Natural Experiments: Missed Opportunities for Causal Inference in Psychology

Causal inference is a central goal of science. Experiments are the preferred design for learning about causal effects, but experiments are often unethical or unfeasible. On the other hand, observational studies are usually feasible but lack the random assignment that renders experiments causally informative. Natural experiments can sometimes offer unique opportunities for dealing with this dilemma, allowing causal inference on the basis of events that are not controlled by the researcher but that nevertheless establish random or as-if random assignment to treatment and control conditions. Yet, psychological researchers are hardly aware of the concept of natural experiments and have therefore rarely exploited natural experiments so far. To remedy this shortage, we describe three main types of studies exploiting natural experiments (standard natural experiments, instrumental variable designs, and regression discontinuity designs) and provide examples from psychology and economics to illustrate how natural experiments can be harnessed. Natural experiments are challenging to find, provide information about only specific causal effects, and involve assumptions that are difficult to validate. Nevertheless, we believe that natural experiments provide valuable causal inference opportunities that have not yet been sufficiently exploited by psychologists.