summary(med_sp)
med_term <- plm(pop_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dst, index = c('congress'), model = 'within', effect = 'time')
maj_term <- plm(pop_pct ~ maj_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes, data = dst, index = c('congress'), model = 'within', effect = 'time')
med_sp <- plm(sp_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes, data = dst, index = c('congress'), model = 'within', effect = 'time')
maj_sp <- plm(sp_pct ~ maj_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes, data = dst, index = c('congress'), model = 'within', effect = 'time')
summary(med_sp)
summary(maj_sp)
summary(med_termd)
summary(maj_termd)
summary(maj_termd)
summary(med_termd)
sumamry(med_spd)
summary(med_spd)
summary(maj_spd)
summary(med_termr)
summary(maj_termr)
summary(med_spr)
summary(maj_spr)
dems_ideology <- stargazer(med_termd, med_spd, title = "Panel Data Models", type = "text",
dep.var.caption = "Dependent Variable", dep.var.labels = c("pop_pct", "sp_pct"),
covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"),
add.lines = list(c("Model 1: Population Percentage", "Model 2: Speed Percentage")))
library(stargazer)
dems_ideology <- stargazer(med_termd, med_spd, title = "Panel Data Models", type = "text",
dep.var.caption = "Dependent Variable", dep.var.labels = c("pop_pct", "sp_pct"),
covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"),
add.lines = list(c("Model 1: Population Percentage", "Model 2: Speed Percentage")))
library(stargazer)
# Create stargazer tables for the models
table_med_termd <- stargazer(med_termd, title = "Panel Data Model - Population Percentage", type = "text", dep.var.caption = "Dependent Variable: pop_pct", covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"))
table_med_spd <- stargazer(med_spd, title = "Panel Data Model - Speed Percentage", type = "text", dep.var.caption = "Dependent Variable: sp_pct", covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism"))
# Modify the table headers and combine the two tables
table_med_termd <- sub("Panel Data Model - Population Percentage", "Model 1", table_med_termd)
table_med_spd <- sub("Panel Data Model - Speed Percentage", "Model 2", table_med_spd)
cat(table_med_termd, "\n\n", table_med_spd)
library(stargazer)
# Create stargazer tables for the models
table_med_termd <- stargazer(med_termd, title = "Population Percentage", type = "latex", dep.var.caption = "Dependent Variable: pop_pct", covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"))
table_med_spd <- stargazer(med_spd, title = "Speech Percentage", type = "latex", dep.var.caption = "Dependent Variable: sp_pct", covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism"))
# Modify the table headers and combine the two tables
table_med_termd <- sub("Panel Data Model - Population Percentage", "Model 1", table_med_termd)
table_med_spd <- sub("Panel Data Model - Speed Percentage", "Model 2", table_med_spd)
# Print the combined LaTeX tables
cat(table_med_termd, "\n\n", table_med_spd)
cat(table_med_termd, "\n\n", table_med_spd)
table_med_termd <- stargazer(med_termd, title = "Population Percentage", type = "latex", dep.var.caption = "Dependent Variable: pop_pct", covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"))
table_med_spd <- stargazer(med_spd, title = "Speech Percentage", type = "latex", dep.var.caption = "Dependent Variable: sp_pct", covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism"))
# Modify the table headers and combine the two tables
table_med_termd <- sub("Word Proportion", "Model 1", table_med_termd)
table_med_spd <- sub("Speech Ratio", "Model 2", table_med_spd)
# Print the combined LaTeX tables
cat(table_med_termd, "\n\n", table_med_spd)
table_combined <- stargazer(med_termd, med_spd, title = "Panel Data Models", type = "latex", dep.var.caption = "Dependent Variable: Populism", dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"), covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"))
# Print the combined LaTeX table
cat(table_combined)
table_combined <- stargazer(med_termd, med_spd, title = "Panel Data Models", type = "latex", dep.var.caption = "Dependent Variable: Populism", dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"), covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator", omit.stat=c("LL","ser","f"), ci=TRUE, ci.level=0.95, single.row=TRUE, digits=1, star.cutoffs = c(0.05)))
table_combined <- stargazer(med_termd, med_spd, title = "Panel Data Models", type = "latex", dep.var.caption = "Dependent Variable: Populism", dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"), covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"), omit.stat=c("LL","ser","f"), ci=TRUE, ci.level=0.95, single.row=TRUE, digits=1, star.cutoffs = c(0.05))
library(stargazer)
