##Analysis of general elections and candidates performance
ggplot(camp, aes(
x = factor(Local_Embeddedness),
y = Vote_Share_Percentage
)) +
geom_boxplot(outlier.shape = NA, fill = "lightgrey", alpha = 0.5) +
labs(
x = "Local Embeddedness of the Candidate",
y = "Vote Share Percentage",
title = "Boxplot Showing Voteshare of Candidates by Local Embeddedness"
) +
theme_minimal() +
theme(
axis.text.x = element_text(angle = 0, hjust = 0.5)
)
ggplot(camp, aes(
x = factor(Local_Embeddedness_2019),
y = Vote_Share_Percentage
)) +
geom_boxplot(outlier.shape = NA, fill = "lightgrey", alpha = 0.5) +
labs(
x = "Local Embeddedness of the Candidate",
y = "Vote Share Percentage",
title = "Boxplot Showing Voteshare of Candidates by Local Embeddedness"
) +
theme_minimal() +
theme(
axis.text.x = element_text(angle = 0, hjust = 0.5)
)
## `summarise()` has grouped output by 'Defection.From.Another.Party.after.2014'.
## You can override using the `.groups` argument.
Years between which candidate(winner and runner-up) changed
their party
| changed party between 2015-2019 |
20 |
12.58 |
| changed party between 2020-2024 |
37 |
23.27 |
| Not Changed or changed before 2014 |
102 |
64.15 |
Proportion of candidates who changed party after 2014
| Didnot change party |
97 |
61.01 |
| Shifted party after 2014 |
62 |
38.99 |
Proportion of candidates who changed party after 2019
| Changed party after 2019 |
37 |
23.27 |
| Did not change party |
122 |
76.73 |
Whether candidate came from different State
| No |
150 |
0.943 |
| Yes |
9 |
0.057 |
Whether candidate came from different constituency
| No |
94 |
0.591 |
| Yes |
65 |
0.409 |
Percentage of candidates changed in a constituency
| Candidate changed in the Constituency |
65 |
40.88 |
| Contested by Alliance Partner in Past |
34 |
21.38 |
| Re-given Ticket |
60 |
37.74 |
Frequency and Proportion Table for Number of Times a Person
Changed Their Party
| Changed 1 time |
37 |
23.27 |
| Changed 2 to 3 times |
27 |
16.98 |
| Changed more than 4 times |
7 |
4.40 |
| Never changed |
88 |
55.35 |
Whether candidate came from different constituency and their
position in the election
| No |
0.44 |
0.56 |
| Yes |
0.58 |
0.42 |
Party and whether candidate came from different constituency in
2024 elections
| India Alliance |
0.58 |
0.42 |
| NDA |
0.60 |
0.40 |
Proportion of candidates by party-shifting period and their
party affiliation
| changed party between 2015-2019 |
0.25 |
0.75 |
| changed party between 2020-2024 |
0.84 |
0.16 |
| Not Changed or changed before 2014 |
0.42 |
0.58 |
Proportion of candidates shifting party before 2019 and their
party affiliation
| Changed party after 2019 |
0.84 |
0.16 |
| Did not change party |
0.39 |
0.61 |
Proportion of candidates shifting party before 2014 and their
party affiliation
| Didnot change party |
0.44 |
0.56 |
| Shifted party after 2014 |
0.58 |
0.42 |
Proportion of candidates changed within a constituency by their
political parties
| Candidate changed in the Constituency |
0.49 |
0.32 |
| Contested by Alliance Partner in Past |
0.41 |
0.03 |
| Re-given Ticket |
0.10 |
0.65 |
Position of candidates changed within a constituency and their
position in the election
| Candidate changed in the Constituency |
0.52 |
0.48 |
| Contested by Alliance Partner in Past |
0.56 |
0.44 |
| Re-given Ticket |
0.43 |
0.57 |
Proportion of number of times changed shifted political
affiliations and their party
| Changed 1 time |
0.24 |
0.22 |
| Changed 2 to 3 times |
0.22 |
0.12 |
| Changed more than 4 times |
0.05 |
0.04 |
| Never changed |
0.49 |
0.61 |
Proportion of number of times candidate changed shifted
political affiliations and their position in the elections
| Changed 1 time |
0.41 |
0.59 |
| Changed 2 to 3 times |
0.48 |
0.52 |
| Changed more than 4 times |
0.71 |
0.29 |
| Never changed |
0.52 |
0.48 |
Proportion of candidates by party-shifting period and their
position in the 2024 election
| changed party between 2015-2019 |
0.50 |
0.50 |
| changed party between 2020-2024 |
0.43 |
0.57 |
| Not Changed or changed before 2014 |
0.52 |
0.48 |
Average voteshare of changed and unchanged candidate within a
constituency
| Candidate changed in the Constituency |
44.61577 |
