Generalized Method of Moments and Generalized Estimating Functions Using Characteristic Function

• 作者: Andrew Luong
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: Generalized Normal Laplace Distribution Generalized Asymmetric Laplace Distribution Optimum Estimating Functions Infinitely Divisible Distribution Simulated Estimation Method
• 年，卷（期）: 2020,（3）
• 页码范围: 581-599
• 页数: 19页
• 分类号: O17

摘要

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.