# Create stargazer tables for the models
table_combined <- stargazer(med_termr, med_spr, title = "Panel Data Models", type = "latex", dep.var.caption = "Dependent Variable: Populism", dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"), covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"), omit.stat=c("LL","ser","f"), ci=TRUE, ci.level=0.95, single.row=TRUE, digits=1, star.cutoffs = c(0.05))
# Print the combined LaTeX table
cat(table_combined)
sd(dems$med_dist)
library(plm)
med_term <- plm(pop_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dst, index = c('congress'), model = 'within', effect = 'time')
maj_term <- plm(pop_pct ~ maj_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes, data = dst, index = c('congress'), model = 'within', effect = 'time')
med_sp <- plm(sp_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dst, index = c('congress'), model = 'within', effect = 'time')
maj_sp <- plm(sp_pct ~ maj_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes, data = dst, index = c('congress'), model = 'within', effect = 'time')
###dems
med_termd <- plm(pop_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dems, index = c('congress'), model = 'within', effect = 'time')
med_spd <- plm(sp_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dems, index = c('congress'), model = 'within', effect = 'time')
###reps
med_termr <- plm(pop_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = reps, index = c('congress'), model = 'within', effect = 'time')
med_spr <- plm(sp_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = reps, index = c('congress'), model = 'within', effect = 'time')
library(stargazer)
# Create stargazer tables for the models
table_combined <- stargazer(med_termd, med_spd, title = "Panel Data Models", type = "latex", dep.var.caption = "Dependent Variable: Populism", dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"), covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"), omit.stat=c("LL","ser","f"), ci=TRUE, ci.level=0.95, single.row=TRUE, digits=1, star.cutoffs = c(0.05))
# Print the combined LaTeX table
cat(table_combined)
med_termr <- plm(pop_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = reps, index = c('congress'), model = 'within', effect = 'time')
med_spr <- plm(sp_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = reps, index = c('congress'), model = 'within', effect = 'time')
library(stargazer)
# Create stargazer tables for the models
table_combined <- stargazer(med_termr, med_spr, title = "Panel Data Models", type = "latex", dep.var.caption = "Dependent Variable: Populism", dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"), covariate.labels = c("Dist. from Chamber Med.", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"), omit.stat=c("LL","ser","f"), ci=TRUE, ci.level=0.95, single.row=TRUE, digits=1, star.cutoffs = c(0.05))
# Print the combined LaTeX table
cat(table_combined)
sd(dems$med_dist)
sd(dst$med_dist)
summary(dst$sp_pct)
sd(dst$sp_pct)
sd(dst$pop_pct)
library(readr)
HSall_parties <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv")
View(HSall_parties)
names(HSall_parties)
View(HSall_parties)
HSall_parties <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv") %>%
select(congress >109)
library(readr)
HSall_parties <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv") %>%
dplyr::select(congress > 109)
party_med <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv")
party_med <- dplyr::select(party_med, congress > 109)
class(party_med$congress)
party_med <- dplyr::filter(party_med, congress > 109)
View(party_med)
names(party_med)
party_med <- party_med %>%
dplyr::filter(congress > 109) %>%
select(congress, party_code, nominate_dim1_median)
dem_med <- dplyr::filter(party_med, dem==100)
dem_med <- dplyr::filter(party_med, party_code==100)
rep_med <- dplyr::filter(party_med, party_code==100)
View(rep_med)
rep_med <- dplyr::filter(party_med, party_code==200)
library(readr)
library(dplyr)
party_med <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv")
party_med <- party_med %>%
dplyr::filter(congress > 109) %>%
select(congress, party_code, nominate_dim1_median) %>%
dplyr::rename(party_med = nominate_dim1_median)
dem_med <- dplyr::filter(party_med, party_code==100)
rep_med <- dplyr::filter(party_med, party_code==200)
dem_med <- dplyr::select(dem_med, congress, party_med)
rep_med <- dplyr::select(dem_med, congress, party_med)
View(rep_med)
party_med <- party_med %>%
dplyr::filter(congress > 109) %>%
select(congress, party_code, nominate_dim1_median) %>%
dplyr::rename(party_med = nominate_dim1_median)
party_med <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv")
party_med <- party_med %>%
dplyr::filter(congress > 109) %>%
select(congress, party_code, nominate_dim1_median) %>%
dplyr::rename(party_med = nominate_dim1_median)
