Matteo Barigozzi, Giuseppe Cavaliere, Graziano Moramarco
arXiv 4 Aug 2022 · Econometrics · publishedJournal of Business and Economic Statistics (2025) · 5 citations (OpenAlex)
arXiv:2208.02925 · PDF · DOI · OpenAlex · Extracted main text
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 between economic agents ("multilayer network"), which are summarized into a smaller number of network matrices ("network factors") through a novel tensor-based principal component approach. We provide consistency and asymptotic normality results for the estimation of the factors, their loadings, and the coefficients of the FNAR, as the number of layers, nodes and time points diverges to infinity. Our approach combines two different dimension-reduction techniques and can be applied to high-dimensional datasets. Simulation results show the goodness of our estimators in finite samples. In an empirical application, we use the FNAR to investigate the cross-country interdependence of GDP growth rates based on a variety of international trade and financial linkages. The model provides a rich characterization of macroeconomic network effects as well as good forecasts of GDP growth rates.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Chen, E.Y., Fan, J. and Zhu, X (2023) Community Network Auto-Regression for High-Dimensional Time Series | 1.000 | 15 | 5 | 100% |
| 2 | Bai, J (2003) Inferential theory for factor models of large dimensions | 1.000 | 12 | 4 | 100% |
| 3 | Zhu, X., Pan, R., Li, G., Liu, Y. and Wang, H (2017) Network Vector Autoregression | 1.000 | 12 | 4 | 100% |
| 4 | Bai, J (2009) Panel data models with interactive fixed effects | 1.000 | 10 | 5 | 100% |
| 5 | Chen, R., Yang, D. and Zhang, C.H (2022) Factor Models for High-Dimensional Tensor Time Series | 1.000 | 10 | 4 | 100% |
| 6 | Bai, J. and Ng, S (2006) Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions | 1.000 | 5 | 3 | 100% |
| 7 | Wang, D., Zheng, Y., Lian, H. and Li, G (2022) High-Dimensional Vector Autoregressive Time Series Modeling via Tensor Decomposition | 1.000 | 5 | 3 | 100% |
| 8 | Barigozzi, M (2022) On estimation and inference of large approximate dynamic factor models via the principal component analysis, ArXiv:2211.01921 self | 0.874 | 19 | 2 | 100% |
| 9 | Barigozzi, M., He, Y., Li, L. and Trapani, L (2023) Statistical Inference for Large-dimensional Tensor Factor Model by Iterative Projections, arXiv:2206.09800 self | 0.811 | 4 | 2 | 100% |
| 10 | Zhu, X., Xu, G. and Fan, J (2023) Simultaneous estimation and group identification for network vector autoregressive model with heterogeneous nodes | 0.644 | 2 | 2 | 100% |
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