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Panel Data Models with Grouped Factor Structure Under Unknown Group Membership
Author(s) -
Ando Tomohiro,
Bai Jushan
Publication year - 2015
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2467
Subject(s) - estimator , econometrics , panel data , mathematics , consistency (knowledge bases) , stock (firearms) , statistics , factor analysis , monte carlo method , group (periodic table) , economics , geography , chemistry , geometry , archaeology , organic chemistry
Summary This paper studies panel data models with unobserved group factor structures. The group membership of each unit and the number of groups are left unspecified. We estimate the model by minimizing the sum of least squared errors with a shrinkage penalty. The number of explanatory variables can be large. The regressions coefficients can be homogeneous or group specific. The consistency and asymptotic normality of the estimator are established. We also introduce new C p ‐type criteria for selecting the number of groups, the numbers of group‐specific common factors and relevant regressors. Monte Carlo results show that the proposed method works well. We apply the method to the study of US mutual fund returns and to the study of individual stock returns of the China mainland stock markets. Copyright © 2015 John Wiley & Sons, Ltd.