The standard econometric modelling practice for quite a long time was founded on strong assumptions concerning the underlying data generating process. Based on these assumptions, estimation and hypothesis testing techniques were derived with known desirable, and in many cases optimal, properties. Frequently, these assumptions were highly unrealistic and unlikely to be true. These shortcomings were attributed to the simplification involved in any modelling process and therefore inevitable and acceptable. The crisis of econometric modelling in the seventies led to many well known new, sometimes revolutionary, developments in the way econometrics was undertaken. Unrealistically strong assumptions were no longer acceptable. Techniques and procedures able to deal with data and models within a more realistic framework were badly required. Just at the right time, i.e., the early eighties when all this became obvious, Lars Peter Hansen's seminal paper on the asymtotic properties of the generalized method of moments (GMM) estimator was published in Econometrica. Although the basic idea of the GMM can be traced back to the work of Denis Sargan in the late fifties, Hansen's paper provided a ready to use, very flexible tool applicable to a large number of models, which relied on mild and plausible assumptions. The die was cast. Applications of the GMM approach have mushroomed since in the literature, which has been, as so many things, further boosted recently by the increased availability of computing power.

Nowadays there are so many different theoretical and practical applications of the GMM principle that it is almost impossible to keep track of them.