Regression modelQuasi-experimental / causal inference

Bayesian Panel Event Study

Bayesian Panel Event Study is a causal inference design that estimates dynamic treatment effects around a datable event using panel data, replacing classical frequentist estimation with Bayesian posterior inference. It produces period-by-period effect estimates with full probability distributions, enabling principled uncertainty quantification, regularization of noisy pre-trend coefficients, and probabilistic tests of parallel trends.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Freyaldenhoven, S., Hansen, C., Shapiro, J. M., & Teso, E. (2021). Visualization, Identification, and Estimation in the Linear Panel Event-Study Design. NBER Working Paper No. 29170. National Bureau of Economic Research. link
  2. Jakiela, P. (2021). Simple Diagnostics for Two-Way Fixed Effects. Working Paper. Center for Global Development. link

Related methods

ScholarGateBayesian Panel Event Study (Bayesian Panel Event Study Design). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/bayesian-panel-event-study