Monday_Nov_14.R

# From class on Monday, Nov 14

# Switching to the OBSERVATIONAL Lalonde data set

# do genetic matching using the observational lalonde data
# use a caliper = to 0.1 standard deviations for every x.
library(Matching)
lalonde <- read.csv("https://tinyurl.com/st9n3dl")

X = cbind(lalonde$age, lalonde$educ, lalonde$black, lalonde$hisp, lalonde$married, lalonde$nodegr, lalonde$u74, lalonde$u75, lalonde$re75, lalonde$re74)


#
genout <- GenMatch(Tr=lalonde$treat, X=X, BalanceMatrix=X, M=1,
                   pop.size=20, max.generations=10,
                   caliper = 0.1,
                   wait.generations=10)

mout <- Match(Tr=lalonde$treat, X=X, caliper = 0.1,
              Weight.matrix=genout)

summary(mout)

# Has good balance been obtained?
#                        
#Let's determine if balance has actually been obtained on the variables of interest
#                        
mb <- MatchBalance(treat~age +educ+black+ hisp+ married+
                     nodegr+ u74+ u75+
                     re75+ re74+ I(re74*re75), data = lalonde,
                   match.out=mout, nboots=500)
mb$AMsmallest.p.value
mb$AMsmallestVarName

treated_units <- lalonde[mout$index.treated,]
control_units <- lalonde[mout$index.control,]
matched_data <- rbind(treated_units,control_units)
unit_level_weights <- mout$weights
dim(matched_data)

library(quantreg)

reg1 <- rq(re78 ~ treat, data = matched_data, tau = 0.5)
summary(reg1)