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Abstract The problem of analyzing interconnectedness is one of today’s premier challenges in understanding systemic risk. Connections can both stabilize networks and provide pathways for contagion. The central problem in such networks is establishing global behavior from local interactions. Jiang-Lim-Yao-Ye (Jianget al2011Mathematical Programming 1271203–244) recently introduced the use of theHodge decomposition(see Lim 2020SIAM Review62685–715 for a review), a fundamental tool from algebraic geometry, to construct global rankings from local interactions (see Barbarossaet al2018(2018 IEEE Data Science Workshop (DSW), IEEE)pp 51–5; Haruna and Fujiki 2016Frontiers in Neural Circuits1077; Jiaet al2019(Proc. of the XXV ACM SIGKDD International Conf. on Knowledge Discovery & Data Mining, pp 761–71 for other applications). We apply this to a study of financial networks, starting from the Eisenberg-Noe (Eisenberg and Noe 2001Management Science47236–249) setup of liabilities and endowments, and construct a network of defaults. We then use Jiang-Lim-Yao-Ye to construct a global ranking from the defaults, which yields one way of quantifying ‘systemic importance’.
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This content will become publicly available on March 25, 2026
The file drawer problem in social science survey experiments
The file drawer problem—often operationalized in terms of statistically significant results being published and statistically insignificant not being published—is widely documented in the social sciences. We extend Franco’s et al. [Science345, 1502–1505(2014)] seminal study of the file drawer problem in survey experiments submitted to the Time-sharing Experiments for the Social Sciences (TESS) data collection program. We examine projects begun after Franco et al. The updated period coincides with the contemporary open science movement. We find evidence of the problem, stemming from scholars opting to not write up insignificant results. However, that tendency is substantially smaller than it was in the prior decade. This suggests increased recognition of the importance of null results, even if the problem remains in the domain of survey experiments.
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- Award ID(s):
- 2017464
- PAR ID:
- 10634364
- Publisher / Repository:
- National Academy of Sciences
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 122
- Issue:
- 12
- ISSN:
- 0027-8424
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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