dem_med <- dplyr::filter(party_med, party_code==100)
rep_med <- dplyr::filter(party_med, party_code==200)
View(rep_med)
View(party_med)
party_med <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv")
View(party_med)
table(party_med$chamber)
library(readr)
library(dplyr)
party_med <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv")
party_med <- party_med %>%
dplyr::filter(congress > 109) %>%
select(congress, party_code, nominate_dim1_median) %>%
dplyr::rename(party_med = nominate_dim1_median) %>%
dplyr::filter(chamber = "House")
library(readr)
library(dplyr)
party_med <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv")
party_med <- party_med %>%
dplyr::filter(congress > 109) %>%
select(congress, party_code, nominate_dim1_median) %>%
dplyr::rename(party_med = nominate_dim1_median) %>%
dplyr::filter(chamber == "House")
party_med <- party_med %>%
dplyr::filter(congress > 109) %>%
dplyr::filter(chamber == "House")   %>%
select(congress, party_code, nominate_dim1_median) %>%
dplyr::rename(party_med = nominate_dim1_median)
dem_med <- dplyr::filter(party_med, party_code==100)
rep_med <- dplyr::filter(party_med, party_code==200)
dem_med <- dplyr::select(dem_med, congress, party_med)
View(dem_med)
rep_med <- dplyr::select(rep_med, congress, party_med)
reps <- left_join(reps, reps_med, by=c("congress"))
rep_med <- dplyr::select(rep_med, congress, party_med)
dems <- left_join(dems, dem_med, by=c("congress"))
reps <- left_join(reps, reps_med, by=c("congress"))
reps <- left_join(reps, rep_med, by=c("congress"))
names(dems)
dems$dwnom1
library(readr)
HSall_members <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_members.csv")
View(HSall_members)
names(HSall_members)
library(readr)
HSall_members <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_members.csv") %>%
filter(congress > 109 & chamber == "House") %>%
select(icpsr, nominate_dim1)
View(HSall_members)
dems <- left_join(dems, HSall_members, by=c("congress"))
library(readr)
HSall_members <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_members.csv") %>%
filter(congress > 109 & chamber == "House") %>%
select(icpsr, nominate_dim1, congress)
dems <- left_join(dems, HSall_members, by=c("congress"))
reps <- left_join(reps, HSall_members, by=c("congress"))
dems <- left_join(dems, HSall_members, by=c("icpsr", "congress"))
names(dems)
names(dst)
dems <- filter(dst, democrat==1)
reps <- filter(dst, democrat==0)
library(readxl)
seat_share <- read_excel("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/seat_share.xlsx")
###party median
library(readr)
library(dplyr)
party_med <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_parties.csv")
party_med <- party_med %>%
dplyr::filter(congress > 109) %>%
dplyr::filter(chamber == "House")   %>%
select(congress, party_code, nominate_dim1_median) %>%
dplyr::rename(party_med = nominate_dim1_median)
dem_med <- dplyr::filter(party_med, party_code==100)
rep_med <- dplyr::filter(party_med, party_code==200)
dem_med <- dplyr::select(dem_med, congress, party_med)
rep_med <- dplyr::select(rep_med, congress, party_med)
dems <- left_join(dems, dem_med, by=c("congress"))
reps <- left_join(reps, rep_med, by=c("congress"))
names(dems)
library(readr)
HSall_members <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_members.csv") %>%
filter(congress > 109 & chamber == "House") %>%
select(icpsr, nominate_dim1, congress)
dems <- left_join(dems, HSall_members, by=c("icpsr", "congress"))
library(readr)
HSall_members <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_members.csv") %>%
filter(congress > 109 & chamber == "House") %>%
select(icpsr, nominate_dim1, congress)  %>%
as.character(icpsr)
dems <- left_join(dems, HSall_members, by=c("icpsr", "congress"))
dems <- dems %>% ungroup()
reps <- reps %>% ungroup()
dems <- left_join(dems, HSall_members, by=c("icpsr", "congress"))
HSall_members <- HSall_members %>% ungroup()
HSall_members <- read_csv("D:/Dropbox (Univ. of Oklahoma)/My Research/Dissertation/Chapter_2/Control variables/HSall_members.csv") %>%
filter(congress > 109 & chamber == "House") %>%
select(icpsr, nominate_dim1, congress)
HSall_members$icpsr <- as.character(HSall_members$icpsr)
dems <- left_join(dems, HSall_members, by=c("icpsr", "congress"))
reps <- left_join(reps, HSall_members, by=c("icpsr", "congress"))
dems$party_dist <- abs((dems$nominate_dim1) - (dems$party_med))
reps$party_dist <- abs((reps$nominate_dim1) - (reps$party_med))
test <- select(dems, nominate_dim1, party_med, party_dist)
View(test)
View(reps)
names(dems)
names(seat_share)
table(seat_Share$house)
table(seat_share$house)
####merge seat share
seat_share <- filter(seat_share, house = "house")
####merge seat share
seat_share <- filter(seat_share, house == "house")
View(seat_share)
d_seat_share <- select(seat_share, d_seat_share, congress)
