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REPRO-Bench / 14 /replication_package /Replication /Code /ESLR_EHPM_PGsCoefPlot.R
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#######################################################
##### ESLR - COEFICIENT PLOTTING - HH SURVEY DATA #####
############# COEF PLOTS OF PG OUTCOMES ###############
#######################################################
rm(list = ls()) # Clear variables
require(foreign)
require(ggplot2)
require(RColorBrewer) # creates nice color schemes
require(scales) # customize scales
require(plyr) # join function
require(dplyr)
require(tidyr)
require(extrafont)
########################################
## Note: This file reads in the coefficient output
## and plots the coefficient estimates for the PG outcomes
########################################
# Set aesthetics:
aesthetics <- list(#guides(color=guide_colorbar(reverse=FALSE)),
#guides(fill=FALSE),
#guides(shape=FALSE),
#guides(size=FALSE),
#coord_equal(),
theme_bw(),
theme(#text=element_text(family="Palatino"),
legend.title=element_blank(),
#legend.justification=c(0,0),
#legend.position= "right", #c(1,0),
panel.grid.minor=element_blank(),
panel.grid.major=element_blank(),
#plot.background=element_rect(colour="white",fill=white),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
axis.text.y=element_text(face="bold"),
axis.title.y=element_text(face="bold")))
#axis.text=element_blank(),
#axis.ticks=element_blank(),
#panel.border = element_blank()))
Multiplier <- 1.96
########################################
# Read in parmests:
ests <- read.csv(file = "./Output/Parmest_EHPM_PGs.csv")
# Note, using the 300 ha bandwidth
########################################
# Keep only coeffients of interest:
ests <- filter(ests, parm == "std_Above500")
ests$label <- as.character(ests$label)
#ests <- ests[dim(ests)[1]:1,]
ests$idstr <- c("Bank or Credit Association","Public Phone","Internet",
"Bus Stop", "Park and/or\nSoccer Field",
"Post Office", "Market", "Health Center",
"Police Station", "Paved Road")
########################################
# Create Matrix for plotting:
MatrixofModels <- ests[c("idstr", "estimate","stderr","t","p")]
colnames(MatrixofModels) <- c("Dependent Variable", "Estimate", "StandardError", "TValue", "PValue")
MatrixofModels$`Dependent Variable` <- factor(MatrixofModels$`Dependent Variable`, levels = MatrixofModels$`Dependent Variable`)
#MatrixofModels$Legend <- c( " PCA Coefficient", rep(" Component Coefficients",dim(MatrixofModels)[1]-1))
# Plot:
OutputPlot <- qplot(`Dependent Variable`, Estimate, ymin = Estimate - Multiplier * StandardError,
ymax = Estimate + Multiplier * StandardError, data = MatrixofModels, geom = "pointrange",
ylab = NULL, xlab = NULL)
OutputPlot <- OutputPlot + geom_hline(yintercept = 0, lwd = I(7/12), colour = I(hsv(0/12, 7/12, 7/12)), alpha = I(5/12))
x_title <-expression(atop(bold("Dependent Variable "),italic("\n(Time to the Neearest)")))
OutputPlot <- OutputPlot + theme_bw() + ylab("Estimated Effect: Above 500 ha") +
aesthetics + xlab(x_title) + coord_flip()
OutputPlot
ggsave(filename="./Output/CoefPlot_PGDistance.pdf")