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摘要翻译：
我们研究了基于Lasso的推理方法，如后双Lasso和去偏Lasso的有限样本行为。我们证明，由于Lasso没有选择相关的控制，这些方法可以表现出大量的省略变量偏差(OVBs)。即使在系数稀疏、样本量大且大于对照数的情况下也会发生这种现象。因此，依赖现有的渐近推理理论在经验应用中可能会出现问题。我们将基于LASSO的推理方法与现代高维OLS的推理方法进行了比较，并提供了实用的指导。
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英文标题：
《Omitted variable bias of Lasso-based inference methods: A finite sample
analysis》
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作者：
Kaspar Wuthrich and Ying Zhu
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最新提交年份：
2021
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分类信息：
一级分类：Mathematics 数学
二级分类：Statistics Theory 统计理论
分类描述：Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计：例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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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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一级分类：Statistics 统计学
二级分类：Statistics Theory 统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
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英文摘要：
We study the finite sample behavior of Lasso-based inference methods such as post double Lasso and debiased Lasso. We show that these methods can exhibit substantial omitted variable biases (OVBs) due to Lasso not selecting relevant controls. This phenomenon can occur even when the coefficients are sparse and the sample size is large and larger than the number of controls. Therefore, relying on the existing asymptotic inference theory can be problematic in empirical applications. We compare the Lasso-based inference methods to modern high-dimensional OLS-based methods and provide practical guidance.
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PDF链接：
https://arxiv.org/pdf/1903.08704
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