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Instrumental Variables, Selection Models, and Tight Bounds on the Average Treatment Effect

Heckman, James J.; Vytlacil, Edward - 2021

This paper exposits and relates two distinct approaches to bounding the average treatment effect. One approach, based on instrumental variables, is due to Manski (1990, 1994), who derives tight bounds on the average treatment effect under a mean independence form of the instrumental variables...

Persistent link: https://www.econbiz.de/10013239385

Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap

D'Haultfœuille, Xavier - 2014

We consider the estimation of a semiparametric location-scale model subject to endogenous selection, in the absence of an instrument or a large support regressor. Identification relies on the independence between the covariates and selection, for arbitrarily large values of the outcome. In this...

Persistent link: https://www.econbiz.de/10013051753

Estimating the Impacts of Program Benefits : Using Instrumental Variables with Underreported and Imputed Data

Stephens, Melvin - 2015

Survey non-response has risen in recent years which has increased the share of imputed and underreported values found on commonly used datasets. While this trend has been well-documented for earnings, the growth in non-response to government transfers questions has received far less attention....

Persistent link: https://www.econbiz.de/10013021468

Semiparametric Estimation of Instrumental Variable Models for Causal Effects

Abadie, Alberto - 2021

This article introduces a new class of instrumental variable (IV) estimators of causal treatment effects for linear and nonlinear models with covariates. The rationale for focusing on nonlinear models is to improve the approximation to the causal response function of interest. For example, if...

Persistent link: https://www.econbiz.de/10013239198

IV Quantile Regression for Group-Level Treatments, with an Application to the Distributional Effects of Trade

Chetverikov, Denis - 2015

of group-level unobservables, standard quantile regression techniques are inconsistent in our setting even if the …, consisting of group-by-group quantile regression followed by two-stage least squares. Using the Bahadur representation of …

Persistent link: https://www.econbiz.de/10013025812

Correcting for Misclassified Binary Regressors Using Instrumental Variables

Haider, Steven; Stephens, Melvin - 2022

Estimators that exploit an instrumental variable to correct for misclassification in a binary regressor typically assume that the misclassification rates are invariant across all values of the instrument. We show that this assumption is invalid in routine empirical settings. We derive a new...

Persistent link: https://www.econbiz.de/10014093957

Optimal Invariant Similar Tests for Instrumental Variables Regression

Andrews, Donald W. K.; Moreira, Marcelo J.; Stock, James H. - 2021

This paper considers tests of the parameter on endogenous variables in an instrumental variables regression model. The …

Persistent link: https://www.econbiz.de/10013231228

Spatial Errors in Count Data Regressions

Bertanha, Marinho - 2014

Count data regressions are an important tool for empirical analyses ranging from analyses of patent counts to measures of health and unemployment. Along with negative binomial, Poisson panel regressions are a preferred method of analysis because the Poisson conditional fixed effects maximum...

Persistent link: https://www.econbiz.de/10013049006

A New Control Function Approach for Non-Parametric Regressions with Endogenous Variables

Kim, Kyoo il - 2011

When the endogenous variable enters the structural equation non-parametrically the linear Instrumental Variable (IV) estimator is no longer consistent. Non-parametric IV (NPIV) can be used but it requires one to impose restrictions during estimation to make the problem well-posed. The...

Persistent link: https://www.econbiz.de/10013131512

Semiparametrically Efficient Estimation of the Average Linear Regression Function

Graham, Bryan S. - 2018

regression of Y onto X in a subpopulation homogenous in W = w (formally a conditional linear predictor). Let b<sub>0</sub> (w) be … the coefficient vector on X in this regression. We introduce a semiparametrically efficient estimate of the average β … methods of semiparametric regression (e.g., the partially linear regression model) …

Persistent link: https://www.econbiz.de/10012908172

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