You can use some of the panel data commands like `xtsum` and `xtreg, fe` to do this. This will give you a couple numbers or their ratio, so this does not quite make for a very interesting graph. One approach would be to bootstrap the ratio and plot a histogram. I show how to do all this below.

    . webuse nlswork, clear
    (National Longitudinal Survey.  Young Women 14-26 years of age in 1968)
    
    . xtsum hours
    
    Variable         |      Mean   Std. Dev.       Min        Max |    Observations
    -----------------+--------------------------------------------+----------------
    hours    overall |  36.55956   9.869623          1        168 |     N =   28467
             between |             7.846585          1       83.5 |     n =    4710
             within  |             7.520712  -2.154726   130.0596 | T-bar = 6.04395
    

As you can see from comparing the SD between women and within women, the hours worked vary almost as much within each woman as across them.

You can also calculate the ratio using a fixed-effects regression:

    . xtreg hours, i(idcode) fe
    
    Fixed-effects (within) regression               Number of obs     =     28,467
    Group variable: idcode                          Number of groups  =      4,710
    
    R-sq:                                           Obs per group:
         within  = 0.0000                                         min =          1
         between = 0.0030                                         avg =        6.0
         overall =      .                                         max =         15
    
                                                    F(0,23757)        =       0.00
    corr(u_i, Xb)  =      .                         Prob > F          =          .
    
    ------------------------------------------------------------------------------
           hours |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
           _cons |   36.55956   .0487928   749.28   0.000     36.46392     36.6552
    -------------+----------------------------------------------------------------
         sigma_u |  7.8465853
         sigma_e |  8.2323986
             rho |  .47601892   (fraction of variance due to u_i)
    ------------------------------------------------------------------------------
    F test that all u_i=0: F(4709, 23757) = 3.64                 Prob > F = 0.0000
    
This says that about half of the variation in the data is within women, which is what we saw above. Working hours seem pretty unpredictable.

You can then bootstrap this ratio:
 
    . bootstrap ratio = e(rho), rep(500) seed(123) strata(idcode) saving("rhos.dta", replace): xtreg hours, i(idcode) fe
    (running xtreg on estimation sample)
    (note: file rhos.dta not found)
    
    Bootstrap replications (500)
    ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
    ..................................................    50
    ..................................................   100
    ..................................................   150
    ..................................................   200
    ..................................................   250
    ..................................................   300
    ..................................................   350
    ..................................................   400
    ..................................................   450
    ..................................................   500
    
    Bootstrap results
    
    Number of strata   =     4,710                  Number of obs     =     28,467
                                                    Replications      =        500
    
          command:  xtreg hours, i(idcode) fe
            ratio:  e(rho)
    
    ------------------------------------------------------------------------------
                 |   Observed   Bootstrap                         Normal-based
                 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
           ratio |   .4760189    .005062    94.04   0.000     .4660976    .4859402
    ------------------------------------------------------------------------------
    
The CI is pretty tight. You can also plot a histogram:

    . use "rhos.dta", clear
    (bootstrap: xtreg)
    
    . tw kdensity ratio

This gives you:
[![enter image description here][1]][1]
 


  [1]: https://i.sstatic.net/3C0yd.png