arXiv 21 Aug 2024 · Econometrics
arXiv:2408.11951 · PDF · DOI · OpenAlex · Extracted main text
Randomized controlled trials (RCTs) have long been the gold standard for causal inference across various fields, including business analysis, economic studies, sociology, clinical research, and network learning. The primary advantage of RCTs over observational studies lies in their ability to significantly reduce noise from individual variance. However, RCTs depend on strong assumptions, such as group independence, time independence, and group randomness, which are not always feasible in real-world applications. Traditional inferential methods, including analysis of covariance (ANCOVA), often fail when these assumptions do not hold. In this paper, we propose a novel approach named Spillover Time Series Causal (\verb+SPORTSCausal+), which enables the estimation of treatment effects without relying on these stringent assumptions. We demonstrate the practical applicability of \verb+SPORTSCausal+ through a real-world budget-control experiment. In this experiment, data was collected from both a 5% live experiment and a 50% live experiment using the same treatment. Due to the spillover effect, the vanilla estimation of the treatment effect was not robust across different treatment sizes, whereas \verb+SPORTSCausal+ provided a robust estimation.
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| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Z. Zheng and C. Liu (2024) Bootstrap matching: a robust and efficient correction for non-random a/b test, and its applications | 0.811 | 4 | 2 | 100% |
| 2 | K. H. Brodersen, F. Gallusser, J. Koehler, N. Remy, S. L. Scott, et al (2015) Inferring causal impact using bayesian structural time-series models | 0.644 | 2 | 2 | 100% |
| 3 | D. B. Rubin (1986) Comment: Which ifs have causal answers | 0.511 | 2 | 1 | 100% |
| 4 | A. Abadie, A. Diamond, and J. Hainmueller (2010) Synthetic control methods for comparative case studies: Estimating the effect of california’s tobacco control program | 0.405 | 1 | 1 | 100% |
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| 8 | J. V. Bradley (1958) Complete counterbalancing of immediate sequential effects in a latin square design | 0.405 | 1 | 1 | 100% |
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