Consistent estimation of the number of dynamic factors in a large N and T panel

Dante Amengual; Mark W. Watson

doi:10.1198/073500106000000585

Consistent estimation of the number of dynamic factors in a large N and T panel

Dante Amengual
, Mark W. Watson

Research output: Contribution to journal › Article › peer-review

137 Scopus citations

Abstract

Bai and Ng proposed a consistent estimator for the number of static factors in a large N and T approximate factor model. This article shows how the Bai-Ng estimator can be modified to consistently estimate the number of dynamic factors in a restricted dynamic factor model. The modification is straightforward: The standard Bai-Ng estimator is applied to residuals obtained by projecting the observed data onto lagged values of principal-components estimates of the static factors.

Original language	English (US)
Pages (from-to)	91-96
Number of pages	6
Journal	Journal of Business and Economic Statistics
Volume	25
Issue number	1
DOIs	https://doi.org/10.1198/073500106000000585
State	Published - Jan 2007

All Science Journal Classification (ASJC) codes

Statistics and Probability
Social Sciences (miscellaneous)
Economics and Econometrics
Statistics, Probability and Uncertainty

Keywords

Approximate factor model
Bai-Ng estimator
Dynamic factor model

Access to Document

10.1198/073500106000000585

Cite this

@article{543eabae699242ebbe87765e60168fc6,

title = "Consistent estimation of the number of dynamic factors in a large N and T panel",

abstract = "Bai and Ng proposed a consistent estimator for the number of static factors in a large N and T approximate factor model. This article shows how the Bai-Ng estimator can be modified to consistently estimate the number of dynamic factors in a restricted dynamic factor model. The modification is straightforward: The standard Bai-Ng estimator is applied to residuals obtained by projecting the observed data onto lagged values of principal-components estimates of the static factors.",

keywords = "Approximate factor model, Bai-Ng estimator, Dynamic factor model",

author = "Dante Amengual and Watson, \{Mark W.\}",

note = "Funding Information: This research is an outgrowth of joint work with Jim Stock, who we thank for his comments and suggestions. Thanks also to Jushan Bai, Serena Ng, two referees, and the associate editor for their useful comments. This work was funded in part by NSF grant SBR-0214131. Copyright: Copyright 2011 Elsevier B.V., All rights reserved.",

year = "2007",

month = jan,

doi = "10.1198/073500106000000585",

language = "English (US)",

volume = "25",

pages = "91--96",

journal = "Journal of Business and Economic Statistics",

issn = "0735-0015",

publisher = "Taylor and Francis Ltd.",

number = "1",

}

TY - JOUR

T1 - Consistent estimation of the number of dynamic factors in a large N and T panel

AU - Amengual, Dante

AU - Watson, Mark W.

N1 - Funding Information: This research is an outgrowth of joint work with Jim Stock, who we thank for his comments and suggestions. Thanks also to Jushan Bai, Serena Ng, two referees, and the associate editor for their useful comments. This work was funded in part by NSF grant SBR-0214131. Copyright: Copyright 2011 Elsevier B.V., All rights reserved.

PY - 2007/1

Y1 - 2007/1

N2 - Bai and Ng proposed a consistent estimator for the number of static factors in a large N and T approximate factor model. This article shows how the Bai-Ng estimator can be modified to consistently estimate the number of dynamic factors in a restricted dynamic factor model. The modification is straightforward: The standard Bai-Ng estimator is applied to residuals obtained by projecting the observed data onto lagged values of principal-components estimates of the static factors.

AB - Bai and Ng proposed a consistent estimator for the number of static factors in a large N and T approximate factor model. This article shows how the Bai-Ng estimator can be modified to consistently estimate the number of dynamic factors in a restricted dynamic factor model. The modification is straightforward: The standard Bai-Ng estimator is applied to residuals obtained by projecting the observed data onto lagged values of principal-components estimates of the static factors.

KW - Approximate factor model

KW - Bai-Ng estimator

KW - Dynamic factor model

UR - https://www.scopus.com/pages/publications/33846041971

UR - https://www.scopus.com/pages/publications/33846041971#tab=citedBy

U2 - 10.1198/073500106000000585

DO - 10.1198/073500106000000585

M3 - Article

AN - SCOPUS:33846041971

SN - 0735-0015

VL - 25

SP - 91

EP - 96

JO - Journal of Business and Economic Statistics

JF - Journal of Business and Economic Statistics

IS - 1

ER -

Consistent estimation of the number of dynamic factors in a large N and T panel

Abstract

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

Other files and links

Fingerprint

Cite this