Lag on multiple variables

library(dplyr,warn.conflicts = FALSE)
    
    # Create dummy data
    dtf <- data_frame(t = rep(2001:2003, 2),
                      c = rep(1:2,each=3),
                      x = rnorm(6))
    # lag over t
    dtf %>% 
        group_by(c) %>% mutate(xt_1 = lag(x))

## # A tibble: 6 x 4
## # Groups:   c [2]
##       t     c          x       xt_1
##   <int> <int>      <dbl>      <dbl>
## 1  2001     1  0.6976657         NA
## 2  2002     1  0.3243983  0.6976657
## 3  2003     1 -0.4733534  0.3243983
## 4  2001     2 -0.7919892         NA
## 5  2002     2  1.4096323 -0.7919892
## 6  2003     2  0.5602788  1.4096323

    # lag over c
    dtf %>% 
        group_by(t) %>% mutate(xc_1 = lag(x))

## # A tibble: 6 x 4
## # Groups:   t [3]
##       t     c          x       xc_1
##   <int> <int>      <dbl>      <dbl>
## 1  2001     1  0.6976657         NA
## 2  2002     1  0.3243983         NA
## 3  2003     1 -0.4733534         NA
## 4  2001     2 -0.7919892  0.6976657
## 5  2002     2  1.4096323  0.3243983
## 6  2003     2  0.5602788 -0.4733534

    computemodel <- function(dtf){
        dtf <- dtf %>%
            # lag over t 
            group_by(c) %>% mutate(xt_1 = lag(x)) %>% 
            # lag over c
            group_by(t) %>% mutate(xc_1 = lag(x)) %>% 
            # place function computation here
            mutate(result = xt_1 * xc_1)
        return(dtf)
    }
    computemodel(dtf)

## # A tibble: 6 x 6
## # Groups:   t [3]
##       t     c          x       xt_1       xc_1     result
##   <int> <int>      <dbl>      <dbl>      <dbl>      <dbl>
## 1  2001     1  0.6976657         NA         NA         NA
## 2  2002     1  0.3243983  0.6976657         NA         NA
## 3  2003     1 -0.4733534  0.3243983         NA         NA
## 4  2001     2 -0.7919892         NA  0.6976657         NA
## 5  2002     2  1.4096323 -0.7919892  0.3243983 -0.2569199
## 6  2003     2  0.5602788  1.4096323 -0.4733534 -0.6672543