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https://doi.org/10.1017/S0266466616000025

has been cited by the following article:

• TITLE: Generalized Method of Moments and Generalized Estimating Functions Using Characteristic Function

  AUTHORS: Andrew Luong

  KEYWORDS: Generalized Normal Laplace Distribution, Generalized Asymmetric Laplace Distribution, Optimum Estimating Functions, Infinitely Divisible Distribution, Simulated Estimation Method

  JOURNAL NAME: Open Journal of Statistics, Vol.10 No.3, June 30, 2020

  ABSTRACT: GMM inference procedures based on the square of the modulus of the model characteristic function are developed using sample moments selected using estimating function theory and bypassing the use of empirical characteristic function of other GMM procedures in the literature. The procedures are relatively simple to implement and are less simulation-oriented than simulated methods of inferences yet have the potential of good efficiencies for models with densities without closed form. The procedures also yield better estimators than method of moment estimators for models with more than three parameters as higher order sample moments tend to be unstable.