Frisch–Waugh–Lovell theorem-type results for the k-Class and 2SGMM estimators

IF 0.9 4区数学 Q3 STATISTICS & PROBABILITY

Statistics & Probability Letters Pub Date : 2024-06-19 DOI:10.1016/j.spl.2024.110188

Deepankar Basu

引用次数: 0

Abstract

The Frisch–Waugh–Lovell (FWL) theorem shows that for the least squares estimator, parameter estimates from full and partial models are identically same. I show that in linear regression models with a mix of exogenous and endogenous regressors, FWL theorem-type results hold for the k-class estimators (including LIML) and the two-step optimal GMM estimator.

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k 类估计器和 2SGMM 估计器的 Frisch-Waugh-Lovell 定理类型结果

Frisch-Waugh-Lovell (FWL) 定理表明，对于最小二乘估计器，完全模型和部分模型的参数估计值完全相同。我的研究表明，在混合了外生和内生回归因子的线性回归模型中，k 类估计器（包括 LIML）和两步最优 GMM 估计器的 FWL 定理类型结果成立。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Statistics & Probability Letters 数学-统计学与概率论

CiteScore

1.60

自引率

0.00%

发文量

173

审稿时长

6 months

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