The method of instrumental variables was first used in the 1920s to estimate supply and demand elasticities, and later used to correct for measurement error in single-equation models. Recently, instrumental variables have been widely used to reduce bias from omitted variables in estimates of causal relationships such as the effect of schooling on earnings. Intuitively, instrumentalvariables methods use only a portion of the variability in key variables to estimate the relationships of interest; if the instruments are valid, that portion is unrelated to the omitted variables. We discuss the mechanics of instrumental variables, and the qualities that make for a good instrument, devoting particular attention to instruments that are derived from "natural experiments." A key feature of the natural experiments approach is the transparency and refutability of identifying assumptions. We also discuss the use of instrumental variables inrandomized experiments. Keywords: simultaneous equations, two-stage least squares, causal inference.