On successful completion of the course, students should be able to:
I. Comprehend Evaluation Methods
1. Distinguish between evaluation and monitoring within economic policy contexts.
2. Identify the differences between quantitative and qualitative evaluation methods.
3. Compare ex-ante and ex-post evaluation approaches.
4. Recognize and address counterfactual problems and selection bias in evaluation methods.
II. Use Theories and Evidence in Policy Design
5. Explain the concept of the theory of change and its importance in policy design.
6. Formulate a results chain aligned with specific evaluation questions.
7. Identify appropriate outcomes and performance indicators based on evaluation criteria and data availability.
8. Assess how theories and empirical evidence inform policy design and evaluation methods.
III. Conduct Systematic Reviews and Meta-Analyses
9. Implement rigorous search strategies for conducting systematic literature reviews.
10. Perform systematic reviews and meta-analysis techniques to synthesize evidence from multiple studies.
11. Evaluate the internal and external validity of evidence and its implications for policy evaluation.
IV. Implement Quantitative Methods for Policy Evaluation
12. Design randomized control trials (RCTs) for policy evaluation.
13. Estimate treatment effects and account for spillovers and impact heterogeneity using R coding.
14. Evaluate the ethical considerations involved in random assignment to policy treatments.
15. Implement instrumental variable (IV) methods to address endogeneity concerns in policy evaluation using R coding.
16. Identify and test for the validity of instruments used in IV methods, addressing weak instrument problems.
17. Apply difference-in-difference (DiD) estimators to evaluate policy impacts over time using R coding.
18. Tackle potential violations of the time-invariant heterogeneity assumption in DiD evaluations.
19. Implement regression discontinuity (RD) designs to evaluate policy impacts, focusing on eligibility thresholds using R coding.
20. Conduct robustness checks to ensure the validity of RD designs and eligibility cutoffs.
V. Implement Qualitative and Mixed-Methods for Policy Evaluation
21. Conduct semi-structured interviews and focus groups as methods to collect data for policy evaluation.
22. Conduct content and thematic analysis techniques using open-source software.
23. Implement process tracing to identify causal pathways and establish causal inferences in policy evaluations.
24. Design and execute mixed methods evaluations, integrating quantitative and qualitative data.
25. Implement triangulation and validation techniques to ensure the robustness of mixed methods for economic policy evaluations.
VI. Develop Critical Thinking and Analytical Skills
26. Critically analyze the strengths and limitations of various evaluation methods.
27. Formulate research questions that can be addressed using different evaluation techniques.
28. Synthesize diverse sources of evidence to draw robust policy conclusions.
