Regression modelQuasi-experimental / causal inference
贝叶斯事件研究设计
贝叶斯事件研究设计通过用完整的贝叶斯推断框架取代频率学派的显著性检验，扩展了经典的事件研究框架。它通过从估计窗口学习先验模型并用观测数据更新它来估计事件（政策变化、公告、冲击）如何改变结果轨迹，从而产生具有完整不确定性量化的异常效应和累积因果影响的后验分布。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Sorescu, A., Warren, N. L., & Ertekin, L. (2017). Event study methodology in the marketing literature: An overview. Journal of the Academy of Marketing Science, 45(2), 186-207. DOI: 10.1007/s11747-017-0516-y ↗
- Glassman, M., & McAfee, R. B. (1996). Bayesian estimation of abnormal stock returns. Journal of Business & Economic Statistics, 10(3), 321-332. link ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Event Study Design for Causal Inference. ScholarGate. https://scholargate.app/zh/causal-inference/bayesian-event-study-design
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 贝叶斯双重差分法因果推断↔ compare
- 因果影响分析因果推断↔ compare
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- 中断时间序列（ITS）分析因果推断↔ compare
- 面板事件研究因果推断↔ compare