View(d_seat_share)
dems <- left_join(dems, d_seat_share, by = c("congress"))
r_seat_share <- select(seat_share, r_seat_share, congress)
dems <- dplyr::rename(seat_share = d_seat_share)
dems <- dplyr::rename(dems, seat_share = d_seat_share)
r_seat_share <- select(seat_share, r_seat_share, congress)
reps <- left_join(reps, r_seat_share, by = c("congress"))
reps <- dplyr::rename(reps, seat_share = r_seat_share)
unity_wd_d <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dems, index = c('congress'), model = 'within', effect = 'time')
summary(unity_wd_d)
sd(dems$loyal_by_cong)
unity_wd_d <- plm(sp_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dems, index = c('congress'), model = 'within', effect = 'time')
summary(unity_wd_d)
unity_wd_d <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dems, index = c('congress'), model = 'within', effect = 'time')
unity_sp_d <- plm(sp_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dems, index = c('congress'), model = 'within', effect = 'time')
###reps
unity_wd_r <- plm(pop_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = reps, index = c('congress'), model = 'within', effect = 'time')
unity_sp_r <- plm(sp_pct ~ med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = reps, index = c('congress'), model = 'within', effect = 'time')
summary(unity_wd_d)
summary(unity_sp_d)
summary(unity_wd_r)
summary(unity_sp_r)
table_combined <- stargazer(unity_wd_d, unity_sp_d, title = "Panel Data Models", type = "latex", dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Party unity", "DW-Nom Dist. from Party Med.", "Seat Share", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
unity_sp_d <- plm(sp_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dems, index = c('congress'), model = 'within', effect = 'time')
summary(unity_sp_d)
dems_unity <- stargazer(unity_wd_d, unity_sp_d, title = "Panel Data Models", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Party unity", "DW-Nom Dist. from Party Med.", "Seat Share", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
table_combined_r <- stargazer(unity_wd_r, unity_sp_r, title = "Panel Data Models - Republicans", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Party unity", "DW-Nom Dist. from Party Med.", "Seat Share", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
summary(unity_wd_r)
unity_wd_r <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = reps, index = c('congress'), model = 'within', effect = 'time')
unity_sp_r <- plm(sp_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = reps, index = c('congress'), model = 'within', effect = 'time')
summary(unity_wd_r)
table_combined_r <- stargazer(unity_wd_r, unity_sp_r, title = "Panel Data Models - Republicans", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Party unity", "DW-Nom Dist. from Party Med.", "Seat Share", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
names(reps)
unity_wd_d <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg, data = dems + maj_party + pres_party, index = c('congress'), model = 'within', effect = 'time')
names(dems)
unity_wd_d <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
unity_wd_d <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
summary(unity_wd_d)
# Create stargazer table for Democratic models
dems_unity <- stargazer(unity_wd_d, unity_sp_d, title = "Panel Data Models - Democrats", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Party unity", "DW-Nom Dist. from Party Med.", "Seat Share", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
###dems
unity_wd_d <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party + maj_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
unity_sp_d <- plm(sp_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party + maj_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
###reps
unity_wd_r <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party + maj_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
unity_sp_r <- plm(sp_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party +  maj_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
# Create stargazer table for Democratic models
dems_unity <- stargazer(unity_wd_d, unity_sp_d, title = "Panel Data Models - Democrats", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Party unity", "DW-Nom Dist. from Party Med.", "Seat Share", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator", "President's Party", "Majority Party"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
###dems
unity_wd_d <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party + maj_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
unity_sp_d <- plm(sp_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party + maj_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
###reps
