Target PCA: Transfer Learning Large Dimensional Panel Data

48 Pages Posted: 27 Dec 2022 Last revised: 30 Aug 2023

See all articles by Junting Duan

Junting Duan

Stanford University - Department of Management Science & Engineering

Markus Pelger

Stanford University - Department of Management Science & Engineering

Ruoxuan Xiong

Emory University

Date Written: December 14, 2022

Abstract

This paper develops a novel method to estimate a latent factor model for a large target panel with missing observations by optimally using the information from auxiliary panel data sets. We refer to our estimator as target-PCA. Transfer learning from auxiliary panel data allows us to deal with a large fraction of missing observations and weak signals in the target panel. We show that our estimator is more efficient and can consistently estimate weak factors, which are not identifiable with conventional methods. We provide the asymptotic inferential theory for target-PCA under very general assumptions on the approximate factor model and missing patterns. In an empirical study of imputing data in a mixed-frequency macroeconomic panel, we demonstrate that target-PCA significantly outperforms all benchmark methods.

Keywords: Factor Analysis, Principal Components, Transfer Learning, Multiple Data Sets, Large-Dimensional Panel Data, Large N and T, Missing Data, Weak Factors, Causal Inference

JEL Classification: C14, C38, C55, G12

Suggested Citation

Duan, Junting and Pelger, Markus and Xiong, Ruoxuan, Target PCA: Transfer Learning Large Dimensional Panel Data (December 14, 2022). Journal of Econometrics, accepted, Available at SSRN: https://ssrn.com/abstract=4302869 or http://dx.doi.org/10.2139/ssrn.4302869

Junting Duan

Stanford University - Department of Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

Markus Pelger

Stanford University - Department of Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

Ruoxuan Xiong (Contact Author)

Emory University ( email )

36 Eagle Row
Atlanta, GA 30322-0001
United States
4707273668 (Phone)

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