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.