unity_wd_r <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party + maj_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
unity_sp_r <- plm(sp_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party +  maj_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
# Create stargazer table for Democratic models
dems_unity <- stargazer(unity_wd_d, unity_sp_d, title = "Panel Data Models - Democrats", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Party unity", "DW-Nom Dist. from Party Med.", "Seat Share", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator", "President's Party", "Majority Party"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
sd(dems$party_unity)
sd(dems$loyal_by_cong)
names(dst)
unity_wd_d <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
unity_sp_d <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
###reps
unity_wd_r <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
unity_sp_r <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
###dems
LES_wd_d <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
LES_sp_d <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
###reps
LES_wd_r <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
LES_sp_r <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
summary(LES_wd_d)
summary(dst$LES)
sd(dst$LES)
summary(LES_sp_d)
summary(LES_wd_r)
summary(LES_sp_r)
dems_LES <- stargazer(LES_wd_d, LES_sp_d, title = "Panel Data Models - Democrats (LES Models)", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("LES", "Med. Dist. from Party Med.", "Vote Share", "Sponsor", "Seniority", "Leader", "Legislative Professionalism", "State Legislator", "Female", "Nonwhite", "Majority Party", "Presidential Party"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
unity_wd_r <- plm(pop_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party + maj_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
unity_sp_r <- plm(sp_pct ~ loyal_by_cong + party_dist + seat_share + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + pres_party +  maj_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
reps_unity <- stargazer(unity_wd_r, unity_sp_r, title = "Panel Data Models - Republicans", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Party unity", "DW-Nom Dist. from Party Med.", "Seat Share", "Vote Share", "Sponsor", "LES", "Seniority", "Leader", "Legislative Professionalism", "State Legislator", "Majority Party"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
# Create stargazer table for Republican "LES" models
reps_LES <- stargazer(LES_wd_r, LES_sp_r, title = "Panel Data Models - Republicans (LES Models)", type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("LES", "Med. Dist. from Party Med.", "Vote Share", "Sponsor", "Seniority", "Leader", "Legislative Professionalism", "State Legislator", "Female", "Nonwhite", "Majority Party", "President's Party"),
omit.stat = c("LL", "ser", "f"), ci = TRUE, ci.level = 0.95, single.row = TRUE, digits = 1, star.cutoffs = c(0.05))
sd(dst$LES)
summary(dst$LES)
summary(dem)
names(dems)
LES_wd_d <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
LES_sp_d <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
###reps
LES_wd_r <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
LES_sp_r <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
summary(LES_wd_r)
LES_wd_d <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
summary(LES_wd_D)
summary(LES_wd_d)
LES_wd_d <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
LES_wd_d <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
LES_sp_d <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
###reps
LES_wd_r <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
LES_sp_r <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = reps, index = c('congress'), model = 'within', effect = 'time')
summary(LES_wd_d)
LES_sp_d <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
summary(LES_sp_d)
summary(LES_sp_r)
summary(LES_wd_r)
names(dst)
am_wd_d <- plm(pop_pct ~ total_amendments + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
am_sp_d <- plm(sp_pct ~ total_amendments + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
am_wd_d <- plm(pop_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
am_sp_d <- plm(sp_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
summary(am_wd_d)
am_wd_d <- plm(pop_pct ~ total_amendments + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
am_sp_d <- plm(sp_pct ~ total_amendments + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
rj_wd_d <- plm(pop_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
rj_sp_d <- plm(sp_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dems, index = c('congress'), model = 'within', effect = 'time')
# Create a stargazer table for all Democratic models with updated variable labels
dems_all <- stargazer(
