Junhui Cai, Dan Yang, Ran Chen, Wu Zhu, Haipeng Shen, Linda Zhao
arXiv 25 Nov 2021 · Econometrics · publishedJournal of the American Statistical Association (2026) · 1 citations (OpenAlex)
arXiv:2111.12921 · PDF · DOI · OpenAlex · Extracted main text
The centrality in a network is often used to measure nodes' importance and model network effects on a certain outcome. Empirical studies widely adopt a two-stage procedure, which first estimates the centrality from the observed noisy network and then infers the network effect from the estimated centrality, even though it lacks theoretical understanding. We propose a unified modeling framework to study the properties of centrality estimation and inference and the subsequent network regression analysis with noisy network observations. Furthermore, we propose a supervised centrality estimation methodology, which aims to simultaneously estimate both centrality and network effect. We showcase the advantages of our method compared with the two-stage method both theoretically and numerically via extensive simulations and a case study in predicting currency risk premiums from the global trade network.
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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 | Richmond, R. J (2019) Trade network centrality and currency risk premia | 0.874 | 8 | 2 | 100% |
| 2 | Han, X., Yang, Q., and Fan, Y (2023) Universal rank inference via residual subsampling with application to large networks | 0.511 | 2 | 2 | 50% |
| 3 | Ahern, K. R (2013) Network centrality and cross section of stock returns | 0.511 | 2 | 1 | 100% |
| 4 | Allen, F., Cai, J., Gu, X., Qian, J., Zhao, L., and Zhu, W (2019) Ownership network and firm growth: What do five million companies tell about chinese economy self | 0.511 | 2 | 1 | 100% |
| 5 | Banerjee, A., Chandrasekhar, A. G., Duflo, E., and Jackson, M. O (2013) The diffusion of microfinance | 0.511 | 2 | 1 | 100% |
| 6 | Kleinberg, J. M (1999) Authoritative sources in a hyperlinked environment | 0.511 | 2 | 1 | 100% |
| 7 | Lakhina, A., Byers, J. W., Crovella, M., and Xie, P (2003) Sampling biases in IP topology measurements | 0.511 | 2 | 1 | 100% |
| 8 | Shabalin, A. A. and Nobel, A. B (2013) Reconstruction of a low-rank matrix in the presence of gaussian noise | 0.511 | 2 | 1 | 100% |
| 9 | Yang, Y. and Zhu, W (2020) Networks and business cycles self | 0.511 | 2 | 1 | 100% |
| 10 | Banerjee, D. and Ma, Z (2017) Optimal hypothesis testing for stochastic block models with growing degrees | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 89 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | 1 Linear Regression with Centrality Measures | 1.000 | 5 | 3 |
| 2 | Hypothesis testing on invariant subspaces of non-diagonalizable matrices with applications to network statistics | 0.405 | 1 | 1 |