# Quant 3: Section on matching procedures
# Alex Herzog
# Nov 16, 2007

# Data is from  Michael J. Gilligan and Ernest J. Sergenti (2007): Do UN Interventions Cause Peace? Using Matching to Improve Causal Inference. Unpublished Manuscirpt. October 31.

# Install Gary King's MatchIt package
# install.packages("MatchIt", dependencies=TRUE) 

# Install Jas Sekhon's Matching package
# install.packages("Matching", dependencies=TRUE) 
# install.packages("rgenoud")

# Load packages
library(MatchIt)
library(Matching)
library(foreign)

# Load Gilligan/Sergenti dataset
peace.data <- read.dta('peace_pre_match.dta')
attach(peace.data)

# Assign country names as row names 
# (Row names are by default the row numbers. Here I replace the row names with the
# name of the observation (country) together with the date of the peace periode 
# (the latter in order to distinguish multiple observations of the same country)).
rownames(peace.data) <- paste(cname,date0,sep=" ")

# Look at variables in the dataset
summary(peace.data)

# Look at treated and non-treated cases
table(UN)



# Match treatment cases to control cases via nearest neigbhor method w/o replacement
#################################################################################### 
m.out1 <- matchit(UN ~ lwdurat + milper + pop + ethfrac + lmtnest + bwplty2 + ssafrica + asia + lamerica, data=peace.data, method="nearest", replace=FALSE)

## Look at matching result
m.out1
m.out1$match.matrix

## Check for balance
summary(m.out1)
plot(m.out1)
plot(m.out1,type="jitter")



# Match treatment cases to control cases via nearest neigbhor method w/ replacement
###################################################################################
m.out2 <- matchit(UN ~ lwdurat + milper + pop + ethfrac + lmtnest + bwplty2 + ssafrica + asia + lamerica, data=peace.data, method="nearest", replace=TRUE)

## Look at matching result
m.out2
m.out2$match.matrix

## Check for balance
summary(m.out2)
plot(m.out2)
plot(m.out2,type="jitter")


# Match treatment cases to control cases via genetic algorithm
##############################################################
m.out3 <- matchit(UN ~ lwdurat + milper + pop + ethfrac + lmtnest + bwplty2 + ssafrica + asia + lamerica, data=peace.data, method="genetic", estimand="ATT", pop.size=1000, max.generations=100, wait.generations=10, int.seed=7, unif.seed=10, data.type.int=FALSE)

## Overview of matching result 
m.out3
m.out3$match.matrix

## Check for balance
summary(m.out3)
plot(m.out3)
plot(m.out3,type="jitter")



# Generate dataset of matched results and convert into Stata datafile 
m.data <- match.data(m.out2)
write.dta(m.data,file="mdata.dta")





#########################################################################################
# See Gary King's website for more info on MatchIt and the different matching algorithms: 
#+ MatchIt: http://gking.harvard.edu/matchit/
#++ NEAREST NEIGHBOR MATCHING: http://gking.harvard.edu/matchit/docs/Nearest_Neighbor_Match.html
#++ GENETIC MATCHING: http://gking.harvard.edu/matchit/docs/Genetic_Matching.html

# See Jas Sekhon's website for more info on the genetic matching algorithm:
# http://sekhon.berkeley.edu/matching/