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Econometrics for Health will introduce you to the main techniques that are used for empirical analysis in health economics and policy evaluation. The main goal of this module is to teach you how to become both producers and critical consumers of empirical research. This is achieved by focusing on the practical implementation of techniques – rather than the theory behind them – as well as their limitations. The module will provide you with:

1. An understanding of relevant econometric techniques and how to use them.

2. A critical appraisal of the application of different econometric techniques to data and contexts.

3. The ability to test empirically, different economic theories relevant to health economics and policy evaluation.

4. A thorough understanding of the differences between correlation and causation, and how different techniques and data provide information about one or the other.

After taking this module you should be able to:

1. Comprehend, formulate, and communicate complex arguments based on statistical/econometric evidence.

2. Confront theory and empirical evidence.

3. Work with quantitative models and numerical data.

4. Understand the roles of empirical evidence in forming and critically assessing policy.

The module is a core module for the MSc Health Economics and Decision Science. The module is open to anyone with a 2.1 or above in a quantitative first degree.

You will be taught primarily through lectures. Tutorials and problem classes will familiarise you with concepts and techniques through a hands-on approach. Problem sheets will be provided to encourage self-study. Moodle will be used to provide a repository of course materials, and in other ways at the discretion of the lecturer.

Selected reading list:

1. Wooldridge, J. M. (2018). Introductory econometrics: A modern approach. 7th Edition. Cengage Learning.

2. Jones, A. M. (2007). Applied econometrics for health economists: a practical guide. Radcliffe publishing

3. Cameroon A.C. and Trivedi, P.C. (2005). Microeconometrics: methods and applications. Cambridge University Press