Eleições municipais: correlacionando valor da receita com valor dos bens

q1.R

tse <- read.csv("Candidatos RS municipais - 2008 e 2012.csv", header=T, sep=",")

# cargo 11 = prefeito; cargo 13 = vereador
f.tse2012p <- tse[tse$ANO_ELEICAO==2012 & tse$CD_CARGO==11,]
f.tse2012v <- tse[tse$ANO_ELEICAO==2012 & tse$CD_CARGO==13,]
f.tse2008p <- tse[tse$ANO_ELEICAO==2008 & tse$CD_CARGO==11,]
f.tse2008v <- tse[tse$ANO_ELEICAO==2008 & tse$CD_CARGO==13,]

# regressões logaritmicas - 2012
lml.tse2012p <- lm(log(f.tse2012p$VL_RECEITA) ~ log(f.tse2012p$VL_BEM))
lml.tse2012v <- lm(log(f.tse2012v$VL_RECEITA) ~ log(f.tse2012v$VL_BEM))

# regressões logaritmicas - 2008
lml.tse2008p <- lm(log(f.tse2008p$VL_RECEITA) ~ log(f.tse2008p$VL_BEM))
lml.tse2008v <- lm(log(f.tse2008v$VL_RECEITA) ~ log(f.tse2008v$VL_BEM))

# gera o gráfico
plot(tse$VL_BEM, tse$VL_RECEITA, log="xy", xlab="Valor dos Bens", ylab="Valor das Receitas", main="Eleições municipais: Receitas em função dos Bens");

# desenha as linhas que representam as regressões
abline(lml.tse2012p, col="red")
abline(lml.tse2012v, col="green")
abline(lml.tse2008p, col="blue")
abline(lml.tse2008v, col="orange")

q2.R

# regressões lineares - 2012 e 2008
lm.tse2012p <- lm(f.tse2012p$VL_RECEITA ~ f.tse2012p$VL_BEM)
lm.tse2012v <- lm(f.tse2012v$VL_RECEITA ~ f.tse2012v$VL_BEM)
lm.tse2008p <- lm(f.tse2008p$VL_RECEITA ~ f.tse2008p$VL_BEM)
lm.tse2008v <- lm(f.tse2008v$VL_RECEITA ~ f.tse2008v$VL_BEM)

summary.R

> summary(lm.tse2012p)

Call:
lm(formula = f.tse2012p$VL_RECEITA ~ f.tse2012p$VL_BEM)

Residuals:
      Min        1Q    Median        3Q       Max 
-27426951    -86736    -57031    -11998  52921991 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)       5.974e+04  7.468e+04    0.80    0.424    
f.tse2012p$VL_BEM 4.276e-02  7.318e-04   58.42   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 2343000 on 994 degrees of freedom
  (127 observations deleted due to missingness)
Multiple R-squared: 0.7745,	Adjusted R-squared: 0.7742 
F-statistic:  3413 on 1 and 994 DF,  p-value: < 2.2e-16 


#---------------------------------------------------------------

> summary(lm.tse2012v)

Call:
lm(formula = f.tse2012v$VL_RECEITA ~ f.tse2012v$VL_BEM)

Residuals:
     Min       1Q   Median       3Q      Max 
-5247321   -11455   -10180    -5653 16905486 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)       1.101e+04  1.305e+03   8.436   <2e-16 ***
f.tse2012v$VL_BEM 8.046e-03  1.208e-04  66.597   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 164400 on 16075 degrees of freedom
  (3104 observations deleted due to missingness)
Multiple R-squared: 0.2162,	Adjusted R-squared: 0.2162 
F-statistic:  4435 on 1 and 16075 DF,  p-value: < 2.2e-16


#---------------------------------------------------------------

> summary(lm.tse2008p)

Call:
lm(formula = f.tse2008p$VL_RECEITA ~ f.tse2008p$VL_BEM)

Residuals:
      Min        1Q    Median        3Q       Max 
-22252540   -101901    -83255    -36562  31751289 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)       8.626e+04  5.447e+04   1.584    0.114    
f.tse2008p$VL_BEM 3.058e-02  8.200e-04  37.296   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 1720000 on 1013 degrees of freedom
  (57 observations deleted due to missingness)
Multiple R-squared: 0.5786,	Adjusted R-squared: 0.5782 
F-statistic:  1391 on 1 and 1013 DF,  p-value: < 2.2e-16


#---------------------------------------------------------------

> summary(lm.tse2008v)

Call:
lm(formula = f.tse2008v$VL_RECEITA ~ f.tse2008v$VL_BEM)

Residuals:
    Min      1Q  Median      3Q     Max 
-880916   -9474   -8093   -4090 2767518 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)       1.023e+04  4.596e+02   22.25   <2e-16 ***
f.tse2008v$VL_BEM 9.688e-04  5.910e-05   16.39   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 55390 on 14661 degrees of freedom
  (873 observations deleted due to missingness)
Multiple R-squared: 0.018,	Adjusted R-squared: 0.01793 
F-statistic: 268.7 on 1 and 14661 DF,  p-value: < 2.2e-16