This is a very simple question, but I haven't been able to find a definitive answer, so I thought I would ask it. I use the plm package for dealing with panel data. I am attempting to use the lag function to lag a variable FORWARD in time (the default is to retrieve the value from the previous period, and I want the value from the NEXT). I found a number of old articles/questions (circa 2009) suggesting that this is possible by using k=-1 as an argument. However, when I attempt this, I get an error.
Sample code:
library(plm)
df<-as.data.frame(matrix(c(1,1,1,2,2,3,20101231,20111231,20121231,20111231,20121231,20121231,50,60,70,120,130,210),nrow=6,ncol=3))
names(df)<-c("individual","date","data")
df$date<-as.Date(as.character(df$date),format="%Y%m%d")
df.plm<-pdata.frame(df,index=c("individual","date"))
Lagging:
lag(df.plm$data,0)
##returns
1-2010-12-31 1-2011-12-31 1-2012-12-31 2-2011-12-31 2-2012-12-31 3-2012-12-31
50 60 70 120 130 210
lag(df.plm$data,1)
##returns
1-2010-12-31 1-2011-12-31 1-2012-12-31 2-2011-12-31 2-2012-12-31 3-2012-12-31
NA 50 60 NA 120 NA
lag(df.plm$data,-1)
##returns
Error in rep(1, ak) : invalid 'times' argument
I've also read that plm.data has replaced pdata.frame for some applications in plm. However, plm.data doesn't seem to work with the lag function at all:
df.plm<-plm.data(df,indexes=c("individual","date"))
lag(df.plm$data,1)
##returns
[1] 50 60 70 120 130 210
attr(,"tsp")
[1] 0 5 1
I would appreciate any help. If anyone has another suggestion for a package to use for lagging, I'm all ears. However, I do love plm because it automagically deals with lagging across multiple individuals and skips gaps in the time series.
EDIT2: lagging forward (=leading values) is implemented in plm CRAN releases >= 1.6-4 .
Functions are either lead() or lag() (latter with a negative integer for leading values).
Take care of any other packages attached that use the same function names. To be sure, you can refer to the function by the full namespace, e.g., plm::lead.
Examples from ?plm::lead:
# First, create a pdata.frame
data("EmplUK", package = "plm")
Em <- pdata.frame(EmplUK)
# Then extract a series, which becomes additionally a pseries
z <- Em$output
class(z)
# compute negative lags (= leading values)
lag(z, -1)
lead(z, 1) # same as line above
identical(lead(z, 1), lag(z, -1)) # TRUE