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Re: st: How to visualize standard errors as the number of bootstrap replications is increased

From   Ulrich Kohler <>
Subject   Re: st: How to visualize standard errors as the number of bootstrap replications is increased
Date   Wed, 23 May 2007 10:56:10 +0200 wrote:
> I would like to visualize the standard errors associated with a
> bootstrapped regression as the number of replications is increased. The
> purpose of this is to assess how many replications to perform. I wrote the
> following code designed for qreg regressions. I named it grbs for "graph
> bootstrap".
> -----------------------------
>  capture program drop grbs
>  program define grbs
>  version 9
>  postfile results n sa using data, replace
>  forvalues n=2(5)10{
>  noisily display "`n'" "`sa'"
>  set seed 123456789
>  quietly bootstrap "qreg $y $x" _b, reps(`n')
>  local n=e(N_reps)
>  local sa=e(sum_adev)
>  post results (`n') (`sa')
>  }
>  postclose results
>  end
>  use data, clear
>  graph twoway scatter sa n, xtitle("replications") ytitle("bootstrap
> standard error")
> -----------------------------
> I am no programmer -- the code was put together by using related bits of
> codes found here and there. There is clearly an error somewhere (or
> several) as the saved dataset "data.dta" appears with missing values.

I have three minor points and one more general. Let me start with the minor 

(1) I don' think you need a program for this. You can simply do this in a 

(2) Where you have typed e(N_reps) you probably mean e(reps). e(reps) is a 
matrix. You need to store the number of replications in a different way 
before you can post them in your postfile. For example:

. matrix x = e(reps)
. local x = x[1,1]
. post results (`x')

(3) e(sum_adev) is stored by -qreg-, but you have called -qreg- with 
-bootsrap- and -bootstrap- do not leave behind e(sum_adev).

My general point is to use a more direct approach:

. sysuse auto
. bootstrap "qreg rep weight" e(sum_adev), reps(10) saving(x)
. use x
. gen n = _n
. gen meansa = sum(_bs_2)/n  
. graph twoway scatter meansa n


Ulrich Kohler
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