Inference on Treatment Effects after Selection among High-Dimensional Controls
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 inform...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Oxford University Press
2017
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| Online Access: | http://hdl.handle.net/1721.1/108404 https://orcid.org/0000-0002-3250-6714 |