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摘要翻译：
内生性和数据缺失是实证研究中常见的问题。我们研究两者如何共同影响因果参数的推断。传统的估计方差的方法是不可靠的，这种方法将估算的数据视为最初观察到的数据。我们推导了渐近方差，并提出了两阶段最小二乘的异方差鲁棒方差估计。蒙特卡罗模拟支持我们的理论发现。
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英文标题：
《On the Effect of Imputation on the 2SLS Variance》
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作者：
Helmut Farbmacher, Alexander Kann
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最新提交年份：
2019
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分类信息：
一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
Endogeneity and missing data are common issues in empirical research. We investigate how both jointly affect inference on causal parameters. Conventional methods to estimate the variance, which treat the imputed data as if it was observed in the first place, are not reliable. We derive the asymptotic variance and propose a heteroskedasticity robust variance estimator for two-stage least squares which accounts for the imputation. Monte Carlo simulations support our theoretical findings.
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PDF链接：
https://arxiv.org/pdf/1903.11004
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