Course Overview

The science of impact evaluation is a rigorous field that requires thorough knowledge of the area of work, simple to complex study designs, as well as knowledge of advanced statistical methods for causal inference. Many programme funders and managers want to know whether their programmes have produced measurable impact. They want to be able to measure that impact and express it in numbers.

The key focus of impact evaluation is attribution and causality – that the programme is indeed responsible for the observed changes reported. To achieve this, a major challenge is the possibility of selecting an “untouched” comparison group and using the appropriate statistical methods for inference.

Course Objectives

• Introduction to impact evaluation
• The need for and culture of impact evaluation
• Programme indicators
• Introduction to programmes and logic models
• What really is impact – efficiency versus effectiveness
• Counterfactuals – looking for a suitable control
• Experimental and quasi-experimental study designs
• Research ethics in IE and design implications
• Causality
• Attribution and research validity in impact evaluation
• Potential biases in impact evaluation
• Design and statistical methods for controlling for confounders
• Statistical techniques for causal inference