| Contested by Alliance Partner in Past |
42.41567 |
| Re-given Ticket |
43.60801 |
Average voteshare of candidate as per their party shifting
period
| Not Changed or changed before 2014 |
44.42424 |
| changed party between 2015-2019 |
42.15008 |
| changed party between 2020-2024 |
42.82066 |
Average voteshare of candidate who were from the constituency
and who came from outside
| No |
43.13643 |
| Yes |
44.67406 |
No of time candidate changed the party and their average
voteshare
| Changed 1 time |
42.36781 |
| Changed 2 to 3 times |
42.75716 |
| Changed more than 4 times |
45.30529 |
| Never changed |
44.53919 |
##
## Regression Models: Predicting Vote Share, Margin, and Turnout
## ===============================================================
## Dependent variable:
## -----------------------------------
## Vote Share % Margin % Turnout 2024
## (1) (2) (3)
## ---------------------------------------------------------------
## Times Defected 0.622 -1.499 0.267
## (0.655) (1.400) (0.355)
##
## Year of Party Change -0.001 0.002 -0.0003
## (0.001) (0.002) (0.0004)
##
## From Different Constituency 1.689 -0.746 -0.520
## (1.070) (2.288) (0.581)
##
## Party Changed Candidate -1.620 -3.738 -1.019
## (1.438) (3.073) (0.780)
##
## Muslim % -0.777 1.321 0.128
## (1.186) (2.536) (0.643)
##
## SC % -0.013 -0.021 0.184***
## (0.051) (0.108) (0.027)
##
## Rural % -0.128 -0.194 0.303***
## (0.115) (0.246) (0.062)
##
## ruralPercent_pcs -0.027 -0.036 0.015
## (0.028) (0.060) (0.015)
##
## Constant 49.409*** 26.687*** 46.174***
## (3.340) (7.141) (1.812)
##
## ---------------------------------------------------------------
## Observations 159 159 159
## R2 0.070 0.036 0.273
## Adjusted R2 0.020 -0.016 0.235
## ===============================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
Mean Vote Share and Sample Size by Defection Status, Constituency
Change, and Alliance
|
From Different Constituency
|
No Defection After 2014
|
Defection After 2014
|
|
No
|
India Alliance: 43.2 (n=26) NDA: 43.8 (n=34)
|
India Alliance: 43.7 (n=20)
NDA: 40.7 (n=14
|
|
Yes
|
India Alliance: 46.7 (n=17) NDA: 44.5 (n=20)
|
India Alliance: 42.8 (n=16)
NDA: 44.6 (n=12
|
Mean Vote Share of candidates who defected after 2019 and came from
different constituency
|
From Different Constituency
|
Changed Party After 2019
|
Did Not Change Party After 2019
|
|
No
|
India Alliance: 43.5 (n=17) NDA: 38.8 (n=3)
|
India Alliance: 43.4 (n=29)
NDA: 43.1 (n=45
|
|
Yes
|
India Alliance: 42.5 (n=14) NDA: 44.7 (n=3)
|
India Alliance: 46.5 (n=19)
NDA: 44.5 (n=29
|
##
## Effect of Local Embeddedness
## =======================================================
## Dependent variable:
## -----------------------------
## Modi2024
## (1) (2) (3)
## -------------------------------------------------------
## Local Embeddedness (2019) -0.028 -0.047 -0.034
## (0.114) (0.124) (0.126)
## BJP 2024 Vote Share 0.009 0.014
## (0.011) (0.013)
## Diff BJP Vote Share 0.022
## (0.020)
## Margin Percentage -0.003
## (0.006)
## Turnout Change from 2019 0.036
## (0.029)
## Turnout 2024 0.006
## (0.017)
## Constant 0.444** 0.074 -0.183
## (0.183) (0.537) (1.268)
## -------------------------------------------------------
## Observations 77 72 72
## R2 0.001 0.013 0.052
## Adjusted R2 -0.013 -0.015 -0.035
## =======================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## Effect of Local Embeddedness
## ======================================================
## Dependent variable:
## -----------------------------
## Modi2024
## (1) (2) (3)
## ------------------------------------------------------
## Local Embeddedness 0.035 0.024 0.036
## (0.092) (0.097) (0.100)
## BJP 2024 Vote Share 0.010 0.014
## (0.011) (0.013)
## Diff BJP Vote Share 0.023
## (0.020)
## Margin Percentage -0.003
## (0.006)
## Turnout Change from 2019 0.037
## (0.029)
## Turnout 2024 0.005
## (0.017)
## Constant 0.359*** -0.053 -0.233
## (0.132) (0.496) (1.251)
## ------------------------------------------------------
## Observations 77 72 72
## R2 0.002 0.012 0.053
## Adjusted R2 -0.011 -0.016 -0.034
## ======================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
library(ggplot2)
ggplot(camp, aes(x = Margin_Percentage, y = turnout_2024)) +
