Introduction to Impact Evaluation


14/11/2023 - 15/11/2023

Organised by:

NCRM, University of Southampton


Dr Angus Holford and Dr Magda Borkowska


Entry (no or almost no prior knowledge)


Jacqui Thorp
Training and Capacity Building Coordinator, National Centre for Research Methods, University of Southampton

video conference logo

Venue: Online


This online course will introduce you to various empirical, quantitative methods that can be used to estimate the impact of a specific policy intervention. These methods can be referred to as “programme evaluation”, “impact assessment”, “causal estimation” or “impact evaluation”. The course assumes knowledge of basic algebra and statistical concepts (mean, median, correlation, expected value, statistical significance and confidence intervals). It does not teach participants how to implement any of these methods using statistical software.

The course covers:

· The evaluation problem, and how randomized experiments solve the problem

· An intuitive explanation of the advantages and disadvantages of matching, including propensity score matching; quasi-experimental methods such as instrumental variables; and difference-in-differences

· It does not teach participants how to implement any of these methods using statistical software

By the end of the course participants will:

· Be able to think about evaluation in terms of “counterfactuals” and “informative contrasts” (or comparisons)

· Be able to explain intuitively the conditions under which propensity score matching, instrumental variables and difference-in-differences are likely to produce unbiased estimates of the impact of an intervention

· Be able to assess whether an actual or proposed design for an impact evaluation is likely to give reliable results, given the nature of the policy under consideration

This course is aimed at Government researchers and analysts, third sector researchers, PhD students and junior researchers interested in quantitative methods for impact evaluation.



Day 1:

10:00 Welcome and Introductions

10:05 Session 1: The Evaluation Problem

c. 10:50-11:10: Group exercise

11:30 Tea/Coffee Break

11:50 Session 2: Matching and Regression as a Strategy to Estimate Causal Impacts

c. 11:35-12:55: Group exercise

13:20 Introduction to (brief!) individual overnight exercise: Case study using matching [TBC]

13:30 Close


Day 2:

09:45 Discussion from overnight exercise

10:00 Session 3: Quasi-Experimental Methods: The regression Discontinuity Design and Instrumental Variables

c. 11:00 – 11:30: Group exercise

12:00 Tea/Coffee Break

12:15 Session 4: The Differences-in-Differences approach

c. 12:45 – 13:05: Group exercise

13:20 Introduction to takeaway exercise; Q&A; Final remarks

13:30 Evaluations and Close



The fee per teaching day is:• £30 per day for registered students• £60 per day for staff at academic institutions, Research Councils researchers, public sector staff, staff at registered charity organisations and recognised research institutions. • £100 per day for all other participantsIn the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. No refunds are available after this date.If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of the cancellation of a course.

Website and registration:


South East


Cross-Sectional Research, Longitudinal Research , Quasi-Experimental Research, Evaluation Research, Regression Methods, Quantitative Approaches (other), Explanatory Research and Causal Analysis, Experimental research

Related publications and presentations:

Cross-Sectional Research
Longitudinal Research
Quasi-Experimental Research
Evaluation Research
Regression Methods
Quantitative Approaches (other)

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