#' New Revealed Comparative Advantage
#'
#' @name nrca
#' @param x A decomposed Inter-Country Input Output table as created by decompr
#' @export
#' @examples
#' # load the decompr package
#' library(decompr)
#'
#' # load the example data set
#' data(leather)
#' attach(leather)
#'
#' # perform Leontief decomposition
#' l <- decomp(x = inter,
#' y = final,
#' k = countries,
#' i = industries,
#' o = out,
#' method = "leontief",
#' post = "exports" )
#'
#' # load gvc package
#' library(gvc)
#'
#' # perform New Revealed Comparative Advantage
#' nrca(l)
#'
nrca <- function ( x ) {
if ( attr(x, "long") == TRUE ) {
# extract attributes
k <- attr(x, "k")
i <- attr(x, "i")
G <- length(k)
N <- length(i)
x <- matrix(x[,5], nrow=G*N, byrow=TRUE)
# remove anything but exports to self
f <- rowSums(diagonals::fatdiag(diagonals::fatdiag(x, steps=G ), steps=G) )
t <- rowSums(diagonals::fatdiag(diagonals::fatdiag(x, steps=G ), steps=G) )
q <- sum(rowSums(diagonals::fatdiag(diagonals::fatdiag(x, steps=G ), steps=G) ))
# sum across rows (source industry)
# divide by own exports to self
for (j in 1:G) {
s <- seq( ((j-1)*N + 1), j*N )
f[s] <- f[s] / sum(f[s])
}
#
for (i in 1:N) {
p <- (seq(1:G)*N) - N + i
t[p] <- sum(t[p])
}
Eij <- f
Eit <- 1
Enj <- t
Ent <- q
} else {
# extract attributes
k <- attr(x, "k")
i <- attr(x, "i")
G <- length(k)
N <- length(i)
# remove anything but exports to self
f <- rowSums(diagonals::fatdiag(diagonals::fatdiag(x, steps=G ), steps=G) )
t <- rowSums(diagonals::fatdiag(diagonals::fatdiag(x, steps=G ), steps=G) )
q <- sum(rowSums(diagonals::fatdiag(diagonals::fatdiag(x, steps=G ), steps=G) ))
# sum across rows (source industry)
# divide by own exports to self
for (j in 1:G) {
s <- seq( ((j-1)*N + 1), j*N )
f[s] <- f[s] / sum(f[s])
}
#
for (i in 1:N) {
p <- (seq(1:G)*N) - N + i
t[p] <- sum(t[p])
}
Eij <- f
Eit <- 1
Enj <- t
Ent <- q
}
# return Bela Balassa (1965) ratio
return( (Eij/Eit)/(Enj/Ent) )
}
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