geom_point(color = "steelblue", alpha = 0.7, size = 2) +
geom_smooth(method = "lm", se = TRUE, color = "darkred", linetype = "dashed") +
labs(
title = "Relationship Between Margin Percentage and Turnout (2024)",
x = "Margin Percentage",
y = "Turnout Percentage (2024)"
) +
theme_minimal(base_size = 14) +
theme(
plot.title = element_text(hjust = 0.5)
)
## `geom_smooth()` using formula = 'y ~ x'
##
## ===============================================================================================
## Dependent variable:
## ---------------------------------------------------------------------------
## Bjp24voteshare
## (1) (2) (3) (4)
## -----------------------------------------------------------------------------------------------
## Modi2024 1.183 2.162
## (1.315) (2.960)
##
## Local_Embeddedness -0.295 0.035
## (1.071) (1.452)
##
## Int_bw_le_Rally 0.383 -0.712
## (0.797) (1.943)
##
## Constant 43.195*** 44.041*** 43.475*** 43.123***
## (0.917) (1.536) (0.856) (2.069)
##
## -----------------------------------------------------------------------------------------------
## Observations 72 72 72 72
## R2 0.011 0.001 0.003 0.015
## Adjusted R2 -0.003 -0.013 -0.011 -0.029
## Residual Std. Error 6.350 (df = 70) 6.383 (df = 70) 6.376 (df = 70) 6.432 (df = 68)
## F Statistic 0.810 (df = 1; 70) 0.076 (df = 1; 70) 0.231 (df = 1; 70) 0.337 (df = 3; 68)
## ===============================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ===============================================================================================
## Dependent variable:
## ---------------------------------------------------------------------------
## Diff_BJP_voteshare
## (1) (2) (3) (4)
## -----------------------------------------------------------------------------------------------
## Modi2024 0.750 0.256
## (0.765) (1.723)
##
## Local_Embeddedness 0.123 -0.072
## (0.624) (0.845)
##
## Int_bw_le_Rally 0.468 0.361
## (0.462) (1.131)
##
## Constant -7.326*** -7.179*** -7.265*** -7.222***
## (0.533) (0.895) (0.496) (1.205)
##
## -----------------------------------------------------------------------------------------------
## Observations 72 72 72 72
## R2 0.014 0.001 0.014 0.015
## Adjusted R2 -0.001 -0.014 0.0004 -0.028
## Residual Std. Error 3.695 (df = 70) 3.719 (df = 70) 3.693 (df = 70) 3.745 (df = 68)
## F Statistic 0.960 (df = 1; 70) 0.039 (df = 1; 70) 1.026 (df = 1; 70) 0.355 (df = 3; 68)
## ===============================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ===============================================================================================
## Dependent variable:
## ---------------------------------------------------------------------------
## Margin_Percentage
## (1) (2) (3) (4)
## -----------------------------------------------------------------------------------------------
## Modi2024 -1.772 6.190
## (2.631) (5.748)
##
## Local_Embeddedness 1.779 5.074*
## (2.074) (2.757)
##
## Int_bw_le_Rally -1.321 -5.962
## (1.587) (3.778)
##
## Constant 20.836*** 17.653*** 20.809*** 14.402***
## (1.824) (3.023) (1.696) (3.911)
##
## -----------------------------------------------------------------------------------------------
## Observations 77 80 77 77
## R2 0.006 0.009 0.009 0.053
## Adjusted R2 -0.007 -0.003 -0.004 0.014
## Residual Std. Error 13.029 (df = 75) 13.108 (df = 78) 13.008 (df = 75) 12.890 (df = 73)
## F Statistic 0.453 (df = 1; 75) 0.736 (df = 1; 78) 0.693 (df = 1; 75) 1.365 (df = 3; 73)
## ===============================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ===============================================================================================
## Dependent variable:
## ---------------------------------------------------------------------------
## turnoutchangefrom2019
## (1) (2) (3) (4)
## -----------------------------------------------------------------------------------------------
## Modi2024 0.516 1.926 1.926
## (0.561) (1.241) (1.241)
##
## Local_Embeddedness -0.065 0.412 0.412
## (0.451) (0.595) (0.595)
##
## Int_bw_le_Rally -1.036 -1.036
## (0.816) (0.816)
##
## Constant -2.445*** -2.157*** -2.988*** -2.988***
## (0.389) (0.646) (0.844) (0.844)
##
