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High Dimensional Sparse Econometric Models: An Introduction

Author(s)
Belloni, Alexandre; Chernozhukov, Victor V.
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Abstract
In this chapter we discuss conceptually high dimensional sparse econometric models as well as estimation of these models using ℓ1-penalization and post- ℓ1-penalization methods. Focusing on linear and nonparametric regression frameworks, we discuss various econometric examples, present basic theoretical results, and illustrate the concepts and methods withMonte Carlo simulations and an empirical application. In the application, we examine and confirm the empirical validity of the Solow-Swan model for international economic growth.
Description
arXiv: (Submitted on 26 Jun 2011 (v1), last revised 2 Sep 2011 (this version, v2))
Date issued
2011
URI
http://hdl.handle.net/1721.1/73908
Department
Massachusetts Institute of Technology. Department of Economics
Journal
Inverse Problems and High-Dimensional Estimation
Publisher
Springer Science + Business Media B.V.
Citation
Belloni, Alexandre and Victor Chernozhukov. "High Dimensional Sparse Econometric Models: An Introduction." Chapter 3 in Inverse Problems and High-Dimensional Estimation. Pierre Alquier, Eric Gautier, Gilles Stoltz, editors. (Lecture Notes in Statistics Volume 203), 2011, pp 121-156. © Springer-Verlag Berlin Heidelberg 2011.
Version: Author's final manuscript
ISBN
9783642199899
3642199895
978-3-642-19988-2

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