Covid-19 factor

Accounting for Covid-19 as a confounding factor during impact evaluations

We know from numerous studies that exogenous factors, such as economic crises, natural disasters or rising conflicts can superimpose societal developments that are subject to development interventions – which again are subject to evaluations. As evaluators we are familiar with such challenges and know how to deal with them adequately. However, we also know that things are getting trickier when the magnitude of influence of a confounding factor exceeds the expected size of an intervention’s impact. This is even more true, if there is more than one of such nasty factors. So, what to do if technically speaking the ‘signal-to-noise ratio’ between our subject of investigation and the unwanted interference is becoming too small for such a corrective maneuver? How can we attribute an observable change to an intervention if this change is influenced significantly more by something else than the intervention under investigation itself? How would you evaluate an intervention aiming at improving the resilience of vulnerable groups at the very moment their resilience is severely tested by a collapsing regional economy?