plot_bunching {bunching}

Bunching Plot

Description

Creates the bunching plot.

Usage

plot_bunching(
  z_vector,
  binned_data,
  cf,
  zstar,
  binwidth,
  bins_excl_l = 0,
  bins_excl_r = 0,
  p_title = "",
  p_xtitle = deparse(substitute(z_vector)),
  p_ytitle = "Count",
  p_miny = 0,
  p_maxy = NA,
  p_ybreaks = NA,
  p_title_size = 11,
  p_axis_title_size = 10,
  p_axis_val_size = 8.5,
  p_freq_color = "black",
  p_cf_color = "maroon",
  p_zstar_color = "red",
  p_grid_major_y_color = "lightgrey",
  p_freq_size = 0.5,
  p_freq_msize = 1,
  p_cf_size = 0.5,
  p_zstar_size = 0.5,
  p_b = FALSE,
  b = NA,
  b_sd = NA,
  p_e = FALSE,
  e = NA,
  e_sd = NA,
  p_b_e_xpos = NA,
  p_b_e_ypos = NA,
  p_b_e_size = 3,
  t0 = NA,
  t1 = NA,
  notch = FALSE,
  p_domregion_color = NA,
  p_domregion_ltype = NA
)

Arguments

z_vector

a numeric vector of (unbinned) data.

binned_data

binned data with frequency and estimated counterfactual.

cf

the counterfactual to be plotted.

zstar

a numeric value for the the bunching point.

binwidth

a numeric value for the width of each bin.

bins_excl_l

number of bins to left of zstar to include in bunching region. Default is 0.

bins_excl_r

number of bins to right of zstar to include in bunching region. Default is 0.

p_title

plot's title. Default is empty.

p_xtitle

plot's x_axis label. Default is the name of z_vector.

p_ytitle

plot's y_axis label. Default is "Count".

p_miny

plot's minimum y_axis value. Default is 0.

p_maxy

plot's maximum y_axis value. Default is optimized internally.

p_ybreaks

a numeric vector of y-axis values at which to add horizontal line markers in plot. Default is optimized internally.

p_title_size

size of plot's title. Default is 11.

p_axis_title_size

size of plot's axes' title labels. Default is 10.

p_axis_val_size

size of plot's axes' numeric labels. Default is 8.5.

p_freq_color

plot's frequency line color. Default is "black".

p_cf_color

plot's counterfactual line color. Default is "maroon".

p_zstar_color

plot's bunching region marker lines color. Default is "red".

p_grid_major_y_color

plot's y-axis major grid line color. Default is "lightgrey".

p_freq_size

plot's frequency line thickness. Default is 0.5.

p_freq_msize

plot's frequency line marker size. Default is 1.

p_cf_size

plot's counterfactual line thickness. Default is 0.5.

p_zstar_size

plot's bunching region marker line thickness. Default is 0.5.

p_b

whether plot should also include the bunching estimate. Default is FALSE.

b

normalized bunching estimate.

b_sd

standard deviation of the normalized bunching estimate.

p_e

whether plot should also include the elasticity estimate. Only shown if p_b is TRUE. Default is FALSE.

e

elasticity estimate.

e_sd

standard deviation of the elasticity estimate.

p_b_e_xpos

plot's x-axis coordinate of bunching/elasticity estimate. Default is set internally.

p_b_e_ypos

plot's y-axis coordinate of bunching/elasticity estimate. Default is set internally.

p_b_e_size

size of plot's printed bunching/elasticity estimate. Default is 3.

t0

numeric value setting the marginal (average) tax rate below zstar in a kink (notch) setting.

t1

numeric value setting the marginal (average) tax rate above zstar in a kink (notch) setting.

notch

whether analysis is for a kink or notch. Default is FALSE (kink).

p_domregion_color

plot's dominated region marker line color in notch setting. Default is "blue".

p_domregion_ltype

line type for the vertical line type marking the dominated region (zD) in the plot for notch settings. Default is "longdash".

Value

plot_bunching returns a plot with the frequency, counterfactual and bunching region demarcated. Can also include the bunching and elasticity estimate if specified.

See Also

bunchit

Examples

data(bunching_data)
binned_data <- bin_data(z_vector = bunching_data$kink, zstar = 10000,
                        binwidth = 50, bins_l = 20, bins_r = 20)
prepped_data <- prep_data_for_fit(binned_data, zstar = 10000, binwidth = 50,
                                  bins_l = 20, bins_r = 20, poly = 4)
fitted <- fit_bunching(thedata = prepped_data$data_binned,
                       themodelformula = prepped_data$model_formula,
                       binwidth = 50)
plot_bunching(z_vector = bunching_data$kink_vector,
              binned_data = prepped_data$data_binned,
              cf = fitted$cf_density, zstar = 10000,
              binwidth = 50, bins_excl_l = 0 , bins_excl_r = 0,
              b = 1.989, b_sd = 0.005, p_b = TRUE)