Background:This article describes eight flaws that occur in impact evaluations.Method:The eight flaws are grouped into four categories on how they affect impact estimates: statistical imprecision; biases; failure of impact estimates to measure effects of the planned treatment; and flaws that result from weakening an evaluation design. Each flaw is illustrated with examples from social experiments. Although these illustrations are from randomized controlled trials (RCTs), they can occur in any type of evaluation; we use RCTs to illustrate because people sometimes assume that RCTs might be immune to such problems. A summary table lists the flaws, indicates circumstances under which they occur, notes their potential seriousness, and suggests approaches for minimizing them.Results:Some of the flaws result in minor hurdles, while others cause evaluations to fail—that is, the evaluation is unable to provide a valid test of the hypothesis of interest. The flaws that appear to occur most frequently are response bias resulting from attrition, failure to adequately implement the treatment as designed, and too small a sample to detect impacts. The third of these can result from insufficient marketing, too small an initial target group, disinterest on the part of the target group in participating (if the treatment is voluntary), or attrition.ConclusionTo a considerable degree, the flaws we discuss can be minimized. For instance, implementation failures and too small a sample can usually be avoided with sufficient planning, and response bias can often be mitigated—for example, through increased follow-up efforts in conducting surveys.
