![]() ![]() As long as these are randomly distributed, we usually need not be overly concerned. So it is with survey data, which is produced by humans and will contain errors. But as these occurrences become regular we might begin to ask ourselves whether something is systematically wrong. Some stains are unavoidable – we all spill wine/sauce/coffee on ourselves from time to time, which is mildly frustrating but easily discarded as a fact of life, a random occurrence. Raw data fresh from the field is a bit like dirty laundry: it needs cleaning. Impact evaluation needs data, and often research teams collect this from scratch. This post was co-authored by Sacha Dray, Felipe Dunsch, and Marcus Holmlund.
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