# ==============================================================================
# Wooldridge - Capitulo 9 - Exemplo 9.3
# Update: 13/09/2022
# ==============================================================================

rm(list = ls())

# Pacotes
library(wooldridge)
library(tidyverse)
library(stargazer)

# Base de dados
data('wage2')
head(wage2)

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

# Criar variavel dependente em log (duas formas)

wage2$lnwage <- log(wage2$wage) # basic
wage2 <- mutate(wage2, lnwage = log(wage)) # tidyverse

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

# Estima regressao 1
reg1 <- lm(lwage ~ educ + exper + tenure + married + south + urban + black, data = wage2)
summary(reg1)

# Estima regressao 2
reg2 <- lm(lwage ~ educ + exper + tenure + married + south + urban + black + IQ, data = wage2)
summary(reg2)

# Estima regressao 3
reg3 <- lm(lwage ~ educ + exper + tenure + married + south + urban + black + IQ + educ:IQ, data = wage2)
summary(reg3)

# Compara resultados
stargazer(reg1, reg2, reg3, type = 'text', keep.stat = c('n', 'rsq'))

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

# Incluindo teste KWW como proxy para habilidade

# estimar regressao 5
reg5 <- lm(lwage ~ educ + exper + tenure + married + south + urban + black + KWW, data = wage2)
summary(reg5)

# estimar regressao 6
reg6 <- lm(lwage ~ educ + exper + tenure + married + south + urban + black + IQ + KWW, data = wage2)
summary(reg6)

# estimar regressao 7
reg7 <- lm(lwage ~ educ + exper + tenure + married + south + urban + black + KWW + KWW:educ, data = wage2)
# ou
# reg7 <- lm(lwage ~ exper + tenure + married + south + urban + black + KWW*educ, data = wage2)
summary(reg7)