Mahyar Habibi, Zahra Khanalizadeh, Negar Ziaeian
arXiv 13 Feb 2025 · Econometrics
arXiv:2502.09806 · PDF · DOI · OpenAlex · Extracted main text
Interdependencies between units in online two-sided marketplaces complicate estimating causal effects in experimental settings. We propose a novel experimental design to mitigate the interference bias in estimating the total average treatment effect (TATE) of item-side interventions in online two-sided marketplaces. Our Two-Sided Prioritized Ranking (TSPR) design uses the recommender system as an instrument for experimentation. TSPR strategically prioritizes items based on their treatment status in the listings displayed to users. We designed TSPR to provide users with a coherent platform experience by ensuring access to all items and a consistent realization of their treatment by all users. We evaluate our experimental design through simulations using a search impression dataset from an online travel agency. Our methodology closely estimates the true simulated TATE, while a baseline item-side estimator significantly overestimates TATE.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Goli, Lambrecht \ Yoganarasimhan (2024) `A bias correction approach for interference in ranking experiments', Marketing Science 43(3), 590–614 | 0.737 | 3 | 2 | 100% |
| 2 | Hudgens \ Halloran (2008) `Toward causal inference with interference', Journal of the american statistical association 103(482), 832–842 | 0.737 | 3 | 2 | 100% |
| 3 | Craswell, Zoeter, Taylor \ Ramsey (2008) An experimental comparison of click position-bias models, in `Proceedings of the 2008 international conference on web search and… | 0.644 | 2 | 2 | 100% |
| 4 | Holtz, Lobel, Lobel, Liskovich \ Aral (2024) `Reducing interference bias in online marketplace experiments using cluster randomization: Evidence from a pricing meta-experime… | 0.644 | 2 | 2 | 100% |
| 5 | Manski (2013) `Identification of treatment response with social interactions', The Econometrics Journal 16(1), S1–S23 | 0.644 | 2 | 2 | 100% |
| 6 | Munro, Kuang \ Wager (2024) `Treatment effects in market equilibrium' | 0.644 | 2 | 2 | 100% |
| 7 | Blake \ Coey (2014) Why marketplace experimentation is harder than it seems: the role of test-control interference, in `Proceedings of the Fifteenth… | 0.511 | 2 | 1 | 100% |
| 8 | Aronow \ Samii (2017) `Estimating average causal effects under general interference, with application to a social network experiment' | 0.405 | 1 | 1 | 100% |
| 9 | Bajari, Burdick, Imbens, Masoero, McQueen, Richardson \ Rosen (2023) `Experimental design in marketplaces', Statistical Science 38(3), 458–476 | 0.405 | 1 | 1 | 100% |
| 10 | Barlow (1972) `Statistical inference under order restrictions: The theory and application of isotonic regression', (No Title) | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 49 scored citations.