{
  "abstract": "Researchers frequently study interactions between two distinct types of actors, represented as bipartite networks. These networks exhibit dependence patterns that differ from those in one-mode networks and therefore require models tailored to their structure. This paper develops an additive and multiplicative effects (AME) framework for longitudinal bipartite data. First, I distinguish the dependence structure and specify the corresponding modeling assumptions. Second, I introduce the bipartite dynamic AME model and develop an estimation procedure based on block coordinate descent. Third, I incorporate a squared iterative method to improve computational efficiency. Using simulations and an application to global production networks, I show that the model improves coefficient estimation, more accurately recovers the data-generating process, and better captures the multiplicative latent structure. The model reveals evolving patterns in countries' global production engagement that are not captured by observed covariates or static specifications. I provide an R package, RAMEN, to facilitate implementation.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.00900",
  "author_total": 1,
  "authors": [
    {
      "name": "Jing Luo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ekmabmpashdm7.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.00900",
  "fulltext_url": null,
  "id": "ekmabmpashdm7",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.00900",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.SI"
    ],
    [
      "arxiv",
      "stat.ME"
    ],
    [
      "openalex",
      "3109|Complex Network Analysis Techniques"
    ]
  ],
  "openalex": "W7216491816",
  "pdf_url": "https://arxiv.org/pdf/2610.00900",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/ekmabmpashdm7.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:26:14Z",
      "native_id": "2610.00900",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.00900"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ME",
      "subfield": "statistics"
    }
  ],
  "title": "Modeling Bipartite Dynamic Networks: An Additive and Multiplicative Effects Model",
  "title_text": "Modeling Bipartite Dynamic Networks: An Additive and Multiplicative Effects Model",
  "type": "preprint",
  "updated_at": "2026-10-30T12:26:14Z",
  "url": "https://research.draconitic.com/paper/ekmabmpashdm7",
  "venue": "arXiv",
  "versions": []
}