## -----------------------------------------------------------------------------------------------
## Observations 77 77 77 77
## R2 0.011 0.0003 0.033 0.033
## Adjusted R2 -0.002 -0.013 -0.007 -0.007
## Residual Std. Error 2.776 (df = 75) 2.791 (df = 75) 2.782 (df = 73) 2.782 (df = 73)
## F Statistic 0.847 (df = 1; 75) 0.021 (df = 1; 75) 0.831 (df = 3; 73) 0.831 (df = 3; 73)
## ===============================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ===============================================================================================
## Dependent variable:
## ---------------------------------------------------------------------------
## turnout_2024.x
## (1) (2) (3) (4)
## -----------------------------------------------------------------------------------------------
## Modi2024 0.019 -0.021
## (0.833) (0.832)
##
## Local_Embeddedness 0.847 0.743
## (0.638) (0.666)
##
## Int_bw_le_Rally -0.178
## (0.502)
##
## Constant 56.946*** 55.967*** 57.046*** 56.036***
## (0.577) (0.931) (0.537) (0.998)
##
## -----------------------------------------------------------------------------------------------
## Observations 77 80 77 77
## R2 0.00001 0.022 0.002 0.017
## Adjusted R2 -0.013 0.010 -0.012 -0.010
## Residual Std. Error 4.122 (df = 75) 4.035 (df = 78) 4.119 (df = 75) 4.116 (df = 74)
## F Statistic 0.001 (df = 1; 75) 1.761 (df = 1; 78) 0.126 (df = 1; 75) 0.623 (df = 2; 74)
## ===============================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
## Warning: package 'pander' was built under R version 4.4.3
regbvs <- lm(Bjp24voteshare~ Modi2024 ,rally_dataset_final)
egbvs3 <- lm(Bjp24voteshare~ Local_Embeddedness_2019 ,rally_dataset_final)
regbvs4 <- lm(Bjp24voteshare~ Int_bw_le_Rally,rally_dataset_final)
egbvs2 <- lm(Bjp24voteshare~ Modi2024 + Int_bw_le_Rally+ Local_Embeddedness_2019 ,rally_dataset_final)
stargazer(regbvs, egbvs3, regbvs4, egbvs2, type= "text")
##
## ===================================================================================================
## Dependent variable:
## ---------------------------------------------------------------------------
## Bjp24voteshare
## (1) (2) (3) (4)
## ---------------------------------------------------------------------------------------------------
## Modi2024 1.183 0.810
## (1.315) (2.835)
##
## Local_Embeddedness_2019 -1.389 -1.442
## (1.353) (1.694)
##
## Int_bw_le_Rally 0.383 0.213
## (0.797) (1.780)
##
## Constant 43.195*** 45.793*** 43.475*** 45.439***
## (0.917) (2.198) (0.856) (2.824)
##
## ---------------------------------------------------------------------------------------------------
## Observations 72 72 72 72
## R2 0.011 0.015 0.003 0.025
## Adjusted R2 -0.003 0.001 -0.011 -0.018
## Residual Std. Error 6.350 (df = 70) 6.339 (df = 70) 6.376 (df = 70) 6.398 (df = 68)
## F Statistic 0.810 (df = 1; 70) 1.053 (df = 1; 70) 0.231 (df = 1; 70) 0.582 (df = 3; 68)
## ===================================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
regtp <- lm(turnout_2024.x~ Modi2024 ,rally_dataset_final)
egtp1 <- lm(turnout_2024.x~ Local_Embeddedness_2019 ,rally_dataset_final)
regtp3 <- lm(turnout_2024.x~ Int_bw_le_Rally ,rally_dataset_final)
egtp2 <- lm(turnout_2024.x~ Modi2024 + Local_Embeddedness_2019 ,rally_dataset_final)
stargazer(regtp, egtp1, regtp3, egtp2, type = "text")
##
## ===================================================================================================
## Dependent variable:
## ---------------------------------------------------------------------------
## turnout_2024.x
## (1) (2) (3) (4)
## ---------------------------------------------------------------------------------------------------
## Modi2024 0.019 0.030
## (0.833) (0.837)
##
## Local_Embeddedness_2019 0.490 0.364
## (0.799) (0.825)
##
## Int_bw_le_Rally -0.178
## (0.502)
##
## Constant 56.946*** 56.300*** 57.046*** 56.394***
## (0.577) (1.301) (0.537) (1.381)
##
## ---------------------------------------------------------------------------------------------------
## Observations 77 80 77 77
## R2 0.00001 0.005 0.002 0.003
## Adjusted R2 -0.013 -0.008 -0.012 -0.024
## Residual Std. Error 4.122 (df = 75) 4.071 (df = 78) 4.119 (df = 75) 4.145 (df = 74)
## F Statistic 0.001 (df = 1; 75) 0.375 (df = 1; 78) 0.126 (df = 1; 75) 0.097 (df = 2; 74)
## ===================================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
ggplot(camp, aes(x = turnout_2024, y = turnout2019)) +
