Improved penalization for determining the number of factors in approximate factor models

被引：175

作者：

Alessi, Lucia ^{[2
]}

Barigozzi, Matteo ^{[1
]}

Capasso, Marco ^{[3
,4
]}

机构：

[1] Univ London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, England

[2] European Cent Bank, Frankfurt, Germany

[3] Univ Utrecht, Fac Geosci, Urban & Reg Res Ctr Utrecht URU, NL-3508 TC Utrecht, Netherlands

[4] Univ Utrecht, Utrecht Sch Econ, Tjalling C Koopmans Inst TKI, NL-3508 TC Utrecht, Netherlands

来源：

STATISTICS & PROBABILITY LETTERS | 2010年 / 80卷 / 23-24期

关键词：

Number of factors; Approximate factor models; Information criterion; Model selection; DYNAMIC-FACTOR MODEL;

D O I：

10.1016/j.spl.2010.08.005

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The procedure proposed by Bai and Ng (2002) for identifying the number of factors in static factor models is revisited. In order to improve its performance, we introduce a tuning multiplicative constant in the penalty, an idea that was proposed by Hallin and Liska (2007) in the context of dynamic factor models. Simulations show that our method in general delivers more reliable estimates, in particular in the case of large idiosyncratic disturbances. (c) 2010 Elsevier B.V. All rights reserved.

引用

页码：1806 / 1813

页数：8

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