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Valid post-selection and post-regularization inference : an elementary, general approach

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

Here we present an expository, general analysis of valid post-selection or post-regularization inference about a low-dimensional target parameter in the presence of a very high-dimensional nuisance parameter which is estimated using selection or regularization methods. Our analysis provides a...

Persistent link: https://www.econbiz.de/10011524714

Double machine learning for treatment and causal parameters

Chernozhukov, Victor; Chetverikov, Denis; Demirer, Mert; … - 2016

.g. a hybrid of a random forest and lasso). We illustrate the application of the general theory through application to the …

Persistent link: https://www.econbiz.de/10011538313

Program evaluation with high-dimensional data

Belloni, Alexandre; Chernozhukov, Victor; … - 2015 - This version: September 20, 2015

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data-rich environments. We can handle very many control variables, endogenous receipt of treatment,...

Persistent link: https://www.econbiz.de/10011337681

Simulation and estimation of hedonic models

Heckman, James J. (contributor); … - 2003 - [Elektronische Ressource]

Persistent link: https://www.econbiz.de/10001835951

Evaluating marginal policy changes and the average effect of treatment for individuals at the margin

Carneiro, Pedro; Heckman, James J.; Vytlacil, Edward - 2009

This paper develops methods for evaluating marginal policy changes. We characterize how the effects of marginal policy changes depend on the direction of the policy change, and show that marginal policy effects are fundamentally easier to identify and to estimate than conventional treatment...

Persistent link: https://www.econbiz.de/10003869267

Sparse models and methods for optimal instruments with an application to eminent domain

Belloni, A.; Chen, D.; Chernozhukov, Victor; Hansen, … - 2010

sample size, n. We rigorously develop asymptotic distribution and inference theory for the resulting IV estimators and … functions which are of independent theoretical and practical interest. Specifically, we develop the asymptotic theory for these … innovatively using moderate deviation theory for self-normalized sums, we provide convergence rates for these estimators that are …

Persistent link: https://www.econbiz.de/10008695561

Inference for high-dimensional sparse econometric models

Belloni, Alexandre; Chernozhukov, Victor; Hansen, … - 2011

This article is about estimation and inference methods for high dimensional sparse (HDS) regression models in econometrics. High dimensional sparse models arise in situations where many regressors (or series terms) are available and the regression function is well-approximated by a parsimonious,...

Persistent link: https://www.econbiz.de/10009419335

Estimation of treatment effects with high-dimensional controls

Belloni, Alexandre; Chernozhukov, Victor; Hansen, … - 2011

We propose methods for inference on the average effect of a treatment on a scalar outcome in the presence of very many controls. Our setting is a partially linear regression model containing the treatment/policy variable and a large number p of controls or series terms, with p that is possibly...

Persistent link: https://www.econbiz.de/10009419338

Program evaluation with high-dimensional data

Belloni, Alexandre; Chernozhukov, Victor; … - 2013

We consider estimation of policy relevant treatment effects in a data-rich environ ment where there may be many more control variables available than there are observations. In addition to allowing many control variables, the setting we consider allows heterogeneous treatment effects, endogenous...

Persistent link: https://www.econbiz.de/10010200037

Quantile models with endogeneity

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