Abstract

The generalized method of moments (GMM) provides a computationally convenient method for inference on the structural parameters of economic models. The method has been applied in many areas of economics but it was in empirical finance that the power of the method was first illustrated. Hansen (1982) introduced GMM and presented its fundamental statistical theory. Hansen and Hodrick (1980) and Hansen and Singleton (1982) showed the potential of the GMM approach to testing economic theories through their empirical analyzes of, respectively, foreign exchange markets and asset pricing. In such contexts, the cornerstone of GMM inference is a set of conditional moment restrictions. More generally, GMM is well suited for the test of an economic theory every time the theory can be encapsulated in the postulated unpredictability of some error term u(Y_t ,?) given as a known function of p unknown parameters ? ∈ ?⊆?^p and a vector of observed random variables Y_t . Then, the testability of the theory of interest is akin to the testability of a set of conditional moment restrictions, 2.1 E t [ u ( Y t + 1 , ? ) ] = 0 ,