rdmulti (version 0.2)

rdms: Analysis of RD designs with cumulative cutoffs or two running variables

Description

rdms() analyzes RD designs with cumulative cutoffs or two running variables.

Usage

rdms(Y, X, C, X2 = NULL, zvar = NULL, C2 = NULL, range.l = NULL,
  range.r = NULL, xnorm = NULL, pooled.opt = NULL, hvec = NULL,
  bvec = NULL, pvec = NULL, kernelvec = NULL, fuzzy = NULL,
  plot = FALSE)

Arguments

Y

outcome variable.

X

running variable.

C

vector of cutoffs.

X2

if specified, second running variable.

zvar

if X2 is specified, treatment indicator.

C2

if specified, second vector of cutoffs.

range.l

range of the running variable to be used for estimation around the cutoff from the left.

range.r

range of the running variable to be used for estimation around the cutoff from the right.

xnorm

normalized running variable to estimate pooled effect.

pooled.opt

options to be passed to rdrobust() to calculate pooled estimand.

hvec

bandwidths to be passed to rdrobust() to calculate cutoff-specific estimates. Should be a vector of length equal to the number of different cutoffs.

bvec

bandwidths for the bias to be passed to rdrobust() to calculate cutoff-specific estimates. Should be a vector of length equal to the number of different cutoffs.

pvec

order of the polynomials to be passed to rdrobust() to calculate cutoff-specific estimates. Should be a vector of length equal to the number of different cutoffs.

kernelvec

kernels to be passed to rdrobust() to calculate cutoff-specific estimates.Should be a vector of length equal to the number of different cutoffs.

fuzzy

specifies a fuzzy design.

plot

plots cutoff-specific estimates and weights.

Value

B

vector of bias-corrected coefficients

V

variance-covariance matrix of the estimators

Coefs

vector of conventional coefficients

Nh

vector of sample sizes within bandwidth at each cutoff

CI

bias corrected confidence intervals

H

bandwidth used at each cutoff

References

M.D. Cattaneo, R. Titiunik and G. Vazquez-Bare. (2018). Analysis of Regression Discontinuity Designs with Multiple Cutoffs or Multiple Scores. Working paper, University of Michigan.

Examples

# NOT RUN {
# Toy dataset: cumulative cutoffs
X <- runif(1000,0,100)
C <- c(33,66)
Y <- (1+X)*(X<C[1])+(0.8+0.8*X)*(X>=C[1]&X<C[2])+(1.2+1.2*X)*(X>=C[2]) + rnorm(1000)
# rmds: basic syntax
tmp <- rdms(Y,X,C)


# }