How Much Should We Trust Linear Instrumental Variables Estimators? An Application to Family Size and Children's Education

M. Mogstad, Matthew Wiswall
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引用次数: 7

Abstract

Many empirical studies specify outcomes as a linear function of endogenous regressors when conducting instrumental variable (IV) estimation. We show that tests for treatment effects, selection bias, and treatment effect heterogeneity are biased if the true relationship is non-linear. These results motivate a re-examination of recent evidence suggesting no causal effect of family size on children's education. Following common practice, a linear IV estimator has been used, assuming constant marginal effects of additional children across family sizes. We find that the conclusion of no effect of family size is an artifact of the linear specification, which masks substantial marginal family size effects.
我们应该在多大程度上信任线性工具变量估计器?家庭规模与儿童教育的应用
许多实证研究在进行工具变量(IV)估计时,将结果指定为内生回归因子的线性函数。我们表明,如果真实关系是非线性的,那么治疗效果、选择偏差和治疗效果异质性的检验是有偏差的。这些结果促使人们重新审视最近的证据,这些证据表明家庭规模对儿童教育没有因果关系。按照通常的做法,使用了线性IV估计器,假设在家庭规模中增加的孩子的边际效应是恒定的。我们发现家庭规模没有影响的结论是线性规范的伪产物,它掩盖了大量的边际家庭规模效应。
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