This paper discusses the role of structural economic models in empirical analysis and policy design. The central payoff of a structural econometric model is that it allows an empirical researcher to go beyond the conclusions of a more conventional empirical study that provides reduced-form causal relationships. Structural models identify mechanisms that determine outcomes and are designed to analyze counterfactual policies, quantifying impacts on specific outcomes as well as effects in the short and longer run. We start by defining structural models, distinguishing between those that are fully specified and those that are partially specified. We contrast the treatment effects approach with structural models, and present an example of how a structural model is specified and the particular choices that were made. We cover combining structural estimation with randomized experiments. We then turn to numerical techniques for solving dynamic stochastic models that are often used in structural estimation, again with an example. The penultimate section focuses on issues of estimation using the method of moments.