13.11 Lab: R Code

13.11.1 Run the following functions

13.11.2 Load data & install packages

  # set.seed(48104) # ?set.seed 
  
# Load data
  data_rdd <- foreign::read.dta("https://docs.google.com/uc?id=1xWHmST5FYcfLxe9V7Hwqd2LIy_A3ninG&export=download")
  # data_rdd <- foreign::read.dta("www/rdd-fouirnaies_hall_financial_incumbency_advantage.dta")
  data_rdd <- data_rdd %>% rename(x_score_victorymargin = rv,
                                  y_donationshare = dv_money,
                                  cov_statelevel = statelevel,
                                  cov_total_race_money = total_race_money,
                                  cov_total_votes = total_votes,
                                  cov_dem_inc = dem_inc,
                                  cov_rep_inc = rep_inc,
                                  cov_total_group_money = total_group_money) %>% 
    dplyr::select(x_score_victorymargin,
           y_donationshare,
           cov_statelevel,
           cov_total_race_money,
           cov_total_votes,
           cov_dem_inc,
           cov_rep_inc,
           cov_total_group_money,
           state,
           dist,
           year)

13.11.3 Explore data and subsetting

# names(data_rdd) # Show variables
# View(data_rdd)

# Filter out state legislative district level
  table(data_rdd$cov_statelevel) # How many state-level elections are there?

0	1
6533	32670

  data_rdd <- filter(data_rdd, cov_statelevel==1)
  data_rdd <- data_rdd %>% arrange(state, dist, year, x_score_victorymargin)

13.11.4 Summary statistics + graphs

Below we inspect the variables. Q: What the min. and max. values of the variable x_score_victorymargin mean substantively? And the same for y_donationshare?

# Summarize score variable (also called running variable): Vote share
  summary(data_rdd$x_score_victorymargin)

Min.	1st Qu.	Median	Mean	3rd Qu.	Max.
-50	-16.05517	0.134985	1.357636	20.07864	50

# Summarize outcome variable
  summary(data_rdd$y_donationshare)

Min.	1st Qu.	Median	Mean	3rd Qu.	Max.	NA’s
0	6.540446	50.60789	50.78094	96.80258	100	5467

  # Share of donations flowing to the incumbent’s party

# Plot oucome var vs. score variable
p = qplot(x_score_victorymargin, y_donationshare, data=data_rdd) + 
  xlab("Democratic margin of victory at t") + 
  ylab("Democratic share of contributions at t+1")
p

We can do the same with plotly..

data_rdd$colour[data_rdd$x_score_victorymargin<=0] <- "Treated"
data_rdd$colour[data_rdd$x_score_victorymargin>0] <- "Control"

plot_ly(data = data_rdd,
        type = "scatter", 
        mode = "markers",
        x = data_rdd$x_score_victorymargin, 
        y = data_rdd$y_donationshare, 
        color = data_rdd$colour,
        marker = list(size=3)) %>% 
    layout(xaxis = list(title = "Democratic margin of victory at t", dtick = 25),
                yaxis = list(title = "Democratic share of contributions at t+1"))