Reducing Marketplace Interference Bias via Shadow Prices

References

• Ahuja RK, Magnanti TL, Orlin JB (1993) Chapter 9: Minimum-cost flows. Network Flows: Theory, Algorithms, and Applications (John Wiley & Sons, Ltd., Hoboken, NJ), 299.Google Scholar
• Bajari P, Burdick B, Imbens GW, Masoero L, McQueen J, Richardson T, Rosen IM (2021) Multiple randomization designs. Working paper, Stanford University, Stanford, CA.Google Scholar
• Blake T, Coey D (2014) Why marketplace experimentation is harder than it seems: The role of test-control interference. Proc. 15th ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 567–582.Google Scholar
• Bojinov I, Simchi-Levi D, Zhao J (2022) Design and analysis of switchback experiments. Management Sci. 69(7):3759–3777.Link, Google Scholar
• Chamandy N (2016) Experimentation in a ridesharing marketplace. Lyft Engineering Blog (September 2), https://eng.lyft.com/experimentation-in-a-ridesharing-marketplace-b39db027a66e.Google Scholar
• Chin A (2019) Regression adjustments for estimating the global treatment effect in experiments with interference. J. Causal Inference 7(2):1–36.Crossref, Google Scholar
• Cochran WG (1939) Long-term agricultural experiments. Supplement J. Roy. Statist. Soc. 6(2):104–148.Crossref, Google Scholar
• Fradkin A (2019) A simulation approach to designing digital matching platforms. Working paper, Boston University, Boston.Google Scholar
• Holtz D, Lobel F, Lobel R, Liskovich I, Aral S (2024) Reducing interference bias in online marketplace experiments using cluster randomization: Evidence from a pricing meta-experiment on Airbnb. Management Sci., ePub ahead of print April 5, https://doi.org/10.1287/mnsc.2020.01157.Google Scholar
• Johari R, Li H, Liskovich I, Weintraub GY (2022) Experimental design in two-sided platforms: An analysis of bias. Management Sci. 68(10):7069–7089.Link, Google Scholar
• Li H, Zhao G, Johari R, Weintraub GY (2022) Interference, bias, and variance in two-sided marketplace experimentation: Guidance for platforms. Proc. ACM Web Conf. (Association for Computing Machinery, New York), 182–192.Google Scholar
• Munro E, Wager S, Xu K (2021) Treatment effects in market equilibrium. Preprint, submitted September 23, https://arxiv.org/abs/2109.11647.Google Scholar
• New York City Taxi and Limousine Commission (2022) Trip record data. Accessed August 23, 2023, https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page.Google Scholar
• Sneider C, Tang Y (2019) Experiment rigor for switchback experiment analysis. Doordash Engineering Blog (February 20), https://doordash.engineering/2019/02/20/experiment-rigor-for-switchback-experiment-analysis/.Google Scholar
• Ugander J, Karrer B, Backstrom L, Kleinberg J (2013) Graph cluster randomization: Network exposure to multiple universes. Proc. 19th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (Association for Computing Machinery, New York), 329–337.Google Scholar
• Wager S, Xu K (2021) Experimenting in equilibrium. Management Sci. 67(11):6694–6715.Link, Google Scholar