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Why are we obsessed with Impact evaluation?

Why are we obsessed with impact evaluation (IE)? To address this question Elliot Stern will discuss contemporary thinking on IE, and how IE has evolved in recent years. He will also explore what IE could offer to the sustainable development goals ‘agenda’, as an example of the challenges evaluating any complex, unpredictable and interconnected system.

United Kingdom
14th June, 2016
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Event State/Province: 
London City
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In the last decade the evaluation debate has been dominated by the big what works question which addresses impact and effectiveness criteria. Are these the only purposes of evaluation? Surely IE also has to address key evaluation concepts/purposes like stakeholders’ engagement, relevance and importance of evaluation criteria. Should we take a step back and ask ourselves whose values we use to determine what works?  Or should we ask how policy making would have to change if we are ever to move beyond the way IE is currently understood.

Bio: Elliot Stern is Emeritus Professor of Evaluation Research at Lancaster University, Editor of the journal Evaluation and past President of both the UK and European Evaluation Societies. In 2012 he led the team commissioned by DFID on the need for ‘a broader range of impact evaluation designs and methods’, ideas taken further in 2015 in a report on IE for commissioners and managers of evaluation published by BOND.

More details are in the form attached. The event will be at the International Institute for Environment and Development (IIED). Address: London, 80-86 Gray’s Inn Road, WC1X 8NH. Closest tube: Chancery Lane.

Further Reading

View the BetterEvaluation Theme Page for Impact Evaluation with resources and advice.

Impact evaluationImpact Evaluation

An impact evaluation provides information about the impacts produced by an intervention - positive and negative, intended and unintended, direct and indirect. This means that an impact evaluation must establish what has been the cause of observed changes (in this case ‘impacts’) referred to as causal attribution (also referred to as causal inference). Read more.