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This lecture covers the Generalized Method of Moments (GMM), a versatile approach for estimation based on moment restrictions. It starts by explaining the method of moments and then delves into GMM, which allows for more moment conditions than parameters and non-linear relationships. The lecture discusses the optimal weighting matrix, the iterative estimation process, and its application in asset pricing models. It also explores the advantages of GMM, such as not requiring distributional assumptions and handling heteroskedasticity, while highlighting its limitations, including issues with weak identification.