Causal Attribution

When examining the impact of a program, a typical analysis will highlight a specific positive change observed in the data. For instance, this could be an increase in voter registration or a higher turnout in elections. One of the main challenges in conducting such studies is to establish a convincing argument that the positive change is a result of the program under investigation, rather than other contributing factors. Many studies rely on simplistic before-and-after comparisons, which often fail to differentiate between program effects and unrelated changes occurring over time (such as a general increase in public interest towards an election). Additionally, some studies compare participants to non-participants, but this approach introduces a significant issue known as selection bias. Those selected or choosing to participate in the program may differ from non-participants in various ways, leading to differences that cannot be solely attributed to the program itself.