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204f58d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | library("lmtest")
library("sandwich")
set.seed(2020)
## Uses the output from the data build.
main <- function(mode = "test", drop_wave_7 = T){
data <- read.csv("output/data.csv")
if (drop_wave_7) data <- data[!(data$wave == 7), ]
drop <- ifelse(drop_wave_7, "drop_7", "keep_7")
if (mode == "test"){
# Randomize data in each column independently for testing purposes.
for (i in 3:ncol(data)){
data[, i] <- sample(data[, i])
}
}
# Baseline "Long" Model
# https://www.r-econometrics.com/methods/hcrobusterrors/
# https://stats.stackexchange.com/questions/117052/replicating-statas-robust-option-in-r (HC1 matches Stata robust option)
model <- lm(gov_consumption ~ sd_gov + mean_gov +
africa + laam + asiae +
col_uka + col_espa + col_otha +
federal + oecd +
log_gdp_per_capita + trade_share + age_15_64 + age_65_plus,
data = data)
out <- coeftest(model, vcov = vcovHC(model, type = "HC1"))
# Clean and produce table
out <- rbind(out, c(length(model$residuals), "", "", ""))
out <- rbind(out, c(summary(model)$r.squared, "", "", ""))
rownames(out) <- c(rownames(out)[-c((nrow(out)-1):nrow(out))], "Obs.", "R-squared")
write.table(out, file = sprintf("output/%s_%s.txt", mode, drop))
}
# Test analysis code
main(mode = "test", drop_wave_7 = T)
main(mode = "test", drop_wave_7 = F)
# Run on real data w/o wave 7
main(mode = "real", drop_wave_7 = T)
# Run on real data w/ wave 7
main(mode = "real", drop_wave_7 = F) |