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#' Mean years of schooling
#'
#' \code{emean} is a function to compute mean years of schooling for any group of
#' countries included in the dataset developed in Jorda and Alonso (2017).
#' It is computed as the average of the national years of schooling
#' weighted by population weights.
#'
#' @param countries character vector with the country codes of the countries
#' to be used. Some macro-regions are already defined and can be used
#' instead of the country codes: \code{South Asia, Europe and Central Asia,
#' Middle East and North Africa, Latin America and the Caribbean, Advanced
#' Economies, Sub-Saharan Africa, East Asia and the Pacific} and \code{all}
#' for the 142 counrties included in the dataset.(see \code{data_country}).
#' @param init.y the first year in which the function is calculated. Available
#' years are 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010.
#' @param final.y the last year in which the function is calculated Available
#' years are 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010.
#' @param database population subgrup for which the function is calculated.
#' The following options are available:
#' \enumerate{
#' \item \code{"total15"}: Total population aged over-15.
#' \item \code{"total25"}: Total population aged over-25.
#' \item \code{"male15"}: Male population aged over-15.
#' \item \code{"male25"}: Male population aged over-25.
#' \item \code{"female15"}: Female population aged over-15.
#' \item \code{"female25"}: Female population aged over-25.
#' }
#' @param plot if \code{TRUE} (the default), displays a graph of the results.
#' @return \code{emean} returns a list with the following objects:
#' \enumerate{
#' \item \code{mean_years_of_schooling}: evolution of mean years of
#' schooling from the initial to the last year.
#' \item \code{countries}: countries used to compute mean years of schooling.
#' \item If \code{plot = TRUE}, graphical representation of the numerical results.
#' }
#' @seealso \code{\link{data_country}}. Visit \url{http://www.educationdata.unican.es}
#' for more information on the constructoin of the dataset and the available
#' \href{http://www.educationdata.unican.es/countries}{countries}.
#' @references Jorda, V. and Alonso, J.M. (2017). New estimates on educational
#' attainment using a continuous approach (1970-2010), World Development,
#' 90, 281 - 293.
#' \url{http://www.sciencedirect.com/science/article/pii/S0305750X16305010}
#' @export
#' @examples
#' emean(countries = "Advanced Economies", init.y = 1980, final.y = 2000,
#' database = "male25")
#' emean(countries = c("DNK", "FIN", "ISL", "NOR", "SWE"), init.y = 1980,
#' final.y = 2000, database = "male25")
emean <- function(countries, init.y, final.y, database, plot = TRUE) {
if (init.y < 1970){init.y = 1970}
if (final.y > 2010){final.y = 2010}
if (final.y < init.y){
print("Initial year must be earlier than final year.")
stop()
}
if((init.y/5)%%1 != 0 | init.y == "" ) {
print("Starting year incorrectly specified")
stop()
}
if (final.y == "" | (final.y/5)%%1 != 0 ) {
print("Final year incorrectly specified")
stop()
}
if (database != "total15" & database != "total25" &
database != "male15" & database != "male25" &
database != "female15" & database != "female25"|
database == "") {
print("Database incorrectly specified. Use total15, total25, male15, male25, female15 or female25.")
stop()
}
if (database == "total15") {
dataset <- ineq_total15
}
if (database == "total25") {
dataset <- ineq_total25
}
if (database == "male15") {
dataset <- ineq_male15
}
if (database == "male25") {
dataset <- ineq_male25
}
if (database == "female15") {
dataset <- ineq_female15
}
if (database == "female25") {
dataset <- ineq_female25
}
if(any(countries %in% levels(data_countries$Region))){
if (length(which(countries %in% levels(data_countries$Region)))<2) {
countries<-data_countries$Code[data_countries$Region ==
countries[which(countries %in% levels(data_countries$Region))]]
}
else{
print("More than two regions used as countries.")
stop()
}
}
if(any(countries == "all")){
countries<-data_countries$Code
}
countries = as.data.frame(countries)
ok.data = merge(x = dataset, y = countries, by.x = "code", by.y = "countries")
if (nrow(ok.data) == 0) {
print("Countries are incorrectly specified. Check the list of countries.")
stop()
}
if (length(unique(ok.data$country)) != nrow(countries)) {
print("Warning: Some countries are incorrectly specified. Check the list of countries.")
}
time <- seq(init.y, final.y, 5)
mys <- matrix(NA, 1, length(time))
for(k in 1:length(time)){
x<-ok.data$mys[ok.data$year==time[k]]
w <- ok.data$pop[ok.data$year==time[k]]/sum(ok.data$pop[ok.data$year==time[k]])
mys[k] <- sum(w * x)
}
if (plot==TRUE){
plot(time, mys, xlab = "Year", ylab = "Mean years of schooling",panel.first = grid(col="gray78"),
xlim = c(min(time), max(time)), ylim = c(0,max(mys)), type = "o", pch = 20,col ="Blue")
box(lwd = 2)
}
colnames(mys) <- time
list(mean_years_of_schooling = mys, countries = unique(ok.data$country))
}
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