IDENTIFYING MULTIPLE MARGINAL EFFECTS WITH A SINGLE INSTRUMENT
IDENTIFYING MULTIPLE MARGINAL EFFECTS WITH A SINGLE INSTRUMENT
复制标题
使用单一工具识别多种边际效应
作者：
Carolina Caetano;J. Escanciano
本文提出了一种新的策略来识别内生多值变量(可以是连续的，也可以是一个向量)在具有低维工具变量(IV，甚至可以是单个二元变量)和多个控制的模型中的边际效应。尽管经典序条件不成立，但我们证明了，通过一种新的秩条件，我们称之为协方差完备性，可以通过利用控制中“第一阶段”的异质性来实现辨识。该辨识策略证明了将仪表和控制之间的相互作用作为附加外生变量使用的合理性，并且可以通过遵循相同的通用算法的参数、半参数和非参数两阶段最小二乘估计器直接实现。蒙特卡罗模拟表明，该估计器在中等样本量下具有良好的性能。最后，我们将我们的方法应用于估计空气质量对房价的影响的问题，基于Chay和Greenstone(2005，Journal of Political Economics 113,376-424)。所有方法都在配套的STATA软件包中实现。
This paper proposes a new strategy for the identification of the marginal effects of an endogenous multivalued variable (which can be continuous, or a vector) in a model with an Instrumental Variable (IV) of lower dimension, which may even be a single binary variable, and multiple controls. Despite the failure of the classical order condition, we show that identification may be achieved by exploiting heterogeneity of the “first stage” in the controls through a new rank condition that we term covariance completeness. The identification strategy justifies the use of interactions between instruments and controls as additional exogenous variables and can be straightforwardly implemented by parametric, semiparametric, and nonparametric two-stage least squares estimators, following the same generic algorithm. Monte Carlo simulations show that the estimators have excellent performance in moderate sample sizes. Finally, we apply our methods to the problem of estimating the effect of air quality on house prices, based on Chay and Greenstone (2005, Journal of Political Economy 113, 376–424). All methods are implemented in a companion Stata software package.
DOI：
10.1257/jep.25.3.153
发表时间：
2011
期刊：
The journal of economic perspectives : a journal of the American Economic Association
影响因子：
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作者：
Almond D;Currie J
通讯作者：
Currie J