具有缺失数据和内生性的有效估计

IF 0.8 4区经济学 Q3 ECONOMICS

Econometric Reviews Pub Date : 2023-02-01 DOI:10.1080/07474938.2023.2178089

Bhavna Rai

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引用次数: 1

摘要

摘要我研究了线性模型中结果和内生协变量的缺失值问题。我提出了一个相对于完整情况2SLS提高效率的估计器。与传统的插补不同，即使模型包含内生协变量的非线性函数（如平方和相互作用），我的估计量也是一致的。它还可以用于组合具有缺失结果、缺失内生协变量和无缺失变量的数据集。它包括众所周知的“两个样本2SLS”，作为一种特殊情况，在比相应文献更弱的假设下。

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Efficient estimation with missing data and endogeneity

Abstract I study the problem of missing values in the outcome and endogenous covariates in linear models. I propose an estimator that improves efficiency relative to a complete cases 2SLS. Unlike traditional imputation, my estimator is consistent even if the model contains nonlinear functions – like squares and interactions – of the endogenous covariates. It can also be used to combine data sets with missing outcome, missing endogenous covariates, and no missing variables. It includes the well-known “Two-Sample 2SLS” as a special case under weaker assumptions than the corresponding literature.

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来源期刊

Econometric Reviews 管理科学-数学跨学科应用

CiteScore

1.70

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Econometric Reviews is widely regarded as one of the top 5 core journals in econometrics. It probes the limits of econometric knowledge, featuring regular, state-of-the-art single blind refereed articles and book reviews. ER has been consistently the leader and innovator in its acclaimed retrospective and critical surveys and interchanges on current or developing topics. Special issues of the journal are developed by a world-renowned editorial board. These bring together leading experts from econometrics and beyond. Reviews of books and software are also within the scope of the journal. Its content is expressly intended to reach beyond econometrics and advanced empirical economics, to statistics and other social sciences.