ddid2 | R Documentation |
ddid2
computes the Quantile Treatment Effect
on the Treated (QTET) using the method of Callaway, Li, and Oka (2015).
ddid2( formla, xformla = NULL, t, tmin1, tname, data, panel = TRUE, dropalwaystreated = TRUE, idname = NULL, probs = seq(0.05, 0.95, 0.05), iters = 100, alp = 0.05, method = "logit", se = TRUE, retEachIter = FALSE, seedvec = NULL, pl = FALSE, cores = NULL )
formla |
The formula y ~ d where y is the outcome and d is the treatment indicator (d should be binary) |
xformla |
A optional one sided formula for additional covariates that will be adjusted for. E.g ~ age + education. Additional covariates can also be passed by name using the x paramater. |
t |
The 3rd time period in the sample (this is the name of the column) |
tmin1 |
The 2nd time period in the sample (this is the name of the column) |
tname |
The name of the column containing the time periods |
data |
The name of the data.frame that contains the data |
panel |
Boolean indicating whether the data is panel or repeated cross sections |
dropalwaystreated |
How to handle always treated observations in panel data case (not currently used) |
idname |
The individual (cross-sectional unit) id name |
probs |
A vector of values between 0 and 1 to compute the QTET at |
iters |
The number of iterations to compute bootstrap standard errors. This is only used if se=TRUE |
alp |
The significance level used for constructing bootstrap confidence intervals |
method |
The method for estimating the propensity score when covariates are included |
se |
Boolean whether or not to compute standard errors |
retEachIter |
Boolean whether or not to return list of results from each iteration of the bootstrap procedure |
seedvec |
Optional value to set random seed; can possibly be used in conjunction with bootstrapping standard errors. |
pl |
boolean for whether or not to compute bootstrap error in parallel. Note that computing standard errors in parallel is a new feature and may not work at all on Windows. |
cores |
the number of cores to use if bootstrap standard errors are computed in parallel |
QTE
object
Callaway, Brantly, Tong Li, and Tatsushi Oka. “Quantile Treatment Effects in Difference in Differences Models under Dependence Restrictions and with Only Two Time Periods.” Working Paper, 2015.
##load the data data(lalonde) ## Run the ddid2 method on the observational data with no covariates d1 <- ddid2(re ~ treat, t=1978, tmin1=1975, tname="year", data=lalonde.psid.panel, idname="id", se=FALSE, probs=seq(0.05, 0.95, 0.05)) summary(d1) ## Run the ddid2 method on the observational data with covariates d2 <- ddid2(re ~ treat, t=1978, tmin1=1975, tname="year", data=lalonde.psid.panel, idname="id", se=FALSE, xformla=~age + I(age^2) + education + black + hispanic + married + nodegree, probs=seq(0.05, 0.95, 0.05)) summary(d2)
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