Nothing
# Bootrstapped "Traditional" Doubly Robust Difference-in-Differences
# 2 periods and 2 groups
wboot_drdid_rc <- function(nn, n, y, post, D, int.cov, i.weights){
#-----------------------------------------------------------------------------
v <- stats::rexp(n)
#v <- v / mean(v)
#weights for the bootstrap
b.weights <- as.vector(i.weights * v)
# Propensity score estimation
ps.b <- suppressWarnings(stats::glm(D ~ -1 + int.cov, family = "binomial", weights = b.weights)$fitted.values)
ps.b <- as.vector(ps.b)
ps.b <- pmin(ps.b, 1 - 1e-16)
#Compute the Outcome regression for the control group at the pre-treatment period, using ols.
reg.coeff.pre.b <- stats::coef(stats::lm(y ~ -1 + int.cov,
subset = ((D==0) & (post==0)),
weights = b.weights))
out.y.cont.pre.b <- as.vector(tcrossprod(reg.coeff.pre.b, int.cov))
#Compute the Outcome regression for the control group at the pre-treatment period, using ols.
reg.coeff.post.b <- stats::coef(stats::lm(y ~ -1 + int.cov,
subset = ((D==0) & (post==1)),
weights = b.weights))
out.y.cont.post.b <- as.vector(tcrossprod(reg.coeff.post.b, int.cov))
#Compute the Outcome regression for the treated group at the pre-treatment period, using ols.
reg.treat.coeff.pre.b <- stats::coef(stats::lm(y ~ -1 + int.cov,
subset = ((D==1) & (post==0)),
weights = b.weights))
out.y.treat.pre.b <- as.vector(tcrossprod(reg.treat.coeff.pre.b, int.cov))
#Compute the Outcome regression for the treated group at the post-treatment period, using ols.
reg.treat.coeff.post.b <- stats::coef(stats::lm(y ~ -1 + int.cov,
subset = ((D==1) & (post==1)),
weights = b.weights))
out.y.treat.post.b <- as.vector(tcrossprod(reg.treat.coeff.post.b, int.cov))
# Compute AIPW estimator
att.b <- aipw_did_rc(y, post, D, ps.b,
out.y.treat.post.b, out.y.treat.pre.b,
out.y.cont.post.b, out.y.cont.pre.b,
b.weights)
#-----------------------------------------------------------------------------
return(att.b)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.