prep_data_for_fit {bunching}

Data Preparation

Description

Prepare binned data and model for bunching estimation.

Usage

prep_data_for_fit(
  data_binned,
  zstar,
  binwidth,
  bins_l,
  bins_r,
  poly = 9,
  bins_excl_l = 0,
  bins_excl_r = 0,
  rn = NA,
  extra_fe = NA,
  correct_above_zu = FALSE
)

Arguments

data_binned

dataframe of counts per bin

zstar

a numeric value for the the bunching point.

binwidth

a numeric value for the width of each bin.

bins_l

number of bins to left of zstar to use in analysis.

bins_r

number of bins to right of zstar to use in analysis.

poly

a numeric value for the order of polynomial for counterfactual fit. Default is 9.

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.

rn

a numeric vector of (up to 2) round numbers to control for. Default includes no controls.

extra_fe

a numeric vector of bin values to control for using fixed effects. Default includes no controls.

correct_above_zu

if integration constraint correction is implemented, should counterfactual be shifted only above zu (upper bound of exclusion region)? Default is FALSE (i.e. shift from above zstar).

Value

data_binned returns a list with the following:

data_binned

The binned data with the extra columns necessary for model fitting, such as indicators for bunching region, fixed effects, etc.

model_formula

The formula used for model fitting.

See Also

bunchit

Examples

data(bunching_data)
binned_data <- bin_data(z_vector = bunching_data$kink, zstar = 10000,
                        binwidth = 50, bins_l = 20, bins_r = 20)
prepped_data <- prep_data_for_fit(binned_data, zstar = 10000, binwidth = 50,
                                  bins_l = 20, bins_r = 20, poly = 4,
                                  bins_excl_l = 2, bins_excl_r = 3,
                                  rn = c(250,500), extra_fe = 10200)
head(prepped_data$data_binned)
prepped_data$model_formula