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Abstract In this article, we propose a new projected PCA to determine the number of factors. We project variables of interest into the space spanned by cross sectional averages of… Click to show full abstract
Abstract In this article, we propose a new projected PCA to determine the number of factors. We project variables of interest into the space spanned by cross sectional averages of variables. And then we construct the eigenvalue tests and the information criteria to estimate the number of factors. We derive the large sample consistency and conduct finite sample simulations to demonstrate the better performances of our estimators. In order to show the edge of our estimators in real data analysis, we revisit a large house price data set for which the number of factors is hard to select.
Journal Title: Communications in Statistics - Theory and Methods
Year Published: 2019
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