estimates_from_microdata.R

library(rlang)
library(dplyr)

it14ih <- data.frame(hid = 1:6,
                     hi11 = c(3601, 13190, 0,  11479, 0, 4713),
                     hi13 = c(973, 0, 0, 478, 815, 399),
                     hi12 = c(0, 0, 0,  0, 0, 842),
                     hicapital = c(40, 41, 0, 100, 0, 83),
                     hpopwgt = c(567.1, 5308.3, 666.7, 
                                 692.2, 254.2, 632.6)
                     )

# Lower-level function
compute_column_from_formula <- function(data, formula) {
  # Check if the input is a data.frame
  if (!is.data.frame(data)) {
    stop("The first argument should be a data.frame")
  }
  
  # Check if the input is a formula
  if (!rlang::is_formula(formula)) {
    stop("The second argument should be a formula")
  }
  
  # Extract the left-hand and right-hand sides of the formula
  lhs <- as.character(formula[[2]])
  rhs <- formula[[3]]
  
  # Evaluate the right-hand side expression
  new_column_values <- eval(rhs, data)
  
  # Add the new column to the data.frame with the name from the left-hand side of the formula
  data[[lhs]] <- new_column_values
  
  # Return the updated data.frame
  return(data)
}

# Higher-level function
compute_columns_from_formulas <- function(data, formulas) {
  # Check if the input is a data.frame
  if (!is.data.frame(data)) {
    stop("The first argument should be a data.frame")
  }
  
  # Check if the input is a list of formulas
  if (!is.list(formulas) || !all(sapply(formulas, rlang::is_formula))) {
    stop("The second argument should be a list of formulas")
  }
  
  # Iterate through the list of formulas and add a new column for each formula
  for (formula in formulas) {
    data <- compute_column_from_formula(data, formula)
  }
  
  # Return the updated data.frame
  return(data)
}


estimates_from_microdata <- function(data, formulas, weights){
  
  df <- compute_columns_from_formulas(data, formulas)
  
  # weighted sum of new variables
  new_vars <- purrr::map_chr(formulas, ~as.character(.x[[2]]))
  
  tibble::enframe(purrr::map2_dbl(set_names(new_vars), weights, .f = function(var, weights, data){sum(df[[var]] * df[[weights]])}, data),
                  name = "indicator")
  
}

estimates_from_microdata(data = it14ih, 
                         formulas = list(D11P ~ hi11 + hi13,
                                         `B3GR+D41R+D42R+D45R` ~ hi12 + hicapital), 
                         weights = c("hpopwgt", "hpopwgt"))