NRDD: Nonlinear RDD estimator

In NonlinearRDD: Nonlinear Regression Discontinuity Design

Nonlinear RDD estimator

Description

Semiparametric estimation of the possibly nonlinear and nonseparable structural function in regression discontinuity designs with a continuous treatment variable

Usage

NRDD(
  df,
  b1 = 2 * nrow(df)^{
     -1/5
 },
  b2 = 2 * nrow(df)^{
     -1/5
 },
  b3 = 2 * nrow(df)^{
     -1/5
 },
  t_tilde = stats::median(df[, 2]),
  e_space,
  Nonseparable = TRUE
)

Arguments

df	Data frame whose columns are outcome Y, treatment Treat, and running variable R, respectively.
b1	Bandwidth for the local linear estimation of the conditional distribution of Y given T,R. Default is n^(-1/5), where n is the sample size.
b2	Bandwidth for the smoothing of the indicator function 1(Y <= y).
b3	Bandwidth for the first-step conditional quantile estimation of T given R.
t_tilde	Normalization constant in the structural function.
e_space	The space of epsilon on which the numerical integration is conducted.
Nonseparable	Whether the structural function should be estimated as a separable or nonseparable function of the treatment. The default is TRUE.

Value

The estimated parameters in the structural function.

Examples

n <- 20
set.seed(123)
Treat <- runif(n)
R <- runif(n)-0.5
epsilon <- Treat^2 + R
Y <- Treat + R + epsilon
df <- data.frame(Y=Y,Treat=Treat,R=R)
NRDD(df,e_space = seq(0,1,by=0.5),Nonseparable=FALSE)


n <- 500
set.seed(123)
data <- nrddgp(n)
NRDD(data,e_space = seq(-10,10,by=1))

NonlinearRDD documentation built on Nov. 26, 2023, 5:07 p.m.