#' Importing to Export
#'
#' @name i2e
#' @param x A Leontief decomposed Inter-Country Input Output table as created by decompr
#' @param by variable to subset by
#' @param subset value(s) of the subset variable to select
#' @export
#' @import decompr
#' @examples
#' # load the decompr package
#' library(decompr)
#'
#' # load the example data set
#' data(leather)
#' attach(leather)
#'
#' # create a leontief decomposed data set
#' l <- decomp(x = inter,
#' y = final,
#' k = countries,
#' i = industries,
#' o = out)
#'
#' # apply the Import to Exports analysis
#' i2e( l )
i2e <- function( x, by=NULL, subset=NULL ) {
# read attributes
k <- attr(x, "k")
i <- attr(x, "i")
# rownam <- attr(x, "rownam")
G <- length(k)
N <- length(i)
# select observations
if (!is.null(by)) {
position <- which(names(x) == by)
x[which(x[position] != subset),]$FVAX <- 0
}
# transform back to 2dim x 2dim matrix
x <- matrix(x[,5], nrow=G*N, byrow=TRUE)
# remove exports to self
f <- x - diagonals::fatdiag(diagonals::fatdiag(x, steps=G), steps=G )
# sum over columns
f <- colSums( f )
# # divide by own exports
# for (j in 1:N) {
# s <- seq( ((j-1)*N + 1), j*N )
# f[s] <- f[s] / sum(colSums(x[,s]))
# }
f <- as.data.frame(f)
f <- cbind(rep(k, each = N),
rep(i, times = G),
f)
rownames(f) <- NULL
names(f) <- c("country", "sector", "i2e")
return(f)
}
# alias
#' Vertical Specialization
#' @rdname i2e
vertical_specialisation <- i2e
# Americano alias
#' Vertical Specialisation
#' @rdname i2e
vertical_specialization <- i2e
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