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We propose robust methods for inference about the effect of a treatment variable on a scalar outcome in the presence of very many regressors in a model with possibly non-Gaussian and heteroscedastic disturbances. We allow for the number of regressors to be larger than the sample size. To make informative inference feasible, we require the model to be approximately sparse; that is, we require that the effect of confounding factors can be controlled for up to a small approximation error by including a relatively small number of variables whose identities are unknown. The latter condition makes it possible to estimate the treatment effect by selecting approximately the right set of regressors. We develop a novel estimation and uniformly valid inference method for the treatment effect in this setting, called the “post-double-selection” method. The main attractive feature of our method is that it allows for imperfect selection of the controls and provides confidence intervals that are valid uniformly across a large class of models. In contrast, standard post-model selection estimators fail to provide uniform inference even in simple cases with a small, fixed number of controls. Thus, our method resolves the problem of uniform inference after model selection for a large, interesting class of models. We also present a generalization of our method to a fully heterogeneous model with a binary treatment variable. We illustrate the use of the developed methods with numerical simulations and an application that considers the effect of abortion on crime rates.

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Chernozhukov, Victor V -  Hansen, Christian B. -  Belloni, Alberto - 

Id.: 69817570

Idioma: inglés (Estados Unidos)  - 

Versión: 1.0

Estado: Final

Tipo de recurso: Article  -  http://purl.org/eprint/type/JournalArticle  - 

Tipo de Interactividad: Expositivo

Nivel de Interactividad: muy bajo

Audiencia: Estudiante  -  Profesor  -  Autor  - 

Estructura: Atomic

Coste: no

Copyright: sí

: Creative Commons Attribution-Noncommercial-Share Alike

Requerimientos técnicos:  Browser: Any - 

Relación: [IsBasedOn] arXiv
[References] http://dx.doi.org/10.1093/restud/rdt044
[References] Review of Economic Studies

Fecha de contribución: 27-abr-2017


* 0034-6527
* 1467-937X
* Belloni, A.; Chernozhukov, V. and Hansen, C. “Inference on Treatment Effects after Selection Among High-Dimensional Controls.” The Review of Economic Studies 81, no. 2 (November 24, 2013): 608–650.

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