Briefly
A quick look at the voting behavior of the 30 House Democrats that represent congressional districts carried by Trump in 2016. Using Rvoteview
. For a more in-depth account of the characteristics of front-line House Democrats in the 116th Congress, see this post.
Front-line House Democrats
I have been going on about the House of Representatives quite a bit lately, especially Democratic members representing Trump districts. These guys were instrumental in Democrats recapturing the House majority in 2018. Over two-thirds of these front-liners are freshman members, and as a group they are super vulnerable heading into November 2020.
I have posted a list of the 30 front-liners as a simple csv, cached as a part of the uspoliticalextras
data package. It is available at the link below.
library(tidyverse)
url1 <- 'https://raw.githubusercontent.com/jaytimm/uspoliticalextras/master/clean-data-sets/thirty-one-house-democrats.csv'
fl <- read.csv(url(url1))
Ideologies in the 116th
So, using the Rvoteview
(!) package, we obtain DW-Nominate scores for all members in the 116th House. This session is still in progress, so these numbers will change depending on when they are accessed.
x116 <- Rvoteview::member_search (chamber = 'House',
congress = 116) %>%
mutate(label = gsub(', .*$', '', bioname),
party_code = ifelse(bioname %in% fl$house_rep,
'xx', party_code),
party_name = ifelse(bioname %in% fl$house_rep,
'Frontline Dems', 'Other Dems'))
The plot below summarizes voting behaviors as approximated by DW-Nominate scores in two dimensions. Here, our focus is on the first dimension (ie, the x-axis). The 30 front-liners are marked in orange. In the aggregate, then, they vote more moderately than their non-front-line Democrat peers.
p <- x116 %>%
ggplot(aes(x=nominate.dim1,
y=nominate.dim2,
label = label
)) +
annotate("path",
x=cos(seq(0,2*pi,length.out=300)),
y=sin(seq(0,2*pi,length.out=300)),
color='gray',
size = .25) +
geom_point(aes(color = as.factor(party_code)),
size= 2.5,
shape= 17) +
theme_bw() +
ggthemes::scale_color_stata() +
theme(legend.position = 'none') +
labs(title="DW-Nominate ideology scores for the 116th US House",
subtitle = '30 front-line House Democrats in orange')
p
## Warning: Removed 2 rows containing missing values (geom_point).
Focusing on Democrats
Next, we home in a bit on House Democrats. To add some context to the above plot, we calculate quartiles for DW-Nominate scores among Democrats. These are summarized in table below, ranging from progressive to moderate.
dems <- x116 %>%
filter(party_code %in% c('xx', '100'))
qq <- data.frame(x = quantile(dems$nominate.dim1, probs = seq(0, 1, 0.25)),
stringsAsFactors = FALSE)
qq %>% knitr::kable()
x | |
---|---|
0% | -0.76100 |
25% | -0.44525 |
50% | -0.37800 |
75% | -0.28575 |
100% | -0.06900 |
We add these quartiles to the plot below, and label front-line House Democrats. Again, front-liners cluster as a group in terms of roll call voting behavior. The most notable exception to this pattern is Lauren Underhood (IL-14). She won her district by five points in 2018, and Trump won the district by 4 points in 2016. It would appear, then, that her voting behavior and the political ideology of her constituents do not especially rhyme. In other words, she represents a Trump district and votes like a progressive.
p1 <- p +
xlim(-1, 0) +
geom_vline(xintercept = qq$x, linetype = 2, color = 'gray') +
ggrepel::geom_text_repel(
data = filter(x116,
bioname %in% fl$house_rep),
nudge_y = -0.005,
direction = "y",
hjust = 0,
size = 2.5)
p1
The table below summarizes counts of Democrats by front-line status & ideology quartile. So, roughly 3/4 of front-liners vote in the most moderate Democratic quartile in the House. And all but Underwood are in top 50%.
dems1 <- dems %>%
mutate(qt = ntile(nominate.dim1, 4))
dems1 %>%
group_by(party_name, qt) %>%
count() %>%
group_by(party_name) %>%
mutate(per = round(n/sum(n)*100, 1)) %>%
knitr::kable(booktabs = T, format = "html") %>%
kableExtra::kable_styling() %>%
kableExtra::row_spec(3,
background = "#e4eef4")
party_name | qt | n | per |
---|---|---|---|
Frontline Dems | 1 | 1 | 3.3 |
Frontline Dems | 3 | 6 | 20.0 |
Frontline Dems | 4 | 23 | 76.7 |
Other Dems | 1 | 58 | 28.2 |
Other Dems | 2 | 59 | 28.6 |
Other Dems | 3 | 53 | 25.7 |
Other Dems | 4 | 36 | 17.5 |
Summary
Support this group of House members!! Follow them on Twitter!
twitter1 |
---|
RepRonKind | DaveLoebsack | RepCheri | RepSeanMaloney | RepCartwright | repohalleran | RepJoshG | RepConorLamb | replucymcbath | RepFinkenauer | RepCindyAxne | RepUnderwood | RepSlotkin | RepHaleyStevens | RepAngieCraig | RepChrisPappas | RepAndyKimNJ | RepSherrill | RepTorresSmall | RepSusieLee | RepMaxRose | repdelgado | RepBrindisi | RepKendraHorn | RepCunningham | RepBenMcAdams | RepElaineLuria | RepSpanberger | repgolden |