[R] How to make a lagged variable in panel data?

[Ila Patnaik]

Suppose we observe N individuals, for each of which we have a
time-series. How do we correctly create a lagged value of the
time-series variable?

As an example, suppose I create:

  A <- data.frame(year=rep(c(1980:1984),3),
                  person= factor(sort(rep(1:3,5))),
                  wage=c(rnorm(15)))

  > A
     year person        wage
  1  1980      1  0.17923212
  2  1981      1  0.25610292
  3  1982      1  0.50833655
  4  1983      1 -0.42448395
  5  1984      1  0.49233532
  6  1980      2 -0.49928025
  7  1981      2  0.06842660
  8  1982      2  0.65677575
  9  1983      2  0.15947390
  10 1984      2 -0.46585116
  11 1980      3 -0.29052635
  12 1981      3 -0.27109203
  13 1982      3 -0.76168164
  14 1983      3  0.02294361
  15 1984      3  2.22828032

What I'd like to do is to make a lagged wage for each person, i.e., I
should get an additional variable A$wage.lag1:

  > A
     year person        wage       wage.lag1
  1  1980      1  0.17923212             NA
  2  1981      1  0.25610292     0.17923212
  3  1982      1  0.50833655     0.25610292
  4  1983      1 -0.42448395     0.50833655
  5  1984      1  0.49233532    -0.42448395
  6  1980      2 -0.49928025             NA
  7  1981      2  0.06842660    -0.49928025
  8  1982      2  0.65677575     0.06842660
  9  1983      2  0.15947390     0.65677575
  10 1984      2 -0.46585116     0.15947390
  11 1980      3 -0.29052635             NA
  12 1981      3 -0.27109203    -0.29052635
  13 1982      3 -0.76168164    -0.27109203
  14 1983      3  0.02294361    -0.76168164
  15 1984      3  2.22828032     0.02294361

I could think of writing code which does this "by hand", but it struck
me as a fundamental requirement when dealing with panel data, so
perhaps there is high level support for such a task?

I have been trying to learn groupedData objects and the tools that go
with them, but I didn't get a hint about how I would address such a
task.

                -Ila