Observational Study
An observational study collects data by watching or measuring subjects without any manipulation or intervention.
Definition
An observational study is when researchers watch and record what happens without changing or interfering with anything: they observe and record data without assigning treatments or manipulating variables. Unlike controlled experiments, observational studies cannot establish causation because of potential confounding variables, and treatment assignment is not under the investigator's control. Causal inference from observational data requires assumptions about no unmeasured confounders (ignorability or unconfoundedness), with methods including propensity score matching, instrumental variables, and difference-in-differences.
Example
Watching how many cars run a red light at an intersection over a week is an observational study; the researchers do not change traffic signals, they just count. Researchers who find that people who drink coffee live longer on average are working observationally: coffee drinkers might also exercise more or have other healthy habits (confounders) that explain the association. To estimate the causal effect of education on earnings using observational data, an economist may use proximity to a college as an instrumental variable (IV), exploiting exogenous variation in education not driven by individual characteristics.
Key Insight
Observational studies can show that two things are related, but they cannot prove that one thing causes the other; the key limitation is confounding, and association does not imply causation without a controlled experiment or careful statistical adjustment. The potential outcomes framework (Rubin causal model) formalizes this challenge: the fundamental problem of causal inference is that we observe only one potential outcome per unit, never both.