Econometrica · 2023 · Victor Chernozhukov、Whitney K. Newey、Andres Santos
中文摘要
形状约束在经济学中发挥了核心作用，它既是理论的可检验含义，也是获得有信息量的反事实预测的充分条件。在本文中，我们为由条件矩约束定义的已识别和部分识别模型中的形状约束下推断提供了一般程序。我们的检验统计量和提出的推断方法基于带有和不带有形状约束的广义矩估计 (GMM) 目标函数的最小值。一致有效的临界值是通过近似真实局部参数空间子集的自助法程序获得的。在关于生育对女性劳动供给影响的实证分析中，我们表明在线性工具变量 (IV) 模型中采用形状约束可以为局部和平均处理效应带来更短的置信域。我们讨论的其他应用包括分位数 IV 处理效应变异性的推断，以及具有一般异质性的需求模型中平均等价变动界限的推断。
Abstract
Shape restrictions have played a central role in economics as both testable implications of theory and sufficient conditions for obtaining informative counterfactual predictions. In this paper, we provide a general procedure for inference under shape restrictions in identified and partially identified models defined by conditional moment restrictions. Our test statistics and proposed inference methods are based on the minimum of the generalized method of moments (GMM) objective function with and without shape restrictions. Uniformly valid critical values are obtained through a bootstrap procedure that approximates a subset of the true local parameter space. In an empirical analysis of the effect of childbearing on female labor supply, we show that employing shape restrictions in linear instrumental variables (IV) models can lead to shorter confidence regions for both local and average treatment effects. Other applications we discuss include inference for the variability of quantile IV treatment effects and for bounds on average equivalent variation in a demand model with general heterogeneity.