Hi, everyone!
I want to make the following operation for the years 2013-2017. The code I have written here works very well for 2017, but I don't to write almost exactly the same thing for all years. Therefore I was thinking of making a FOR-loop. The only thing I would have to do to end up with a data.frame for all years would be to change the 2017 to any other year.
Does anyone have an idea of how to do this?
Merging datasets:
T <- data.frame(equipment_pct$2017, infrastructure_pct$2017, other_pct$2017, personnel_pct$2017, pwt91_xr$2017,
poecd_ppp_series$2017, oecd_ppp_series$2017, w$2017)
Changing the variable names
names(T) <- c("qequip_2017", "qinfra_2017", "qother_2017", "qpers_2017", "pequip_2017", "pinfra_2017", "pother_2017", "ppers_2017")
Data frame with quantities
Tq <- data.frame(equipment_pct$2017, infrastructure_pct$2017, other_pct$2017, personnel_pct$2017)
Data frame with prices
Tp <- data.frame(pwt91_xr$2017, poecd_ppp_series$2017, oecd_ppp_series$2017, w$2017)
Changing variable names
names(Tp) <- c("pequip_2017", "pinfra_2017", "pother_2017", "ppers_2017")
Vector with quantity names
names(Tq) <- c("qequip_2017", "qinfra_2017", "qother_2017", "qpers_2017")
Vectors with names of prices and quantities
prices <- colnames(Tp)
quantities <- colnames(Tq)
Making a FOR-loop to compute the fisher index for all countries as a base. This will be stored in a list in the global environment.
output <- matrix(NA, nrow=22, ncol=22)
for (tt in 1:22) {
output[[tt]] <- as.data.frame(priceIndex(prices, quantities, tt, T, method= "Fisher"))
}
Extracting the columns i need from the list.
f_2017 <- do.call(cbind.data.frame, output[1:22])
Naming rows and columns
rownames(f_2017) <- country_vector
colnames(f_2017) <- paste("base", rownames(f_2017), sep=".")
Applying the eks-method on the fisher-matrix
eks_2017 <- eks(f_2017)
colnames(eks_2017) <- paste("base", rownames(eks_2017), sep=".")
So, I would like to end up with 5 data frames, called eks_2013, eks_2014 etc...
I was thinking of something like this to start with:
Merging datasets:
year <- c(2013:2017)
for (tt in year) {
T[tt] <- data.frame(equipment_pct$tt, infrastructure_pct$tt, other_pct$tt, personnel_pct$tt, pwt91_xr$tt,
oecd_ppp_series$tt, oecd_ppp_series$tt, w$tt)
}
But I can't make it work.
Thanks! 