plot_es: Plot Event Study Results

In fixes: Tools for Creating and Visualizing Fixed-Effects Event Study Models

Plot Event Study Results

Description

This function creates a plot for event study results using 'ggplot2'. Users can choose between ribbon-style confidence intervals or error bars to visualize the estimates and their uncertainty.

Usage

plot_es(
  data,
  type = "ribbon",
  vline_val = 0,
  vline_color = "#000",
  hline_val = 0,
  hline_color = "#000",
  linewidth = 1,
  pointsize = 2,
  alpha = 0.2,
  barwidth = 0.2,
  color = "#B25D91FF",
  fill = "#B25D91FF"
)

Arguments

data	A dataframe containing the results from the 'run_es' function. The dataframe must include the following columns: - 'relative_time': The scaled time relative to the treatment. - 'estimate': The estimated coefficients. - 'conf_low': The lower bound of the 95 - 'conf_high': The upper bound of the 95 - 'std.error': The standard errors (required if 'type = "errorbar"').
type	The type of confidence interval visualization: "ribbon" (default) or "errorbar". - "ribbon": Shaded area representing the confidence intervals. - "errorbar": Vertical error bars for each estimate.
vline_val	The x-intercept for the vertical reference line (default: 0). Typically represents the time of treatment.
vline_color	The color of the vertical reference line (default: "#000").
hline_val	The y-intercept for the horizontal reference line (default: 0). Usually represents the null effect line.
hline_color	The color of the horizontal reference line (default: "#000").
linewidth	The width of the lines in the plot (default: 1).
pointsize	The size of the points for the estimates (default: 2).
alpha	The transparency level for the ribbon (default: 0.2).
barwidth	The width of the error bars (default: 0.2).
color	The color of the lines and points (default: "#B25D91FF").
fill	The fill color for the ribbon (default: "#B25D91FF").

Details

This function provides a flexible visualization tool for event study results. Users can customize the appearance of the plot by adjusting the parameters for line styles, point sizes, colors, and confidence interval types.

**Column Requirements**: The input dataframe ('data') must include: - 'relative_time': A numeric column for the time relative to the treatment. - 'estimate': The estimated coefficients for each relative time. - 'conf_low' and 'conf_high': The bounds of the confidence intervals. - 'std.error': The standard errors (only required if 'type = "errorbar"').

**Type Options**: - '"ribbon"': A shaded area to represent the confidence intervals. - '"errorbar"': Error bars for each point. Standard errors ('std.error') are required.

Value

A ggplot object displaying the event study results. The plot includes: - A line connecting the estimates over relative time. - Points for the estimated coefficients. - Either ribbon-style confidence intervals or error bars, depending on 'type'. - Vertical and horizontal reference lines for better interpretability.

Note

If 'type = "errorbar"', ensure that the 'std.error' column is present in the input dataframe. Missing values in the 'std.error' column for any term will result in incomplete confidence intervals.

Examples

# Simulate panel data
df <- tibble::tibble(
  firm_id = rep(1:50, each = 10),  # 50 firms over 10 years
  state_id = rep(sample(1:10, size = 50, replace = TRUE), each = 10),
  year = rep(2000:2009, times = 50),
  is_treated = rep(sample(c(1, 0), size = 50, replace = TRUE, prob = c(0.5, 0.5)), each = 10),
  y = rnorm(500, mean = 0, sd = 1)  # Simulated outcome variable
)

# Run event study
event_study <- run_es(
  data       = df,
  outcome    = y,
  treatment  = is_treated,
  time       = year,
  timing     = 2005,
  lead_range = 5,              # Corresponds to years 2000-2004 (relative time: -5 to -1)
  lag_range  = 4,              # Corresponds to years 2006-2009 (relative time: 1 to 4)
  fe         = firm_id + year,
  cluster    = "state_id",
  baseline   = -1,
  interval   = 1
)

# Basic plot
plot_es(event_study)

# Use error bars instead of ribbon confidence intervals
plot_es(event_study, type = "errorbar")

# Adjust vertical reference line
plot_es(event_study, type = "errorbar", vline_val = -0.5)

# Customize axis breaks and title
library(ggplot2)
plot_es(event_study, type = "errorbar") +
  ggplot2::scale_x_continuous(breaks = seq(-5, 4, by = 1)) +
  ggplot2::ggtitle("Result of Event Study")

fixes documentation built on April 3, 2025, 6:08 p.m.