14 Ballot order effect

library(tidyverse)
library(readxl)
library(moderndive)
library(plm)
library(sandwich)
library(lmtest)
library(stargazer)
library(zoo)

candidates.2020 <- read_excel("ballot/candidates-2020.xls")
candidates.2016 <- read_excel("ballot/candidates-2016.xls")
candidates.2012 <- read_excel("ballot/candidates-2012.xls")
candidates.2008 <- read_excel("ballot/candidates-2008.xls")

candidates <- bind_rows(candidates.2020 %>% mutate(year = 2020),
                        candidates.2016 %>% mutate(year = 2016),
                        candidates.2012 %>% mutate(year = 2012),
                        candidates.2008 %>% mutate(year = 2008))

candidates.2020 <- candidates.2020 %>%
  mutate(top = ifelse(號次 == 1, 1, 0),
         sex = ifelse(性別 == "男", 1, 0),
         incumbent = ifelse(是否現任 == "是", 1, 0),
         birth = as.integer(出生年次),
         share = 得票率)

candidates.2016 <- candidates.2016 %>%
  mutate(top = ifelse(號次 == 1, 1, 0),
         sex = ifelse(性別 == "男", 1, 0),
         incumbent = ifelse(是否現任 == "是", 1, 0),
         birth = as.integer(出生年次),
         share = 得票率)

candidates.2012 <- candidates.2012 %>%
  mutate(top = ifelse(號次 == 1, 1, 0),
         sex = ifelse(性別 == "男", 1, 0),
         incumbent = ifelse(是否現任 == "是", 1, 0),
         birth = as.integer(出生年次),
         share = 得票率)

candidates.2008 <- candidates.2008 %>%
  mutate(top = ifelse(號次 == 1, 1, 0),
         sex = ifelse(性別 == "男", 1, 0),
         incumbent = ifelse(是否現任 == "是", 1, 0),
         birth = as.integer(出生年次),
         share = 得票率)

candidates <- candidates %>%
  mutate(top = ifelse(號次 == 1, 1, 0),
         sex = ifelse(性別 == "男", 1, 0),
         incumbent = ifelse(是否現任 == "是", 1, 0),
         birth = as.integer(出生年次),
         share = 得票率,
         year = as.character(year))

ols <- lm(share ~ top + sex + incumbent + birth + year, candidates)
ols.2020 <- lm(share ~ top + sex + incumbent + birth, candidates.2020)
ols.2016 <- lm(share ~ top + sex + incumbent + birth, candidates.2016)
ols.2012 <- lm(share ~ top + sex + incumbent + birth, candidates.2012)
ols.2008 <- lm(share ~ top + sex + incumbent + birth, candidates.2008)

plm <- plm(share ~ top + sex + incumbent + birth + year,
          data = candidates,
          index = c("year"),
          model = "within")

knitr::kable(get_regression_table(ols))

term	estimate	std_error	statistic	p_value	lower_ci	upper_ci
intercept	-1.090	0.818	-1.333	0.183	-2.695	0.514
top	0.041	0.011	3.727	0.000	0.019	0.062
sex	-0.006	0.011	-0.525	0.600	-0.026	0.015
incumbent	0.375	0.011	34.456	0.000	0.354	0.397
birth	0.001	0.000	1.460	0.145	0.000	0.001
year: 2012	0.068	0.014	4.827	0.000	0.040	0.096
year: 2016	0.026	0.013	1.957	0.051	0.000	0.053
year: 2020	0.004	0.013	0.267	0.789	-0.023	0.030

knitr::kable(get_regression_table(ols.2020))

term	estimate	std_error	statistic	p_value	lower_ci	upper_ci
intercept	-1.359	1.285	-1.057	0.291	-3.885	1.168
top	0.018	0.019	0.917	0.360	-0.020	0.056
sex	-0.037	0.016	-2.314	0.021	-0.069	-0.006
incumbent	0.405	0.020	20.565	0.000	0.366	0.443
birth	0.001	0.001	1.160	0.247	-0.001	0.002

knitr::kable(get_regression_table(ols.2016))

term	estimate	std_error	statistic	p_value	lower_ci	upper_ci
intercept	-2.035	1.595	-1.276	0.203	-5.171	1.102
top	0.049	0.023	2.159	0.032	0.004	0.094
sex	-0.002	0.021	-0.094	0.925	-0.044	0.040
incumbent	0.385	0.024	16.178	0.000	0.338	0.432
birth	0.001	0.001	1.357	0.176	0.000	0.003

knitr::kable(get_regression_table(ols.2012))

term	estimate	std_error	statistic	p_value	lower_ci	upper_ci
intercept	-2.014	2.054	-0.981	0.328	-6.059	2.030
top	0.068	0.024	2.777	0.006	0.020	0.116
sex	0.020	0.026	0.780	0.436	-0.031	0.072
incumbent	0.336	0.025	13.459	0.000	0.287	0.385
birth	0.001	0.001	1.058	0.291	-0.001	0.003

knitr::kable(get_regression_table(ols.2008))

term	estimate	std_error	statistic	p_value	lower_ci	upper_ci
intercept	1.597	1.890	0.845	0.399	-2.122	5.317
top	0.026	0.022	1.197	0.232	-0.017	0.069
sex	0.021	0.024	0.846	0.398	-0.027	0.069
incumbent	0.366	0.020	18.366	0.000	0.327	0.406
birth	-0.001	0.001	-0.802	0.423	-0.003	0.001

coeftest(plm, vcov. = vcovHC, type = "HC1")

## 
## t test of coefficients:
## 
##              Estimate  Std. Error t value  Pr(>|t|)    
## top        0.04080519  0.01040288  3.9225  9.22e-05 ***
## sex       -0.00553474  0.01343974 -0.4118   0.68054    
## incumbent  0.37545948  0.01238707 30.3106 < 2.2e-16 ***
## birth      0.00060766  0.00030180  2.0135   0.04427 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1