The generalized method of moments (GMM) is a statistical technique used to estimate parameters in models. It relies on the idea of matching sample moments, such as means or variances, with theoretical moments derived from a model. By minimizing the difference between these moments, GMM provides efficient and consistent estimates, even in complex models. GMM is particularly useful in econometrics, where it can handle situations with limited data or when traditional methods, like maximum likelihood estimation, are difficult to apply. It is widely used in various fields, including finance and social sciences, to analyze relationships between variables.