geom_point(color = "steelblue", alpha = 0.7, size = 2) +
geom_smooth(method = "lm", se = TRUE, color = "darkred", linetype = "dashed") +
labs(
title = "Turnout in 2024 vs Turnout in 2019",
x = "Turnout Percentage (2024)",
y = "Turnout Percentage (2019)"
) +
theme_minimal(base_size = 14) +
theme(
plot.title = element_text(hjust = 0.5)
)
## `geom_smooth()` using formula = 'y ~ x'
##
## ===============================================
## Dependent variable:
## ---------------------------
## turnout_2024
## -----------------------------------------------
## Local_Embeddedness -0.073
## (0.266)
##
## turnout2019 0.707***
## (0.041)
##
## Constant 15.247***
## (2.432)
##
## -----------------------------------------------
## Observations 159
## R2 0.656
## Adjusted R2 0.651
## Residual Std. Error 2.388 (df = 156)
## F Statistic 148.590*** (df = 2; 156)
## ===============================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ===================================================
## Dependent variable:
## ---------------------------
## Vote_Share_Percentage
## ---------------------------------------------------
## Local_Embeddedness_2019 -0.342
## (0.786)
##
## Constant 44.230***
## (1.190)
##
## ---------------------------------------------------
## Observations 159
## R2 0.001
## Adjusted R2 -0.005
## Residual Std. Error 6.605 (df = 157)
## F Statistic 0.189 (df = 1; 157)
## ===================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ===================================================
## Dependent variable:
## ---------------------------
## Margin_Percentage
## ---------------------------------------------------
## Local_Embeddedness_2019 0.131
## (1.652)
##
## Constant 19.136***
## (2.499)
##
## ---------------------------------------------------
## Observations 159
## R2 0.00004
## Adjusted R2 -0.006
## Residual Std. Error 13.877 (df = 157)
## F Statistic 0.006 (df = 1; 157)
## ===================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ===================================================
## Dependent variable:
## ---------------------------
## turnout_change
## ---------------------------------------------------
## Local_Embeddedness_2019 -0.049
## (0.327)
##
## Constant -2.149***
## (0.495)
##
## ---------------------------------------------------
## Observations 159
## R2 0.0001
## Adjusted R2 -0.006
## Residual Std. Error 2.748 (df = 157)
## F Statistic 0.022 (df = 1; 157)
## ===================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
Average difference in turnout when candidates where from same
constituency VS different
| Both Different |
-2.403235 |
| Both Same |
-2.652698 |
| One Different |
-1.667742 |
Average Mobilization when candidat came from differen
constituency
| Both Different |
2439.240 |
| Both Same |
2553.789 |
| One Different |
2467.833 |
Average turnout when candidates were from different vs same
constituency
| Both Different |
57.35265 |
| Both Same |
57.81905 |
| One Different |
56.03516 |
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: Removed 47 rows containing non-finite outside the scale range
## (`stat_density()`).
dis <-lm(formula = turnout_change~ Candidate_changed_party_after_2019 +
From.different.constituency, data = camp)
stargazer(dis, type = "text")
##
## ==================================================================================
## Dependent variable:
## ---------------------------
## turnout_change
## ----------------------------------------------------------------------------------
## Candidate_changed_party_after_2019Did not change party 0.270
## (0.517)
##
## From.different.constituencyYes 0.289
## (0.444)
##
## Constant -2.540***
## (0.496)
##
## ----------------------------------------------------------------------------------
## Observations 159
## R2 0.004
## Adjusted R2 -0.009
## Residual Std. Error 2.751 (df = 156)
## F Statistic 0.329 (df = 2; 156)
## ==================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01