- Code
rm(list=ls())
setwd("/Users/yendindin/Desktop/R/Econme 2")
library(haven)
library(dplyr)
library(ivreg)
library(sandwich)
library(dummies)
#data import
data <- read.csv("/Users/yendindin/Library/Mobile Documents/com~apple~CloudDocs/Master/Master Course/UWM/2021 Spring/Econometrics II/PS/3/AK91.csv")
data <- data %>%
filter(sob<51)
#dummy construction
yobdf <- dummy(data$yob, sep = "")
qobdf <- dummy(data$qob, sep = "")
sobdf <- dummy(data$sob, sep = "")
data <- data %>%
cbind(yobdf) %>%
cbind(qobdf) %>%
cbind(sobdf)
#2SLS formula
f1 <- paste("educ",
paste(colnames(yobdf)[-1],collapse = "+"),
paste(colnames(sobdf)[-1],collapse="+"),
sep="+")
f2 <- paste(paste(colnames(qobdf)[-1],collapse = "+"),
paste(colnames(yobdf)[-1],collapse = "+"),
paste(colnames(sobdf)[-1],collapse="+"),
sep="+")
f <- formula(paste("lwage~",f1,"|",f2,sep=""))
#2SLS
res <- ivreg(f,data=data)
restbl <- summary(res, vcov = sandwich, diagnostics = TRUE)
resbeta1 <- round(restbl$coefficients[2,],3)
#Note: Sandwich function for calculating heteroskadasticity robust standard error
- Result of beta 1
print(resbeta1)
Estimate Std. Error t value Pr(>|t|)
0.121 0.021 5.812 0.000
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