# Inference for High-Dimensional Sparse Econometric Models

@article{Belloni2011InferenceFH,
title={Inference for High-Dimensional Sparse Econometric Models},
author={Alexandre Belloni and Victor Chernozhukov and Christian Hansen},
journal={arXiv: Methodology},
year={2011},
pages={245-295}
}
• Published 30 December 2011
• Economics, Computer Science
• arXiv: Methodology
Introduction We consider linear, high-dimensional sparse (HDS) regression models in econometrics. The HDS regression model allows for a large number of regressors, p , which is possibly much larger than the sample size, n , but imposes that the model is sparse. That is, we assume that only s ≪ n of these regressors are important for capturing the main features of the regression function. This assumption makes it possible to effectively estimate HDS models by searching for approximately the…
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