Causal Inference for Policy Evaluation
Causal inference has become increasingly important for evaluating the impact of policy interventions in a wide range of social, cultural, environmental, economic and political contexts. This micro-credential introduces key causal inference methods with examples drawn from different disciplines. Participants learn fundamental concepts and principles that underpin causal inference, various causal inference methods under different policy intervention contexts, and transferrable causal modelling tools using R and R studio. After the course you will be able to apply appropriate causal inference tools to real policy analyses and impact valuations.
Upon successful completion of this micro-credential, you'll receive:
- Six PD Points
- A Certificate of Achievement
- A UWA Plus Professional Development Transcript, listing all successfully completed micro-credentials
- Delivery mode
- Start dates
- 24 July 2023
- Applications close
- 17 July 2023
- 13 weeks
- Total effort - 150 hours: each week 1.5 hours lectures, 1 hour guided computer practical, 10 hours self-directed learning and
- Academic lead
- Associate Professor Chunbo Ma
- $990 inc. GST
- Critical information summary
- ECONM501 Causal Inference for Policy Evaluation [PDF 244KB]
Demonstrate understanding and proper use of counterfactuals to define causal effects
Be able to construct causal diagrams to identify potential bias
Demonstrate understanding of key assumptions for different causal inference methods
Be able to implement various causal inference methods using R
Be able to appropriately interpret and effectively communicate results of casual analyses
Be able to apply to real cases of policy analysis/impact evaluation
Why study this course?
Causal inference has become increasingly important for evaluating the impact of policy interventions in a wide range of social, cultural, environmental, economic and political contexts.
Who should study this course?
Policy analysts, consultants, social scientists and researchers that have interest in learning and using causal inference methods.
Recommended prior knowledge
Introductory econometrics or statistics
What's next after this course?
Individual support from Professor Ma may be available for an applied causal inference project that a course participant works on. Support can include advice on research design, data preparation, results interpretation and feedback on draft report. Specific forms of consultation after the course regarding an applied project may be discussed with unit coordinator.
Students who complete this micro-credential can apply for credit if they subsequently apply for a Master of Agricultural Economics or a Master of Environmental Economics, or another award course.