arXiv 22 Feb 2024 · Statistics — Applications
arXiv:2402.14538 · PDF · DOI · OpenAlex · Extracted main text
It is standard practice in online retail to run pricing experiments by randomizing at the article-level, i.e. by changing prices of different products to identify treatment effects. Due to customers' cross-price substitution behavior, such experiments suffer from interference bias: the observed difference between treatment groups in the experiment is typically significantly larger than the global effect that could be expected after a roll-out decision of the tested pricing policy. We show in simulations that such bias can be as large as 100%, and report experimental data implying bias of similar magnitude. Finally, we discuss approaches for de-biased pricing experiments, suggesting observational methods as a potentially attractive alternative to clustering.
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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 | Cooprider el al., “Science of price experimentation at Amazon”. AEA (2023) | 0.644 | 2 | 2 | 100% |
| 2 | Karrer et al., “Network Experimentation at Scale”. Proceedings of th… (2021) | 0.644 | 2 | 2 | 100% |
| 3 | Bajari et al., “Experimentation in Marketplaces”. Statistical Science (2023) | 0.405 | 1 | 1 | 100% |
| 4 | Berman et al., “False Discovery in A/B Testing”. Management Science… (2022) | 0.405 | 1 | 1 | 100% |
| 5 | Brandes et al., "On Modularity Clustering". IEEE Transactions on Kno… (2008) | 0.405 | 1 | 1 | 100% |
| 6 | Eckles et al. “Design and Analysis of Experiments in Networks: Reduc… (2016) | 0.405 | 1 | 1 | 100% |
| 7 | Holtz et al., "Reducing interference bias in online marketplace pric… (2020) | 0.405 | 1 | 1 | 100% |
Showing the top 7 of 7 scored citations.