Sparse High-Dimensional Models in Economics

Posted: 31 Aug 2011

See all articles by Jianqing Fan

Jianqing Fan

Princeton University - Bendheim Center for Finance

Jinchi Lv

University of Southern California - Marshall School of Business

Lei Qi

Princeton University

Multiple version iconThere are 2 versions of this paper

Date Written: September 2011

Abstract

This article reviews the literature on sparse high-dimensional models and discusses some applications in economics and finance. Recent developments in theory, methods, and implementations in penalized least-squares and penalized likelihood methods are highlighted. These variable selection methods are effective in sparse high-dimensional modeling. The limits of dimensionality that regularization methods can handle, the role of penalty functions, and their statistical properties are detailed. Some recent advances in sparse ultra-high-dimensional modeling are also briefly discussed.

Suggested Citation

Fan, Jianqing and Lv, Jinchi and Qi, Lei, Sparse High-Dimensional Models in Economics (September 2011). Annual Review of Economics, Vol. 3, pp. 291-317, 2011. Available at SSRN: https://ssrn.com/abstract=1920103 or http://dx.doi.org/10.1146/annurev-economics-061109-080451

Jianqing Fan (Contact Author)

Princeton University - Bendheim Center for Finance ( email )

26 Prospect Avenue
Princeton, NJ 08540
United States
609-258-7924 (Phone)
609-258-8551 (Fax)

HOME PAGE: http://orfe.princeton.edu/~jqfan/

Jinchi Lv

University of Southern California - Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA 90089
United States

HOME PAGE: http://www-rcf.usc.edu/~jinchilv

Lei Qi

Princeton University ( email )

22 Chambers Street
Princeton, NJ 08544-0708
United States

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