| title | Wasserstein-Barycentric Interaction Fields for Spatial Factor Models: Evidence from Language-Model Representations |
|---|---|
| authors | Marcus Gawronsky, Chun-Sung Huang |
| date | 2026-08-30 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2608.29669 |
| affiliation | University of Cape Town |
| upvotes | 2 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf |
| abstract | Spatial return models take the interaction matrix as given and leave feedback uninterpreted. We construct a bandwidth-free field from firms' language-model article embedding distributions using target-anchored Wasserstein barycentric reconstruction. A quadratic exposure-adjustment problem maps feedback into a peer-misalignment penalty ratio. For 52 firms, the field, frozen from 2018-2022 news, yields a 2023-2026 penalty ratio of 3.46 (95% interval [2.89, 4.17]) and higher conditional quasi-likelihood than equal-weighted peer support or RBF weighting of the same distances. Joint penalty ratios for the barycentric and news co-mention fields are 2.33 and 0.86 with boundary calibrated tests which reject both exclusions. |
cite
@misc{gawronsky2026wasserstein,
title={Wasserstein-Barycentric Interaction Fields for Spatial Factor Models: Evidence from Language-Model Representations},
author={Marcus Gawronsky and Chun-Sung Huang},
year={2026},
eprint={2608.29669},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2608.29669}
}