Testing Hypotheses About the Number of Factors in Large Factor Models

Abstract

In this paper we study high-dimensional time series that have the generalized dynamic factor structure. We develop a test of the null of k 0 factors against the alternative that the number of factors is larger than k 0 but no larger than k 1 >k 0 . Our test statistic equals max k 0 >k⩽k 1 (Gamma k - Gamma k+1 )(Gamma k+1 - Gamma k+2 ), where Gamma i is the ith largest eigenvalue of the smoothed periodogram estimate of the spectral density matrix of data at a prespecified frequency. We describe the asymptotic distribution of the statistic, as the dimensionality and the number of observations rise, as a function of the Tracy-Widom distribution and tabulate the critical values of the test. As an application, we test different hypotheses about the number of dynamic factors in macroeconomic time series and about the number of dynamic factors driving excess stock returns. Copyright 2009 The Econometric Society.