fixes (version 0.4.1)

plot_es: 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"
)

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.

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.

Examples

if (FALSE) {
# 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")
}