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most citedPrincipal Component Analysis for High-Dimensional Approximate Factor Models in Time Series: Assumptions, Asymptotic Theory, and Identification

3 citations · 3 across the 1 of their papers we have counts for

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econ.EM2026★ 3 cited

Principal Component Analysis for High-Dimensional Approximate Factor Models in Time Series: Assumptions, Asymptotic Theory, and Identification

Matteo Barigozzi

We consider estimation of large approximate factor models in high-dimensional panels of stationary time series using Principal Component Analysis (PCA). We review the key results e…

econ.EM2025

Factor Network Autoregressions

Matteo Barigozzi, Giuseppe Cavaliere, Graziano Moramarco

We propose a factor network autoregressive (FNAR) model for time series with complex network structures. The coefficients of the model reflect many different types of connections b…

econ.EM2024

Modelling Large Dimensional Datasets with Markov Switching Factor Models

Matteo Barigozzi, Daniele Massacci

We study a novel large dimensional approximate factor model with regime changes in the loadings driven by a latent first order Markov process. By exploiting the equivalent linear r…