| Identification and estimation of a partially linear regression model using network data E Auerbach Econometrica 90 (1), 347-365, 2022 | 90* | 2022 |
| Recovering Network Structure from Aggregated Relational Data using Penalized Regression H Alidaee, E Auerbach, MP Leung arXiv preprint arXiv:2001.06052, 2020 | 23 | 2020 |
| The Local Approach to Causal Inference under Network Interference E Auerbach, M Tabord-Meehan arXiv. org Papers, 2021 | 17* | 2021 |
| Testing for Differences in Stochastic Network Structure E Auerbach arXiv preprint arXiv:1903.11117, 2019 | 8* | 2019 |
| Identification and Estimation of a Partially Linear Regression Model using Network Data: Inference and an Application to Network Peer Effects E Auerbach arXiv preprint arXiv:2105.10002, 2021 | 3 | 2021 |
| Discussion of ‘Causal inference with misspecified exposure mappings: separating definitions and assumptions’ E Auerbach, J Auerbach, M Tabord-Meehan Biometrika 111 (1), 21-24, 2024 | 1 | 2024 |
| Digitization and Employment in the Pandemic: Evidence from Seventy Billion Emails S Peng, P Wang, E Auerbach, H Liang, A Wu | 1 | 2021 |
| Exposure effects are policy relevant only under strong assumptions about the interference structure E Auerbach, J Auerbach, M Tabord-Meehan arXiv preprint arXiv:2401.06264, 2024 | | 2024 |
| Identifying Socially Disruptive Policies E Auerbach, Y Cai arXiv preprint arXiv:2306.15000, 2023 | | 2023 |
| Heterogeneous Treatment Effects for Networks, Panels, and other Outcome Matrices E Auerbach, Y Cai arXiv preprint arXiv:2205.01246, 2022 | | 2022 |
Max Tabord-MeehanUniversity of ChicagoVerified email at uchicago.edu
