inst/doc/nndd.R

In nndd: Nearest Neighbour Matching (NN) followed by a Linear Model with Difference in Differences (DD)

### R code from vignette source 'nndd.Rnw'

###################################################
### code chunk number 1: preliminaries
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options(width = 70, prompt = "R> ", continue = "+  ")
library("Formula")
library("lmtest")
library("multiwayvcov")
library("memisc")
library("nndd")


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### code chunk number 2: IRCA
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library("nndd")
data("IRCA", package = "nndd")

IRCA$StateFIPS <- factor(IRCA$StateFIPS)

formula <- Formula(treated | v_crime ~ unemprate + povrate + pop  
                   + crack_index + officers_pc + income + abortions + StateFIPS 
                   | unemprate + povrate + pop +  crack_index +officers_pc    ) 

nndd1 <- nndd(formula = formula, data = IRCA, 
              index = c("county", "year"),  
              t_time = "1986", 
              displ_coefs = c("unemprate",  "povrate", "pop" , "crack_index", 
                              "officers_pc", "income" , "abortions", "post", 
                              "treated", "post:treated") )


print(nndd1)
summary(nndd1)


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### code chunk number 3: cluster
###################################################
nndd1c <- nndd(formula = formula, data = IRCA, 
               index = c("county", "year"),  
               t_time = "1986" , 
               clustervariables = "StateFIPS",
               displ_coefs = c("unemprate",  "povrate", "pop" , "crack_index", 
                               "officers_pc", "income" , "abortions", 
                               "post", "treated", "post:treated"))


###################################################
### code chunk number 4: simple dd
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lm1 <- lm(update(formula(formula, lhs = 2, rhs = 1), 
                 paste(paste(".", 
                             paste(formula(formula, lhs = 0, rhs = (2)), 
                                   collapse = " . + ")), 
                   "+post*treated")), 
          data = IRCA)

lm1$displ_coefs <- c("unemprate",  "povrate", "pop" , "crack_index", 
                     "officers_pc", "income" , "abortions", 
                     "post", "treated", "post:treated")
class(lm1) <- c("lmc", "lm")

lm1c <- lm1
lm1c$clustervariables <- "StateFIPS"
class(lm1c) <- c("lmc", "lm")


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### code chunk number 5: compare (eval = FALSE)
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## mtable(lm1,nndd1, lm1c, nndd1c)


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### code chunk number 6: mtable-latex
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gsub("_", "\\\\_", toLatex(mtable(lm1,nndd1, lm1c, nndd1c)))


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### code chunk number 7: comapre (eval = FALSE)
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## #dev.new()
## par(mfrow = c(1,2))
## plot(nndd1c,data = IRCA ,which = c(1,2))