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The Double Diagonal Estimator: Reducing Bias in Two-Sided Marketplace Experiments — arXiv:2610.41294

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.41294
License (as archived): CC0-1.0
Archived: 2026-11-02T08:13:42.355Z
SHA-256 of the archived text: 39bdad2c10c2d307c5fabb8e4411c1fef775e34de6236d8a32fbe85519e817fb
Stable URL of this page: https://metraipolis.com/documento/dc_2cdcbf0de226

How to cite

The Double Diagonal Estimator: Reducing Bias in Two-Sided Marketplace Experiments — arXiv:2610.41294 — arXiv (en), https://arxiv.org/abs/2610.41294 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_2cdcbf0de226 (Metraipolis archive dc_2cdcbf0de226, sha256 39bdad2c10c2d307c5fabb8e4411c1fef775e34de6236d8a32fbe85519e817fb)

BibTeX

@misc{dc2cdcbf0de226,
  title = {The Double Diagonal Estimator: Reducing Bias in Two-Sided Marketplace Experiments — arXiv:2610.41294},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.41294},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_2cdcbf0de226; sha256 39bdad2c10c2d307c5fabb8e4411c1fef775e34de6236d8a32fbe85519e817fb},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.41294. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Interference between participants in two-sided marketplace experiments can severely bias conventional A/B tests. While two-sided randomization (TSR), which randomizes both supply and demand, enables estimators that mitigate this bias, existing analyses offer limited guidance on which estimator to prefer for the balanced market conditions common in practice, as they largely focus on extreme supply- or demand-constrained regimes. We introduce the Double Diagonal (DD) estimator, a novel method for interference-robust treatment effect estimation. The DD estimator contrasts the outcomes of treated-treated and control-control pairs and uses the off-diagonal interactions (treated-control and control-treated) to correct for interference-induced bias. We provide the first theoretical comparison between the DD and the standard naive TSR (TSRN) estimator under a simplifying mean-field market model, proving two key results: (i) DD's bias is strictly smaller than the standard estimator's below a critical threshold of the outside-option parameter; in particular, DD's bias is smaller whenever the outside option is at most twice as attractive as platform options; and (ii) the two estimators exhibit biases in opposite directions, with DD underestimating and the standard estimator overestimating the true effect, respectively. Extensive numerical experiments in realistic market settings--spanning heterogeneous treatment effects, supply-demand imbalances, and varied market structures--corroborate our theoretical findings. Across a wide range of configurations, the DD estimator demonstrates the lowest bias, establishing it as a robust and often superior choice for reliable experimentation in two-sided marketplaces.

Tema degli esploratori: economia dei servizi IA (elenco arXiv econ.EM, nuovi lavori del giorno).
Categorie arXiv: Econometrics (econ.EM).
Pagina del lavoro: https://arxiv.org/abs/2610.41294 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-02T07:52:15.875Z dalla pagina https://arxiv.org/list/econ.EM/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).