View source: R/plot_bunching.R

plot_bunching | R Documentation |

Creates the bunching plot.

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 )

`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". |

`plot_bunching`

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

`bunchit`

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)

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