The fastest way to do this is with the dplyr package. This follows the same procedure as Rob mentioned in his comment above, but using dplyr::inner_join() is much faster.

Adding an updated answer for completeness' sake

The way I do this is using lapply and Reduce

dat.files <- list.files("*.csv") #whatever you need to get the files listed
dat <- lapply(dat.files, read.table, sep=",", ...)
## Now process dat so column names are consistent etc. - you might need a loop
## Once done,

dat <- Reduce(merge, dat) # or Reduce(dplyr::inner_join, dat)