#' Select place of birth
#'
#' @param numapp path to the NUMAPP files
#' @return NUMAPP data.frame with best bpl column and cycle dates
#' @keywords internal
#' @import data.table
#' @export
select_birthplace <- function(data = numapp,
crosswalk = "/censoc/data/crosswalks/bpl_crosswalk.csv") {
data <- data[, c("ssn", "pob_state_country","pob_foreign_ind", "year_cycle", "month_cycle"), with=FALSE]
## Create foreign born dummy variable
data[, bpl_foreign_flag := 0]
data <- data[pob_foreign_ind == "f", bpl_foreign_flag := 1]
## Read in crosswalk
crosswalk <- fread(crosswalk)
## Inner-Join Crosswalk; keep only certain years
data <- merge(data, crosswalk, by.x = c("bpl_foreign_flag", "pob_state_country"), by.y=c("foreign_born", "ss_bpl"))
## Remove applications with 0 (no information) for BPL
applications <- nrow(data)
data[bpl == " "] <- NA
data <- na.omit(data, cols="bpl")
removed_na <- applications - nrow(data)
cat(removed_na, "applications removed with NA for bpl", "\n")
## Set missing values equal to 0. These will be selected last according to our selection process.
for (col in c("year_cycle", "month_cycle")) data[is.na(get(col)), (col) := 0]
## Maybe should convert this to century months in the future?
data[,"cycle_year_month" := year_cycle + (month_cycle/12)]
data$cycle_year_month[is.na(data$cycle_year_month)] <- 0
## Number of different BPL per SSN
data[, number_of_distinct_bpl:=uniqueN(bpl), by = ssn]
## Create flag (0 or 1 dichotomous var) for more than one birth place
data[, bpl_multiple_flag := (ifelse(number_of_distinct_bpl > 1, 1, 0))]
## Select most recent BPL
data <- data[data[, .I[which.max(cycle_year_month)], by=ssn]$V1]
## Recode BPL
data[,"bpl_year_cycle" := year_cycle]
data[,"bpl_month_cycle" := month_cycle]
## Recode originally missing years back to NA.
data[bpl_year_cycle == 0, bpl_year_cycle := NA]
data[bpl_month_cycle == 0, bpl_month_cycle := NA]
numapp_bpl <- data[, c("ssn", "bpl", "bpl_year_cycle", "bpl_month_cycle", "bpl_multiple_flag", "bpl_foreign_flag" ), with=FALSE]
return(numapp_bpl)
}
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