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Report NEP-NET-2023-11-20
This is the archive for NEP-NET, a report on new working papers in the area of Network Economics. Alfonso Rosa-García (Alfonso Rosa-Garcia) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-NET
The following items were announced in this report:
- Luca Mungo & Alexandra Brintrup & Diego Garlaschelli & Franc{c}ois Lafond, 2023, "Reconstructing supply networks," Papers, arXiv.org, number 2310.00446, Sep.
- Gary W. Cox & Jon H. Fiva & Max-Emil M. King, 2023, "Bound by Borders: Voter Mobilization through Social Networks," CESifo Working Paper Series, CESifo, number 10718.
- Yuanrong Wang & Antonio Briola & Tomaso Aste, 2023, "Topological Portfolio Selection and Optimization," Papers, arXiv.org, number 2310.14881, Oct.
- John List & Fatemeh Momeni & Michael Vlassopoulos & Yves Zenou, 2023, "The Social Side of Early Human Capital Formation: Using a Field Experiment to Estimate the Causal Impact of Neighborhoods," Framed Field Experiments, The Field Experiments Website, number 00722.
- Tamas David-Barrett, 2023, "Network Ecology of Marriage," Papers, arXiv.org, number 2310.05928, Aug.
- Davide Viviano & Lihua Lei & Guido Imbens & Brian Karrer & Okke Schrijvers & Liang Shi, 2023, "Causal clustering: design of cluster experiments under network interference," Papers, arXiv.org, number 2310.14983, Oct, revised Jan 2025.
- Shijia Song & Handong Li, 2023, "Unveiling Early Warning Signals of Systemic Risks in Banks: A Recurrence Network-Based Approach," Papers, arXiv.org, number 2310.10283, Oct.
- Nail Kashaev & Natalia Lazzati & Ruli Xiao, 2023, "Peer Effects in Consideration and Preferences," Papers, arXiv.org, number 2310.12272, Oct, revised Feb 2026.
- Emmet Hall-Hoffarth, 2023, "Non-linear approximations of DSGE models with neural-networks and hard-constraints," Papers, arXiv.org, number 2310.13436, Oct.
- Xie, Gang & Wang, Bing & Manyweathers, Jennifer, 2023, "A novel Bayesian Network modelling approach that can ideally represent the information contained in a set of sample data," SocArXiv, Center for Open Science, number gqud3, Oct, DOI: 10.31219/osf.io/gqud3.