Econ 710 PS2 Code

#Environment
rm(list=ls())
setwd("/Users/yendindin/Desktop/R/Econme 2")
library(haven)
library(dplyr)
library(ivreg)
library(stargazer)
data <- read_dta("/Users/yendindin/Library/Mobile Documents/com~apple~CloudDocs/Master/Master Course/UWM/2021 Spring/Econometrics II/PS/2/AE80.dta")

#Sample
data.m <- data %>%
  filter(msample==1) %>%
  select(35,36,33,34,38,37,40,39,42,44,17,16,14,15,12,13,18,19,20,21,22,23,28,29,31,32)
data.w <- data %>%
  select(35,36,33,34,38,37,40,39,42,44,17,16,14,15,12,13,18,19,20,28,29,31,32)

#(1)
dep_var_w <- c("workedm","weeksm1","hourswm","incomem","famincl")
ind_var_w <- "morekids+agem1+agefstm+boy1st+boy2nd+blackm+hispm+othracem"

for(i in 1:length(dep_var_w)){
  f <- as.formula(paste(dep_var_w[i],ind_var_w,sep="~"))
  res <- data.w %>%
    lm(formula = f,data=.)
  res_esti <- coef(summary(res))[2,][1:2]
  if(i==1){
    df <- as.data.frame(t(res_esti))
  }else{
    df <- rbind(df,t(res_esti))
  }
}
df.1 <- df

#(2)
tsls_dep_var_w <-"morekids+agem1+agefstm+boy1st+boy2nd+blackm+hispm+othracem |
                samesex+agem1+agefstm+boy1st+boy2nd+blackm+hispm+othracem"
for(i in 1:length(dep_var_w)){
  f <- as.formula(paste(dep_var_w[i],tsls_dep_var_w,sep="~"))
  res <- data.w %>%
    ivreg(formula = f,data=.)
  res_esti <- coef(summary(res))[2,][1:2]
  if(i==1){
    df <- as.data.frame(t(res_esti))
  }else{
    df <- rbind(df,t(res_esti))
  }
}
df.2 <- df

#(5)
tsls_dep_var_mw <-"morekids+agem1+agefstm+boy1st+boy2nd+blackm+hispm+othracem |
                samesex+agem1+agefstm+boy1st+boy2nd+blackm+hispm+othracem"
dep_var_mw <- c("workedm","weeksm1","hourswm","incomem","famincl","nonmomil")

for(i in 1:length(dep_var_mw)){
  f <- as.formula(paste(dep_var_mw[i],tsls_dep_var_mw,sep="~"))
  res <- data.m %>%
    ivreg(formula = f,data=.)
  res_esti <- coef(summary(res))[2,][1:2]
  if(i==1){
    df <- as.data.frame(t(res_esti))
  }else{
    df <- rbind(df,t(res_esti))
  }
}
df.3 <- df

#(7)
dep_var_mm <- c("workedd","weeksd1","hourswd","incomed")
ind_var_m <- "morekids+aged1+agefstd+boy1st+boy2nd+blackd+hispd+othraced"
for(i in 1:length(dep_var_mm)){
  f <- as.formula(paste(dep_var_mm[i],ind_var_m,sep="~"))
  res <- data.m %>%
    lm(formula = f,data=.)
  res_esti <- coef(summary(res))[2,][1:2]
  if(i==1){
    df <- as.data.frame(t(res_esti))
  }else{
    df <- rbind(df,t(res_esti))
  }
}
df.4 <- df

#(8)
tsls_dep_var_mm <-"morekids+aged1+agefstd+boy1st+boy2nd+blackd+hispd+othraced |
                samesex+aged1+agefstd+boy1st+boy2nd+blackd+hispd+othraced"
dep_var_mm <- c("workedd","weeksd1","hourswd","incomed")

for(i in 1:length(dep_var_mm)){
  f <- as.formula(paste(dep_var_mm[i],tsls_dep_var_mm,sep="~"))
  res <- data.m %>%
    ivreg(formula = f,data=.)
  res_esti <- coef(summary(res))[2,][1:2]
  if(i==1){
    df <- as.data.frame(t(res_esti))
  }else{
    df <- rbind(df,t(res_esti))
  }
}
df.5 <- df

#Check relevance
fsls_var_w <-"morekids ~ samesex+agem1+agefstm+boy1st+boy2nd+blackm+hispm+othracem"
fsls_var_mw <-"morekids ~ samesex+agem1+agefstm+boy1st+boy2nd+blackm+hispm+othracem"
fsls_var_mm <-"morekids ~ samesex+aged1+agefstd+boy1st+boy2nd+blackd+hispd+othraced"

coef(summary(lm(formula = fsls_var_w,data=data.w)))[2,][1:2]
coef(summary(lm(formula = fsls_var_mw,data=data.m)))[2,][1:2]
coef(summary(lm(formula = fsls_var_mm,data=data.m)))[2,][1:2]

#Output
df.1 <- round(df.1,3)
df.2 <- round(df.2,3)
df.3 <- round(df.3,3)
df.4 <- round(df.4,3)
df.5 <- round(df.5,3)


df.1$`Std. Error` <- paste("(",df.1$`Std. Error`,")",sep="")
df.2$`Std. Error` <- paste("(",df.2$`Std. Error`,")",sep="")
df.3$`Std. Error` <- paste("(",df.3$`Std. Error`,")",sep="")
df.4$`Std. Error` <- paste("(",df.4$`Std. Error`,")",sep="")
df.5$`Std. Error` <- paste("(",df.5$`Std. Error`,")",sep="")

cat(as.vector(t(df.1)))
cat(as.vector(t(df.2)))
cat(as.vector(t(df.3)))
cat(as.vector(t(df.4)))
cat(as.vector(t(df.5)))

#Notes: The table reports estimates of the coefficient on the More than 2 children variable in equations (4) and (6) in the text.
#Other covariates in the models are Age, Age at first birth, plus indicators for Boy 1st, Boy 2nd, Black, Hispanic, and Other race. 
#The variable Boy 2nd is excluded from equation (6). 
#The p-value for the test of overidentifying restrictions associated with equation (6) is showli in brackets. 
#Standard errors are reported in parentheses.