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Determining the Number of Factors in Approximate Factor Models-英文文献
DETERMINING THE NUMBER OF FACTORS IN APPROXIMATE
FACTOR MODELS
Jushan Bai Serena Ng
Department of Economics
Boston College
Chestnut Hill
MA 02467
Januar y31, 2000
Abstract
In this paper we develop some statistical theory for factor models of large dimen-
sions. The focus is the determination of the number of factors, which is an unresolved
issue in the rapidly growing literature on multifactor models. We propose a panel Cp
criterion and show that the number of factors can be consistently estimated using the
criterion. The theory is developed under the framework of large cross-sections (N ) and
large time dimensions (T ). No restriction is imposed on the relation between N and
T . Simulations show that the proposed criterion yields almost precise estimates of the
number of factors for configurations of the panel data encountered in practice.
JEL Classification: C13, C33, C43
1 Introduction
The idea that variations in a large number of economic variables can be modelled b ya small
number of reference variables is appealing and is used in man yeconomic analysis. In the
finance literature, the arbitrage pricing theor y(APT) of Ross (1976) assumes that a small
number of factors can be used to explain a large number of asset returns.1 The observed
comovements in a large number of macroeconomic time series have likewise generated enor-
mous interests in developing ways to account for business cycle dynamics b ya small number
of reference variables. In demand analysis, Lewbel (1991) showed that
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