library(plyr)
load("lee.RData")
# Subsetting to Democrats
d <- d[which(d$party == "100"), ]
# Create vote share variable (DV)
d$share_t <- d$origvote/d$totvote
# Create adjusted vote margin variable
d$margin_t <- d$origvote/(d$highestvote + d$sechighestvote) - 0.5
# Create forcing variable (adjusted vote margin from previous
# year)
d <- ddply(d, c("state", "distnum", "distid", "party"), function(d.sub) {
out <- d.sub[order(d.sub$yearel), ]
out$margin_tm1 <- c(NA, out$margin_t[-nrow(out)])
return(out)
})
d$incumbent <- ifelse(d$margin_tm1 > 0, 1, 0)
# Plot treatment against forcing
plot(x = d$margin_tm1, y = d$incumbent, xlab = "Vote Margin (t-1)",
ylab = "Incumbency", main = "Vote Margin and Incumbency")
abline(v = 0, lty = 3)

mod <- lm(share_t ~ incumbent + margin_tm1, data = d)
# Create scatterplot
plot(d$margin_tm1, d$share_t, xlab = "Vote Margin (t-1)", ylab = "Vote Share",
     main = "Party Incumbency Advantage \n Linear w/ Common Slope", cex.main = 0.8)
# Plot curves
curve(mod$coefficients[1] + mod$coefficients[2] + mod$coefficients[3] * x, 0, 0.5,
      add = T, lwd = 3, col = "red")
curve(mod$coefficients[1] + mod$coefficients[3] * x, -0.5, 0,
      add = T, lwd = 3, col = "blue")