Studying at York
Health Economics for Research - ECO00081M
Module summary
This module aims to provide research students with the applied microeconomic and microeconometric skills necessary to understand and undertake research in health economics.
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 2 2023-24 |
Module aims
This module aims to provide research students with the applied microeconomic and microeconometric skills necessary to understand and undertake research in health economics in preparation for writing their thesis.The module covers a selection of topics in microeconomics and microeconometrics applied to research developments in health economics with a strong emphasis on methods (either mathematical derivation of a microeconomic model or econometric methods with a focus on causality).
Module learning outcomes
Upon completing this module successfully, a student should be able to have a working knowledge of microeconomic models and of microeconometric methods and understand how to apply them in the health economics context and within their research (for example by developing a theoretical model on a new topic, and identifying the relevant data and econometric methods to test a specific hypothesis).
Indicative assessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 67 |
| Online Exam -less than 24hrs (Centrally scheduled) | 33 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 67 |
| Online Exam -less than 24hrs (Centrally scheduled) | 33 |
Module feedback
Feedback will be in line with University policy
Indicative reading
Empirical methods:
An overview of some key ideas for effective data visualization and how they can be applied to econometric analysis of health care costs and outcomes is given by:
Jones, A.M., “Data visualization and health econometrics”, Foundations and Trends in Econometrics, 9, 1-78, 2017. DOI: 10.1561/0800000033.
Conventional approaches to econometric modelling for health care costs are reviewed in:
Jones, A.M., “Models for health care”, Oxford Handbook of Economic Forecasting, Hendry, D. and Clements, M. (eds.), Oxford: Oxford University Press, 625-654, 2011.
An overview of machine learning for economists is provided by:
Athey, S. and Imbens, G.W., Machine learning methods that economists should know, Annual Review of Economics, 11: 685-725, 2019.
https://www.annualreviews.org/doi/pdf/10.1146/annurev-economics-080217-053433
An overview of using machine learning for policy evaluation is provided by:
Kreif, N. and DiazOrdaz, K., Machine Learning in Policy Evaluation: New Tools for Causal Inference, Oxford Online Research Encyclopedia, OUP, 2020.
https://doi.org/10.1093/acrefore/9780190625979.013.256
An introductory overview of the econometrics of policy evaluation in health economics can be found in (see link to pdf above):
Jones, A.M. and Rice, N. "Econometric evaluation of health policies" in Oxford Handbook of Health Economics, Glied, S. and Smith, P.C. (eds), Oxford: Oxford University Press, 2011.
Background reading that covers more established methods for panel data analysis in health economics is provided by:
Jones, A.M., “Panel data methods and applications to health economics”, Palgrave Handbook of Econometrics. Volume 2, Mills, T.C. and Patterson, K. (eds.), London: Palgrave MacMillan, 557-631, 2009.