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Historical econometrics : instrumental variables and regression discontinuity designs

Caicedo, Felipe Valencia - 2020

Persistent link: https://www.econbiz.de/10012299251

Chernozhukov, Victor; Hansen, Christian Bailey - 2013

In this article, we review quantile models with endogeneity. We focus on models that achieve indentification through the use of instrumental variables and discuss conditions under which partial and point identification are obtained. We discuss key conditions, which include monotonicity and...

Persistent link: https://www.econbiz.de/10009747939

Nonparametric instrumental variable estimation

Wilhelm, Daniel; Chetverikov, Denis; Kim, Dongwoo - 2017

This paper introduces Stata commands [R] npivreg and [R] npivregcv, which implement nonparametric instrumental variable …

Persistent link: https://www.econbiz.de/10011758353

What do instrumental variable models deliver with discrete dependent variables?

Chesher, Andrew; Rosen, Adam M. - 2013

We study models with discrete endogenous variables and compare the use of two stage least squares (2SLS) in a linear probability model with bounds analysis using a nonparametric instrumental variable model. 2SLS has the advantage of providing an easy to compute point estimator of a slope...

Persistent link: https://www.econbiz.de/10009718426

Simultaneous equations models for discrete outcomes : coherence, completeness, and identification

Chesher, Andrew; Rosen, Adam M. - 2012

This paper studies simultaneous equations models for two or more discrete outcomes. These models may be incoherent, delivering no values of the outcomes at certain values of the latent variables and covariates, and they may be incomplete, delivering more than one value of the outcomes at certain...

Persistent link: https://www.econbiz.de/10009580790

hdm : high-dimensional metrics

Chernozhukov, Victor; Hansen, Christian Bailey; … - 2016

. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment … or policy variable) in a high-dimensional approximately sparse regression model, for average treatment effect (ATE) and … heteroscedastic and non-Gaussian errors are implemented. Moreover, joint/ simultaneous confidence intervals for regression …

Persistent link: https://www.econbiz.de/10011524715

Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors

Severini, Thomas A. (contributor); … - 2007

Persistent link: https://www.econbiz.de/10003481731

Nonparametric identification of the classical errors-in-variables model without side information

Schennach, Susanne M. (contributor); Hu, Yingyao (contributor) - 2007

Persistent link: https://www.econbiz.de/10003502450

Nonparametric instrumental variables estimation of a quantile regression model

Horowitz, Joel (contributor); Lee, Sokbae (contributor) - 2006

Persistent link: https://www.econbiz.de/10003332176

Inference on treatment effects after selection amongst high-dimensional controls

Belloni, Alexandre; Chernozhukov, Victor; Hansen, … - 2013 - This version May 30, 2013

We propose robust methods for inference on the effect of a treatment variable on a scalar outcome in the presence of very many controls. Our setting is a partially linear model with possibly non-Gaussian and heteroscedastic disturbances where the number of controls may be much larger than the...

Persistent link: https://www.econbiz.de/10009747934

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