Diversified weighted averages of panel data estimate latent factors up to an affine transformation that is consistent for factor spans even when the working number of factors R exceeds the true r, with T possibly finite.
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Learning Latent Factors from Diversified Projections and its Applications to Over-Estimated and Weak Factors
Diversified weighted averages of panel data estimate latent factors up to an affine transformation that is consistent for factor spans even when the working number of factors R exceeds the true r, with T possibly finite.