of the assignment is announced during the course. Importantly, students must submit an appendix including the STATA-codes used to produce their results.

Extent of written assignments:
Students are obliged to disclose the number of characters of the submission of written assignments with maximum length. A standard page contains 2,400 characters including spaces. The individual pages can consist of fewer or more than 2,400 characters, but the total number of characters must not exceed 2,400 characters x max. number of pages. On the tasks and projects, which is a maximum length of the number of standard pages of 2,400 characters with spaces, the front page must contain an indication of number of characters in the assignment, excluding table of contents, abstract, tables, figures, bibliography and appendices, but including footnote or endnotes. It is allowed to attach attachments if it is agreed with the supervisor. Appendix, as a student wishes to be included in the overall assessment shall be identified and counted in the number of pages. If assignments exceed the permitted number of pages/characters, this must affect the assessment.

Management of receipts:
For written take-home assignments, the student must be aware that additional appendices, such as audio files, central computer printouts, etc., may be forwarded to the examiner or co-examiner if they require it. The student has an obligation to keep relevant material, until the assignment is assessed.

Group assignments:
Requirements for individualisation of written assignments means that the student must account for the students who have been the main responsibility for which section. This division must follow a meaningful division of the assignment, e.g. in sections and subsections. Up to 1/3 of the assignment may be prepared with collective responsibility, which obviously can include the introduction and conclusion. The division of responsibility is displayed on a separate page, which is included in the task, but does not count towards characters, so that the assignment of roles and responsibilities is a single file that can easily be submitted in digital exam.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
External censorship
Exam period

Please see the exam schedule at KUnet 

Re-exam

3. og sidste eksamensforsøg udbydes i reeksamensperioden: august 2024

Please see the exam schedule at KUnet 

 

Criteria for exam assesment

To achieve the grade 12 the student is expected to: 

  • Knowledge
    • Explain central health economic concepts related to micro behavior
    • Reflect on the counterfactual problem in health econometric applications
    • Explain and apply econometric techniques (eg. OLS, Instrumental variables, differences in differences) to identify causal relationships
    • Reflect on underlying assumptions for these models
  • Skills
    • Understand and extract relevant information from scientific papers in applied health econometrics 
    • Choose among econometric models for different applications and argue for the choice
    • Formulate testable research questions related to casual relations
    • Assess not only the advantages of different techniques, but also their pitfalls
    • Write clearly about data, econometric analyses and results
    • Interpret empirical results within a health economic framework
    • Code in STAT
    • Carry out micro-econometric analyses on individual level data using STATA software
  • Competencies
    • Independently plan and carry out health economic evaluations using micro data
    • Understand commonly used empirical strategies byhealth economists and compare them to those of epidemiologists