Looping regressions in the tidy verse

tidy_regression_loop.r

library(gapminder)
library(tidyverse)
library(broom)
library(huxtable)
library(lfe)

# Example dataset (via gapminder package)
glimpse(gapminder)

# Create a function to make looping easier
lagged_felm <- function(yvar, tlags, fe) {
  lags_formula <- paste("lag(gdpPercap, ", 1:tlags, ")", sep = "", collapse = " + ")
  lags_formula <- paste("gdpPercap +", lags_formula)
  felm_formula <- paste(yvar, " ~ ", lags_formula, " | ", fe)
  felm_est     <- felm(as.formula(felm_formula), data = gapminder)
  return_df    <- tidy(felm_est) %>% mutate(yvar = yvar)
  return(felm_est)
}

yvars <- c("lifeExp", "pop")
lags  <- seq(1, 2)
fes   <- c("country", "year", "continent", "continent + year")

cross_args <- cross_df(list(yvar  = yvars,
                            tlags = lags,
                            fe    = fes))

results <- cross_args %>% pmap(lagged_felm)

lifeExpTable <- results[which(cross_args$yvar == "lifeExp")]
popTable     <- results[which(cross_args$yvar == "pop")]

do.call(stargazer, lifeExpTable)
do.call(stargazer, popTable)

# End of script