Plot Event Study Coefficients from Multiple Estimators — plot_event

Creates a combined coefficient plot comparing event study estimates from multiple estimators (e.g., TWFE, Sun-Abraham, Callaway-Sant'Anna, Gardner). This is useful for showing robustness of dynamic treatment effects across different estimation strategies.

Usage

plot_event_coefs(
  estimates,
  reference_period = -1,
  conf_level = 0.95,
  title = NULL,
  xlab = "Periods Relative to Treatment",
  ylab = "Estimate"
)

Arguments

estimates: A named list of data frames, each with columns term (relative time period), estimate, and std_error. The names of the list become the legend labels.
reference_period: Numeric. The reference period (omitted category). Default is -1.
conf_level: Numeric. Confidence level for error bars. Default is 0.95.
title: Character string. Plot title. Default is NULL.
xlab: Character string. X-axis label. Default is "Periods Relative to Treatment".
ylab: Character string. Y-axis label. Default is "Estimate".

Value

A ggplot2 object.

Examples

if (FALSE) { # \dontrun{
# After running different estimators:
estimates <- list(
  "TWFE" = data.frame(term = -5:5, estimate = rnorm(11), std_error = 0.1),
  "Sun-Abraham" = data.frame(term = -5:5, estimate = rnorm(11), std_error = 0.1)
)
plot_event_coefs(estimates)
} # }