LES_wd_d, LES_sp_d,
am_wd_d, am_sp_d,
rj_wd_d, rj_sp_d,
title = "Panel Data Models - Democrats",
type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("LES Model 1: Population Percentage", "LES Model 2: Speed Percentage",
"Amendment Model 1: Population Percentage", "Amendment Model 2: Speed Percentage",
"Reject Model 1: Population Percentage", "Reject Model 2: Speed Percentage"),
covariate.labels = c("LES", "Med. Dist.", "Vote", "Sponsor", "Seniority", "Leader",
"Leg. Prof.", "State Leg.", "Female", "Nonwhite", "Pres. Party"),
omit.stat = c("LL", "ser", "f"),
ci = TRUE,
ci.level = 0.95,
single.row = TRUE,
digits = 1,
star.cutoffs = c(0.05)
)
dems_am_rj <- stargazer(
am_wd_d, am_sp_d,
rj_wd_d, rj_sp_d,
title = "Panel Data Models - Democrats (Amendment and Reject Models)",
type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Amendment Model 1: Population Percentage", "Amendment Model 2: Speed Percentage",
"Reject Model 1: Population Percentage", "Reject Model 2: Speed Percentage"),
covariate.labels = c("Total Amendments", "Med. Dist.", "Vote", "Sponsor", "Seniority", "Leader",
"Leg. Prof.", "State Leg.", "Female", "Nonwhite", "Pres. Party"),
omit.stat = c("LL", "ser", "f"),
ci = TRUE,
ci.level = 0.95,
single.row = TRUE,
digits = 1,
star.cutoffs = c(0.05)
)
summary(am_wd_d)
summary(rj_wd_d)
summary(rj_sp_d)
summary(am_sp_d)
dems_rj <- stargazer(
rj_wd_d, rj_sp_d,
title = "Panel Data Models - Democrats (Reject Models)",
type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Reject", "Med. Dist.", "Vote", "Sponsor", "LES", "Seniority", "Leader",
"Leg. Prof.", "State Leg.", "Female", "Nonwhite", "Pres. Party"),
omit.stat = c("LL", "ser", "f"),
ci = TRUE,
ci.level = 0.95,
single.row = TRUE,
digits = 1,
star.cutoffs = c(0.05)
)
dema <- filter(dems, congress %in% c(112, 113, 114, 115))
table(dema$congress)
repa <- filter(reps, congress %in% c(110, 111))
table(repa$congress)
###dems
am_wd_d <- plm(pop_pct ~ total_amendments + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dema, index = c('congress'), model = 'within', effect = 'time')
am_sp_d <- plm(sp_pct ~ total_amendments + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dema, index = c('congress'), model = 'within', effect = 'time')
rj_wd_d <- plm(pop_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dema, index = c('congress'), model = 'within', effect = 'time')
rj_sp_d <- plm(sp_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = dema, index = c('congress'), model = 'within', effect = 'time')
###reps
am_wd_r <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = repa, index = c('congress'), model = 'within', effect = 'time')
am_sp_r <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = repa, index = c('congress'), model = 'within', effect = 'time')
rj_wd_r <- plm(pop_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = repa, index = c('congress'), model = 'within', effect = 'time')
rj_sp_r <- plm(sp_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = repa, index = c('congress'), model = 'within', effect = 'time')
dems_rj <- stargazer(
rj_wd_d, rj_sp_d,
title = "Panel Data Models - Democrats (Reject Models)",
type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage", "Model 2: Speed Percentage"),
covariate.labels = c("Reject", "Med. Dist.", "Vote", "Sponsor", "LES", "Seniority", "Leader",
"Leg. Prof.", "State Leg.", "Female", "Nonwhite", "Pres. Party"),
omit.stat = c("LL", "ser", "f"),
ci = TRUE,
ci.level = 0.95,
single.row = TRUE,
digits = 1,
star.cutoffs = c(0.05)
)
am_wd_r <- plm(pop_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = repa, index = c('congress'), model = 'within', effect = 'time')
am_sp_r <- plm(sp_pct ~ LES + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + maj_party + pres_party, data = repa, index = c('congress'), model = 'within', effect = 'time')
rj_wd_r <- plm(pop_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = repa, index = c('congress'), model = 'within', effect = 'time')
rj_sp_r <- plm(sp_pct ~ reject + med_dist + vote_pct + sponsor + LES + seniority + leader + leg_profes + state_leg + female + nonwhite + pres_party, data = repa, index = c('congress'), model = 'within', effect = 'time')
summary(rj_wd_r)
reps_rj <- stargazer(
rj_wd_r, rj_sp_r,
title = "Panel Data Models - Republicans (Reject Models)",
type = "latex",
dep.var.caption = "Dependent Variable: Populism",
dep.var.labels = c("Model 1: Population Percentage (R)", "Model 2: Speed Percentage (R)"),
covariate.labels = c("Reject", "Med. Dist.", "Vote", "Sponsor", "LES", "Seniority", "Leader",
"Leg. Prof.", "State Leg.", "Female", "Nonwhite", "Pres. Party"),
omit.stat = c("LL", "ser", "f"),
ci = TRUE,
ci.level = 0.95,
single.row = TRUE,
digits = 1,
star.cutoffs = c(0.05)
)
sd(dst$reject)
