Moment Restriction-Based Econometric Methods: An overview
基于矩限制的计量经济学方法：概览AI 解读 ↓
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基于矩限制的计量经济学方法：概览
- 研究问题
- 矩限制如何统摄参数、半参数与非参数建模？这篇专刊概览介绍相关研究方向，涉及识别、估计、检验及渐近与有限样本性质。
- 方法与思路
- 摘要从矩与条件矩的非参数性质出发，说明有限维参数如何形成半参数估计或检验，并指出以得分构造矩限制可得到最大似然估计。
- 材料陈述的贡献
- 摘要梳理专刊涉及的空间回归、多工具变量、条件矩识别及非线性因果检验等方向；所列方法与成果属于各篇论文，不能归为概览自身的新结果。
- 阅读关注点
- 阅读时应核对各项成果对应的专刊论文，分别确认模型设定、识别要求与适用范围，并区分概览的概念说明和各篇论文的技术贡献。
- 阅读边界
- 仅依据所给65/2010工作稿摘要，稿内日期为2006-10；不能推断同行评审状态或刊本变化。摘要未提供各篇成果的具体条件、证明与数值结果。
原文摘要
Moment restriction-based econometric modelling is a broad class which includes the parametric, semiparametric and nonparametric approaches. Moments and conditional moments themselves are nonparametric quantities. If a model is specified in part up to some finite dimensional parameters, this will provide semiparametric estimates or tests. If we use the score to construct moment restrictions to estimate finite dimensional parameters, this yields maximum likelihood (ML) estimates. Semiparametric or nonparametric settings based on moment restrictions have been the main concern in the literature, and comprise the most important and interesting topics. The purpose of this special issue on “Moment Restriction-based Econometric Methods” is to highlight some areas in which novel econometric methods have contributed significantly to the analysis of moment restrictions, specifically asymptotic theory for nonparametric regression with spatial data, a control variate method for stationary processes, method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models, properties of the CUE estimator and a modification with moments, finite sample properties of alternative estimators of coefficients in a structural equation with many instruments, instrumental variable estimation in the presence of many moment conditions, estimation of conditional moment restrictions without assuming parameter identifiability in the implied unconditional moments, moment-based estimation of smooth transition regression models with endogenous variables, a consistent nonparametric test for nonlinear causality, and linear programming-based estimators in simple linear regression.