Advanced Empirical Health Economics

Course content

The focus of the current course is the evaluation problem, i.e., how to identify causal effects from empirical data. Starting from a health economic framework, in which health is perceived as a human capital stock, we use the econometrician’s tool-box to analyze patterns in health surveys typically used in public health and health economics. During the course we will use the software STATA to analyze data from Survey on Health Aging and Retirement in Europe (SHARE). One application will be the socio-economic gradients in health, which have gained large attention in both epidemiology and economics. Using real data we take the economist’s approach and analyze how health measures relate to household choices and characteristics.

A central focus in the course will be to distinguish correlations from causal effects and the students will be introduced to state-of-the-art difference-in-differences estimators, instrumental variables and regression discontinuity designs.

 

Education

MSc in Public Health Science

Learning outcome
  •  Knowledge (Viden)
    • Explain central health economic concepts related to micro behavior
    • Reflect on the counterfactual problem in health econometric applications
    • Explain linear econometric techniques (eg. OLS, Instrumental variables, differences in differences) to identify causal relationships
    • Reflect on underlying assumptions for these models
  • Skills (Færdigheder)
    • be able to understand and extract relevant information from scientific papers in applied health econometrics 
    • be able to 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
    • be able to write clearly about data, econometric analyses and results
    • interpret empirical results within a health economic framework
    • be able to carry out micro-econometric analyses on health surveys using STATA software
  • Competencies (Kompetencer)
    • Independently plan and carry out health economic evaluations using micro data.
    • Professionally, being able to (cross-disciplinarily) understand empirical strategies of health economists and comparing them to those of epidemiologist.    

Lectures and excercises

Book:

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

Papers (more papers may be added to the list during the course):

Cutler, DM and Lleras-Muney A. Education and Health: Evaluating Theories and Evidence. In RF Schoeni, JS House, G Kaplan and H Pollack (Eds.): Making Americans Healthier: Social and Economics Policy as Health Policy, , New York: Russell Sage Foundation 2008. Published as NBER working paper:
dx.doi.org/10.3386/w12352

Almond, D and Currie, J, ”Killing me softly: The Fetal Origins Hypothesis”, Journal of Economic Perspectives—Volume 25, Number 3—Summer 2011—Pages 153–172
http://dx.doi.org/10.1257/jep.25.3.153

Almond, Douglas. 2006. “Is the 1918 Influenza Pandemic Over? Long-Term Effects of in utero Influenza Exposure in the Post-1940 U.S. Population.” Journal of Political Economy, 114(4): 672–712
Link to paper

Smith, James P., 2009, “The Impact of Childhood Health on Adult Labor Market Outcomes”, The Review of Economics and Statistics, August 2009, 91(3): 478-489
http://www.mitpressjournals.org/doi/pdf/10.1162/rest.91.3.478

Angrist, Joshua D., and Alan B. Krueger. 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments." Journal of Economic Perspectives, 15(4): 69-85.
http://dx.doi.org/10.1257/jep.15.4.69

Angrist,  Joshua D., “Instrumental variables methods in experimental criminological research: what, why and how”, Journal of Experimental Criminology (2006) 2: 23–44

http://dx.doi.org/10.1257/jep.15.4.69

Currie, J. & Madrian, BC. (1999): Health, health insurance and the labor market (eds.):  Handbook of Labor Economics, Vol. 3 , chapter 50, p. 3309-3416  http://dx.doi.org.ep.fjernadgang.kb.dk/10.1016/S1573-4463(99)30041-9
 

 

Statistics at MSc/MA level

Passed statistics course at MSc/MA level.

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 provided they previously have passed statistics course at MSc level.

ECTS
10 ECTS
Type of assessment
Written assignment
Written assignment
Course paper
Marking scale
7-point grading scale
Censorship form
External censorship
Criteria for exam assessment
  •  Knowledge (Viden)
    • Explain central health economic concepts related to micro behavior
    • Reflect on the counterfactual problem in health econometric applications
    • Explain linear econometric techniques (eg. OLS, Instrumental variables, differences in differences) to identify causal relationships
    • Reflect on underlying assumptions for these models
  •     Skills (færdigheder)
    • be able to understand and extract relevant information from scientific papers in applied health econometrics 
    • be able to 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
    • be able to write clearly about data, econometric analyses and results
    • interpret empirical results within a health economic framework
    • be able to carry out micro-econometric analyses on health surveys using STATA software
  • Competencies (kompetencer)
    • Independently plan and carry out health economic evaluations using micro data.
  • Category
  • Hours
  • Class Instruction
  • 30
  • Preparation
  • 120
  • Exam
  • 125
  • English
  • 275