The course aimed to address an important prerequisite for incorporating impact evaluation (IE) into programmer design: a theoretical and understanding of IE approaches to enable selection of appropriate methodologies, coupled with careful appraisal of the resulting evidence. the course introduced participants to current quantitative as well as qualitative evaluation techniques for impact evaluation and gave them an insight into the critical understanding of the roles they can play in the design and assessment of public policy and development intervention. The group enthusiastically tackled and difficulties of learning STATA, NVIVO and the intricacies of evaluation research design and econometric techniques, all bolstered by the support of the experienced teaching team.
Result framework
M&E project indicators
Logical framework
Performance evaluation
Defining impact evaluation
Deciding whether to evaluate
Attribution in impact evaluation
Contribution Vs attribution
Types of evaluations
Theories of change
Evaluation hypothesis
Impact evaluation indicators
Causal reference
Comparison groups and counterfactuals
Estimating counterfactual in impact evaluation
Impact evaluation when a comparison and baseline data are not available
Experimental design randomized control trials
Quasi experimental design
Regression discontinuity
Difference in matching Non-experimental designs
Sampling technique in impact evaluation
Sample size calculation
Sampling weight
Statistical power
Constructing valid comparison group
Setting the counterfactual
Statistical design of randomized
Impacts of program placement
Impact of program participation
Capturing both program placement and participation
Measuring spillover effects
Introduction to PSM
Application of PSM in impact evaluation
Constructing propensity scores
Matching analysis (nearest –neighbor, stratification, radius, kernel)
Common support
Doubly robust estimation
What is DID?
Application of DID in impact evaluation
Estimating DID estimator: single DID with covariates, quantile DID
DID for cross selection data
Delaying test
Diff –in diff with propensity score matching
Most significant change
Outcome mapping
Outcome harvesting
Appreciative inquiry
Impact evaluation plan
Impact evaluation reports: baseline report, impact evaluation reports
Case studies
Conduct a rigorous impact evaluation of a project
Learn and practice econometric techniques for impact evaluation
Carry out impact data analysis using propensity matching and difference _in_ difference
Understand IE designs: randomized, quasi and mon- experimental
Learn about evaluation problem: Attribution, selection and placement biases
Learn about theories and practices of impact evaluation
Conduct sampling and power calculation
Report and disseminate impact evaluation findings
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