GME - Page 9

GME, or Generalized Method of Moments, is a statistical technique used in econometrics and machine learning for estimating parameters in models. It is based on the idea of using moment conditions—functions of the data that should equal certain theoretical moments based on the model's parameters. By leveraging these moment conditions, GME allows researchers to find parameter estimates that minimize the difference between the sample moments (calculated from the data) and the population moments (theoretical values based on the model).This method is particularly useful when the standard assumptions of traditional maximum likelihood estimation do not hold, as it offers a more flexible framework that does not require the full specification of the error distribution. GME can be applied in various contexts, including time series analysis and dynamic models, making it a versatile tool for empirical research.