Hossein Alidaee, Eric Auerbach, Michael P. Leung
arXiv 16 Jan 2020 · Econometrics · 14 citations (OpenAlex)
arXiv:2001.06052 · PDF · DOI · OpenAlex · Extracted main text
Social network data can be expensive to collect. Breza et al. (2017) propose aggregated relational data (ARD) as a low-cost substitute that can be used to recover the structure of a latent social network when it is generated by a specific parametric random effects model. Our main observation is that many economic network formation models produce networks that are effectively low-rank. As a consequence, network recovery from ARD is generally possible without parametric assumptions using a nuclear-norm penalized regression. We demonstrate how to implement this method and provide finite-sample bounds on the mean squared error of the resulting estimator for the distribution of network links. Computation takes seconds for samples with hundreds of observations. Easy-to-use code in R and Python can be found at https://github.com/mpleung/ARD.
appendix boundary found by appendix_command · 73% of the source is main text. Read the extracted text to check this.
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 | Breza, Chandrasekhar, McCormick and Pan (2017) Using Aggregated Relational Data to feasibly identify network structure without network data | 1.000 | 16 | 5 | 100% |
| 2 | Negahban and Wainwright (2011) Estimation of (near) low-rank matrices with noise and high-dimensional scaling | 0.874 | 9 | 5 | 67% |
| 3 | Ji and Ye (2009) An accelerated gradient method for trace norm minimization | 0.843 | 5 | 4 | 60% |
| 4 | Hoff, Raftery and Handcock (2002) Latent Space Approaches to Social Network Analysis | 0.644 | 2 | 2 | 100% |
| 5 | Wainwright (2015) High-dimensional statistics: A non-asymptotic viewpoint | 0.644 | 2 | 2 | 100% |
| 6 | Abbe (2017) Community detection and stochastic block models: recent developments | 0.405 | 1 | 1 | 100% |
| 7 | Athey, Bayati, Doudchenko, Imbens and Khosravi (2018) Matrix completion methods for causal panel data models | 0.405 | 1 | 1 | 100% |
| 8 | Athreya, Fishkind, Tang, Priebe, Park, Vogelstein, Levin, Lyzinski a… (2017) Statistical inference on random dot product graphs: a survey | 0.405 | 1 | 1 | 100% |
| 9 | Banerjee, Chandrasekhar, Duflo and Jackson (2013) The diffusion of microfinance | 0.405 | 1 | 1 | 100% |
| 10 | Barigozzi and Brownlees (2018) Nets: Network estimation for time series | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 28 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.